WorldWideScience

Sample records for classifications severity weighting

  1. Fire severity classification: Uses and abuses

    Science.gov (United States)

    Theresa B. Jain; Russell T. Graham

    2003-01-01

    Burn severity (also referred to as fire severity) is not a single definition, but rather a concept and its classification is a function of the measured units unique to the system of interest. The systems include: flora and fauna, soil microbiology and hydrologic processes, atmospheric inputs, fire management, and society. Depending on the particular system of interest...

  2. 42 CFR 412.60 - DRG classification and weighting factors.

    Science.gov (United States)

    2010-10-01

    ... DRG classification system provides a DRG, and an appropriate weighting factor, for the group of cases... 42 Public Health 2 2010-10-01 2010-10-01 false DRG classification and weighting factors. 412.60... Determining Prospective Payment Federal Rates for Inpatient Operating Costs § 412.60 DRG classification and...

  3. Application Study of Fire Severity Classification

    International Nuclear Information System (INIS)

    Kim, In Hwan; Kim, Hyeong Taek; Jee, Moon Hak; Kim, Yun Jung

    2013-01-01

    This paper introduces the Fire Incidents Severity Classification Method for Korean NPPs that may be derived directly from the data fields and feasibility study for domestic uses. FEDB was characterized in more detail and assessed based on the significance of fire incidents in the updated database and five fire severity categories were defined. The logical approach to determine the fire severity starts from the most severe characteristics, namely challenging fires, and continues to define the less challenging and undetermined categories in progress. If the FEDB is utilized for Korean NPPs, the ways of Fire Severity Classification suggested in 2.4 above can be utilized for the quantitative fire risk analysis in future. The Fire Events Database (FEDB) is the primary source of fire data which are used for fire frequency in Fire PSA (Probabilistic Safety Assessment). The purpose of its development is to calculate the quantitative fire frequency at the comprehensive and consolidated source derived from the fire incident information available for Nuclear Power Plants (NPPs). Recently, the Fire Events Database (FEDB) was updated by Electric Power Research Institute (EPRI) and Nuclear Regulatory Commission (NRC) in U. S. The FEDB is intended to update the fire event history up to 2009. A significant enhancement to it is the reorganization and refinement of the database structure and data fields. It has been expanded and improved data fields, coding consistency, incident detail, data review fields, and reference data source traceability. It has been designed to better support several Fire PRA uses as well

  4. Text Categorization Using Weight Adjusted k-Nearest Neighbor Classification

    National Research Council Canada - National Science Library

    Han, Euihong; Karypis, George; Kumar, Vipin

    1999-01-01

    .... The authors present a nearest neighbor classification scheme for text categorization in which the importance of discriminating words is learned using mutual information and weight adjustment techniques...

  5. SEVERITY CLASSIFICATION OF MICROANEURYSMS USING NEURAL NETWORK

    Directory of Open Access Journals (Sweden)

    Shree Divya R

    2014-01-01

    Full Text Available Diabetic Retinopathy is one of the most common causes of blindness that leads to the loss of vision to the human eye. Several methods have been proposed to detect several defects of the human eye like hemorrhages, exudates etc. which are to be considered as the major symptoms. Among them, Microaneurysms should be considered as one of the severe condition for the early blindness. Several techniques have been proposed based on this, but they have certain drawbacks. A new technique called neural network taken for presentation, helps to detect and determine the severity of Microaneurysms which would be able to give a better performance than the existing techniques.

  6. Classification of Company Performance using Weighted Probabilistic Neural Network

    Science.gov (United States)

    Yasin, Hasbi; Waridi Basyiruddin Arifin, Adi; Warsito, Budi

    2018-05-01

    Classification of company performance can be judged by looking at its financial status, whether good or bad state. Classification of company performance can be achieved by some approach, either parametric or non-parametric. Neural Network is one of non-parametric methods. One of Artificial Neural Network (ANN) models is Probabilistic Neural Network (PNN). PNN consists of four layers, i.e. input layer, pattern layer, addition layer, and output layer. The distance function used is the euclidean distance and each class share the same values as their weights. In this study used PNN that has been modified on the weighting process between the pattern layer and the addition layer by involving the calculation of the mahalanobis distance. This model is called the Weighted Probabilistic Neural Network (WPNN). The results show that the company's performance modeling with the WPNN model has a very high accuracy that reaches 100%.

  7. Effect of weight loss on the severity of psoriasis

    DEFF Research Database (Denmark)

    Jensen, P; Zachariae, Claus; Christensen, R

    2013-01-01

    Psoriasis is associated with adiposity and weight gain increases the severity of psoriasis and the risk of incident psoriasis. Therefore, we aimed to measure the effect of weight reduction on the severity of psoriasis in obese patients with psoriasis.......Psoriasis is associated with adiposity and weight gain increases the severity of psoriasis and the risk of incident psoriasis. Therefore, we aimed to measure the effect of weight reduction on the severity of psoriasis in obese patients with psoriasis....

  8. Classification of EEG Signals using adaptive weighted distance nearest neighbor algorithm

    Directory of Open Access Journals (Sweden)

    E. Parvinnia

    2014-01-01

    Full Text Available Electroencephalogram (EEG signals are often used to diagnose diseases such as seizure, alzheimer, and schizophrenia. One main problem with the recorded EEG samples is that they are not equally reliable due to the artifacts at the time of recording. EEG signal classification algorithms should have a mechanism to handle this issue. It seems that using adaptive classifiers can be useful for the biological signals such as EEG. In this paper, a general adaptive method named weighted distance nearest neighbor (WDNN is applied for EEG signal classification to tackle this problem. This classification algorithm assigns a weight to each training sample to control its influence in classifying test samples. The weights of training samples are used to find the nearest neighbor of an input query pattern. To assess the performance of this scheme, EEG signals of thirteen schizophrenic patients and eighteen normal subjects are analyzed for the classification of these two groups. Several features including, fractal dimension, band power and autoregressive (AR model are extracted from EEG signals. The classification results are evaluated using Leave one (subject out cross validation for reliable estimation. The results indicate that combination of WDNN and selected features can significantly outperform the basic nearest-neighbor and the other methods proposed in the past for the classification of these two groups. Therefore, this method can be a complementary tool for specialists to distinguish schizophrenia disorder.

  9. [Determinant-based classification of acute pancreatitis severity. International multidisciplinary classification of acute pancreatitis severity: the 2013 German edition

    NARCIS (Netherlands)

    Layer, P.; Dellinger, E.P.; Forsmark, C.E.; Levy, P.; Maravi-Poma, E.; Shimosegawa, T.; Siriwardena, A.K.; Uomo, G.; Whitcomb, D.C.; Windsor, J.A.; Petrov, M.S.; Geenen, E.J.M. van; et al.,

    2013-01-01

    OBJECTIVE: The aim of this study was to develop a new international classification of acute pancreatitis severity on the basis of a sound conceptual framework, comprehensive review of published evidence, and worldwide consultation. BACKGROUND: The Atlanta definitions of acute pancreatitis severity

  10. Spatial Analysis of Accident Spots Using Weighted Severity Index ...

    African Journals Online (AJOL)

    ADOWIE PERE

    Spatial Analysis of Accident Spots Using Weighted Severity Index (WSI) and ... pedestrians avoiding the use of pedestrian bridges/aid even when they are available. ..... not minding an unforeseen obstruction, miscalculations and wrong break.

  11. [Severity classification of chronic obstructive pulmonary disease based on deep learning].

    Science.gov (United States)

    Ying, Jun; Yang, Ceyuan; Li, Quanzheng; Xue, Wanguo; Li, Tanshi; Cao, Wenzhe

    2017-12-01

    In this paper, a deep learning method has been raised to build an automatic classification algorithm of severity of chronic obstructive pulmonary disease. Large sample clinical data as input feature were analyzed for their weights in classification. Through feature selection, model training, parameter optimization and model testing, a classification prediction model based on deep belief network was built to predict severity classification criteria raised by the Global Initiative for Chronic Obstructive Lung Disease (GOLD). We get accuracy over 90% in prediction for two different standardized versions of severity criteria raised in 2007 and 2011 respectively. Moreover, we also got the contribution ranking of different input features through analyzing the model coefficient matrix and confirmed that there was a certain degree of agreement between the more contributive input features and the clinical diagnostic knowledge. The validity of the deep belief network model was proved by this result. This study provides an effective solution for the application of deep learning method in automatic diagnostic decision making.

  12. A Weighted Block Dictionary Learning Algorithm for Classification

    OpenAIRE

    Shi, Zhongrong

    2016-01-01

    Discriminative dictionary learning, playing a critical role in sparse representation based classification, has led to state-of-the-art classification results. Among the existing discriminative dictionary learning methods, two different approaches, shared dictionary and class-specific dictionary, which associate each dictionary atom to all classes or a single class, have been studied. The shared dictionary is a compact method but with lack of discriminative information; the class-specific dict...

  13. Joint learning and weighting of visual vocabulary for bag-of-feature based tissue classification

    KAUST Repository

    Wang, Jim Jing-Yan; Bensmail, Halima; Gao, Xin

    2013-01-01

    their power in this field. Two important issues of bag-of-feature strategy for tissue classification are investigated in this paper: the visual vocabulary learning and weighting, which are always considered independently in traditional methods by neglecting

  14. 42 CFR 412.517 - Revision of LTC-DRG group classifications and weighting factors.

    Science.gov (United States)

    2010-10-01

    ... 42 Public Health 2 2010-10-01 2010-10-01 false Revision of LTC-DRG group classifications and... the LTC-DRG classifications and recalibration of the weighting factors described in paragraph (a) of... SERVICES Prospective Payment System for Long-Term Care Hospitals § 412.517 Revision of LTC-DRG group...

  15. 42 CFR 419.31 - Ambulatory payment classification (APC) system and payment weights.

    Science.gov (United States)

    2010-10-01

    ... 42 Public Health 3 2010-10-01 2010-10-01 false Ambulatory payment classification (APC) system and... Outpatient Services § 419.31 Ambulatory payment classification (APC) system and payment weights. (a) APC... of resource use into APC groups. Except as specified in paragraph (a)(2) of this section, items and...

  16. Implementation of several mathematical algorithms to breast tissue density classification

    International Nuclear Information System (INIS)

    Quintana, C.; Redondo, M.; Tirao, G.

    2014-01-01

    The accuracy of mammographic abnormality detection methods is strongly dependent on breast tissue characteristics, where a dense breast tissue can hide lesions causing cancer to be detected at later stages. In addition, breast tissue density is widely accepted to be an important risk indicator for the development of breast cancer. This paper presents the implementation and the performance of different mathematical algorithms designed to standardize the categorization of mammographic images, according to the American College of Radiology classifications. These mathematical techniques are based on intrinsic properties calculations and on comparison with an ideal homogeneous image (joint entropy, mutual information, normalized cross correlation and index Q) as categorization parameters. The algorithms evaluation was performed on 100 cases of the mammographic data sets provided by the Ministerio de Salud de la Provincia de Córdoba, Argentina—Programa de Prevención del Cáncer de Mama (Department of Public Health, Córdoba, Argentina, Breast Cancer Prevention Program). The obtained breast classifications were compared with the expert medical diagnostics, showing a good performance. The implemented algorithms revealed a high potentiality to classify breasts into tissue density categories. - Highlights: • Breast density classification can be obtained by suitable mathematical algorithms. • Mathematical processing help radiologists to obtain the BI-RADS classification. • The entropy and joint entropy show high performance for density classification

  17. [Intractable diarrhoea and severe weight loss by roflumilast].

    Science.gov (United States)

    Horna, Oihana; Toyas, Carla

    2013-08-04

    Roflumilast is a recently marketed drug, indicated for maintenance treatment of severe chronic obstructive pulmonary disease associated with chronic bronchitis in adult patients with a history of frequent exacerbations as add on to bronchodilator treatment. The safety data of this drug have always been subjected to controversy and concerns. The Food and Drug Administration rejected the drug after the first evaluation, asking the company to clarify the adverse reactions during the investigation process, the European Medicines Agency approved the drug including a Risk Management Plan, designed to promote a safe use of the drug. During the first months after the marketing process, the Spanish Pharmacovigilance System has already been acquainted of several adverse events notifications; therefore, these patients may be closely monitored, mainly because of digestive and psychiatric disorders. Here we report the case of a female patient who showed a serious digestive clinical profile and a severe weight loss, more than 25% of her initial weight, when a treatment with roflumilast was started. The suspicion of a side effect as the cause of the reported clinical profile and its resolution required 3 hospital admissions. Copyright © 2013 Elsevier España, S.L. All rights reserved.

  18. Bilateral weighted radiographs are required for accurate classification of acromioclavicular separation: an observational study of 59 cases.

    Science.gov (United States)

    Ibrahim, E F; Forrest, N P; Forester, A

    2015-10-01

    Misinterpretation of the Rockwood classification system for acromioclavicular joint (ACJ) separations has resulted in a trend towards using unilateral radiographs for grading. Further, the use of weighted views to 'unmask' a grade III injury has fallen out of favour. Recent evidence suggests that many radiographic grade III injuries represent only a partial injury to the stabilising ligaments. This study aimed to determine (1) whether accurate classification is possible on unilateral radiographs and (2) the efficacy of weighted bilateral radiographs in unmasking higher-grade injuries. Complete bilateral non-weighted and weighted sets of radiographs for patients presenting with an acromioclavicular separation over a 10-year period were analysed retrospectively, and they were graded I-VI according to Rockwood's criteria. Comparison was made between grading based on (1) a single antero-posterior (AP) view of the injured side, (2) bilateral non-weighted views and (3) bilateral weighted views. Radiographic measurements for cases that changed grade after weighted views were statistically compared to see if this could have been predicted beforehand. Fifty-nine sets of radiographs on 59 patients (48 male, mean age of 33 years) were included. Compared with unilateral radiographs, non-weighted bilateral comparison films resulted in a grade change for 44 patients (74.5%). Twenty-eight of 56 patients initially graded as I, II or III were upgraded to grade V and two of three initial grade V patients were downgraded to grade III. The addition of a weighted view further upgraded 10 patients to grade V. No grade II injury was changed to grade III and no injury of any severity was downgraded by a weighted view. Grade III injuries upgraded on weighted views had a significantly greater baseline median percentage coracoclavicular distance increase than those that were not upgraded (80.7% vs. 55.4%, p=0.015). However, no cut-off point for this value could be identified to predict an

  19. Determinant-Based Classification of Acute Pancreatitis Severity: An International Multidisciplinary Consultation

    NARCIS (Netherlands)

    Dellinger, E.P.; Forsmark, C.E.; Layer, P.; Levy, P.; Maravi-Poma, E.; Petrov, M.S.; Shimosegawa, T.; Siriwardena, A.K.; Uomo, G.; Whitcomb, D.C.; Windsor, J.A.; Geenen, E.J.M. van; et al.,

    2012-01-01

    OBJECTIVE:: To develop a new international classification of acute pancreatitis severity on the basis of a sound conceptual framework, comprehensive review of published evidence, and worldwide consultation. BACKGROUND:: The Atlanta definitions of acute pancreatitis severity are ingrained in the

  20. Accuracy of automated classification of major depressive disorder as a function of symptom severity

    Directory of Open Access Journals (Sweden)

    Rajamannar Ramasubbu, MD, FRCPC, MSc

    2016-01-01

    Conclusions: Binary linear SVM classifiers achieved significant classification of very severe depression with resting-state fMRI, but the contribution of brain measurements may have limited potential in differentiating patients with less severe depression from healthy controls.

  1. Implementation of several mathematical algorithms to breast tissue density classification

    Science.gov (United States)

    Quintana, C.; Redondo, M.; Tirao, G.

    2014-02-01

    The accuracy of mammographic abnormality detection methods is strongly dependent on breast tissue characteristics, where a dense breast tissue can hide lesions causing cancer to be detected at later stages. In addition, breast tissue density is widely accepted to be an important risk indicator for the development of breast cancer. This paper presents the implementation and the performance of different mathematical algorithms designed to standardize the categorization of mammographic images, according to the American College of Radiology classifications. These mathematical techniques are based on intrinsic properties calculations and on comparison with an ideal homogeneous image (joint entropy, mutual information, normalized cross correlation and index Q) as categorization parameters. The algorithms evaluation was performed on 100 cases of the mammographic data sets provided by the Ministerio de Salud de la Provincia de Córdoba, Argentina—Programa de Prevención del Cáncer de Mama (Department of Public Health, Córdoba, Argentina, Breast Cancer Prevention Program). The obtained breast classifications were compared with the expert medical diagnostics, showing a good performance. The implemented algorithms revealed a high potentiality to classify breasts into tissue density categories.

  2. Asian Americans: Diabetes Prevalence Across U.S. and World Health Organization Weight Classifications

    OpenAIRE

    Oza-Frank, Reena; Ali, Mohammed K.; Vaccarino, Viola; Narayan, K.M. Venkat

    2009-01-01

    OBJECTIVE To compare diabetes prevalence among Asian Americans by World Health Organization and U.S. BMI classifications. RESEARCH DESIGN AND METHODS Data on Asian American adults (n = 7,414) from the National Health Interview Survey for 1997–2005 were analyzed. Diabetes prevalence was estimated across weight and ethnic group strata. RESULTS Regardless of BMI classification, Asian Indians and Filipinos had the highest prevalence of overweight (34–47 and 35–47%, respectively, compared with 20–...

  3. Algorithm for Optimizing Bipolar Interconnection Weights with Applications in Associative Memories and Multitarget Classification

    Science.gov (United States)

    Chang, Shengjiang; Wong, Kwok-Wo; Zhang, Wenwei; Zhang, Yanxin

    1999-08-01

    An algorithm for optimizing a bipolar interconnection weight matrix with the Hopfield network is proposed. The effectiveness of this algorithm is demonstrated by computer simulation and optical implementation. In the optical implementation of the neural network the interconnection weights are biased to yield a nonnegative weight matrix. Moreover, a threshold subchannel is added so that the system can realize, in real time, the bipolar weighted summation in a single channel. Preliminary experimental results obtained from the applications in associative memories and multitarget classification with rotation invariance are shown.

  4. Radiotherapy on the neck nodes predicts severe weight loss in patients with early stage laryngeal cancer

    International Nuclear Information System (INIS)

    Langius, Jacqueline A.E.; Doornaert, Patricia; Spreeuwenberg, Marieke D.; Langendijk, Johannes A.; Leemans, C. Rene; Schueren, Marian A.E. van Bokhorst-de van der

    2010-01-01

    Background and purpose: Although patients with early stage (T1/T2) laryngeal cancer (LC) are thought to have a low incidence of malnutrition, severe weight loss is observed in a subgroup of these patients during radiotherapy (RT). The objective of this study was to evaluate weight loss and nutrition-related symptoms in patients with T1/T2 LC during RT and to select predictive factors for early identification of malnourished patients. Methods: Of all patients with T1/T2 LC, who received primary RT between 1999 and 2007, the following characteristics were recorded: sex, age, TNM classification, tumour location, radiation schedule, performance status, quality of life, weight loss, and nutrition-related symptoms. The association between baseline characteristics and malnutrition (>5% weight loss during RT) was investigated by Cox regression analysis. Results: The study population consisted of 238 patients. During RT, 44% of patients developed malnutrition. Tumour location, TNM classification, RT on the neck nodes, RT dose, nausea/vomiting, pain, swallowing, senses problems, trouble with social eating, dry mouth and the use of painkillers were all significantly associated with malnutrition. In the multivariate analysis, RTs on both the neck nodes (HR 4.16, 95% CI 2.62-6.60) and dry mouth (HR 1.72, 95% CI 1.14-2.60) remained predictive. Nevertheless, RT on the neck nodes alone resulted in the best predictive model for malnutrition scores. Conclusions: Patients with early stage laryngeal cancer are at risk of malnutrition during radiotherapy. Radiotherapy on the neck nodes is the best predictor of malnutrition during radiotherapy. Therefore, we suggest to offer nutritional counselling to all the patients who receive nodal irradiation.

  5. Support vector machine for breast cancer classification using diffusion-weighted MRI histogram features: Preliminary study.

    Science.gov (United States)

    Vidić, Igor; Egnell, Liv; Jerome, Neil P; Teruel, Jose R; Sjøbakk, Torill E; Østlie, Agnes; Fjøsne, Hans E; Bathen, Tone F; Goa, Pål Erik

    2018-05-01

    Diffusion-weighted MRI (DWI) is currently one of the fastest developing MRI-based techniques in oncology. Histogram properties from model fitting of DWI are useful features for differentiation of lesions, and classification can potentially be improved by machine learning. To evaluate classification of malignant and benign tumors and breast cancer subtypes using support vector machine (SVM). Prospective. Fifty-one patients with benign (n = 23) and malignant (n = 28) breast tumors (26 ER+, whereof six were HER2+). Patients were imaged with DW-MRI (3T) using twice refocused spin-echo echo-planar imaging with echo time / repetition time (TR/TE) = 9000/86 msec, 90 × 90 matrix size, 2 × 2 mm in-plane resolution, 2.5 mm slice thickness, and 13 b-values. Apparent diffusion coefficient (ADC), relative enhanced diffusivity (RED), and the intravoxel incoherent motion (IVIM) parameters diffusivity (D), pseudo-diffusivity (D*), and perfusion fraction (f) were calculated. The histogram properties (median, mean, standard deviation, skewness, kurtosis) were used as features in SVM (10-fold cross-validation) for differentiation of lesions and subtyping. Accuracies of the SVM classifications were calculated to find the combination of features with highest prediction accuracy. Mann-Whitney tests were performed for univariate comparisons. For benign versus malignant tumors, univariate analysis found 11 histogram properties to be significant differentiators. Using SVM, the highest accuracy (0.96) was achieved from a single feature (mean of RED), or from three feature combinations of IVIM or ADC. Combining features from all models gave perfect classification. No single feature predicted HER2 status of ER + tumors (univariate or SVM), although high accuracy (0.90) was achieved with SVM combining several features. Importantly, these features had to include higher-order statistics (kurtosis and skewness), indicating the importance to account for heterogeneity. Our

  6. Joint learning and weighting of visual vocabulary for bag-of-feature based tissue classification

    KAUST Repository

    Wang, Jim Jing-Yan

    2013-12-01

    Automated classification of tissue types of Region of Interest (ROI) in medical images has been an important application in Computer-Aided Diagnosis (CAD). Recently, bag-of-feature methods which treat each ROI as a set of local features have shown their power in this field. Two important issues of bag-of-feature strategy for tissue classification are investigated in this paper: the visual vocabulary learning and weighting, which are always considered independently in traditional methods by neglecting the inner relationship between the visual words and their weights. To overcome this problem, we develop a novel algorithm, Joint-ViVo, which learns the vocabulary and visual word weights jointly. A unified objective function based on large margin is defined for learning of both visual vocabulary and visual word weights, and optimized alternately in the iterative algorithm. We test our algorithm on three tissue classification tasks: classifying breast tissue density in mammograms, classifying lung tissue in High-Resolution Computed Tomography (HRCT) images, and identifying brain tissue type in Magnetic Resonance Imaging (MRI). The results show that Joint-ViVo outperforms the state-of-art methods on tissue classification problems. © 2013 Elsevier Ltd.

  7. Severity of Airflow Obstruction in Chronic Obstructive Pulmonary Disease (COPD): Proposal for a New Classification.

    Science.gov (United States)

    Coton, Sonia; Vollmer, William M; Bateman, Eric; Marks, Guy B; Tan, Wan; Mejza, Filip; Juvekar, Sanjay; Janson, Christer; Mortimer, Kevin; P A, Mahesh; Buist, A Sonia; Burney, Peter G J

    2017-10-01

    Current classifications of Chronic Obstructive Pulmonary Disease (COPD) severity are complex and do not grade levels of obstruction. Obstruction is a simpler construct and independent of ethnicity. We constructed an index of obstruction severity based on the FEV 1 /FVC ratio, with cut-points dividing the Burden of Obstructive Lung Disease (BOLD) study population into four similarly sized strata to those created by the GOLD criteria that uses FEV 1 . We measured the agreement between classifications and the validity of the FEV 1 -based classification in identifying the level of obstruction as defined by the new groupings. We compared the strengths of association of each classification with quality of life (QoL), MRC dyspnoea score and the self-reported exacerbation rate. Agreement between classifications was only fair. FEV 1 -based criteria for moderate COPD identified only 79% of those with moderate obstruction and misclassified half of the participants with mild obstruction as having more severe COPD. Both scales were equally strongly associated with QoL, exertional dyspnoea and respiratory exacerbations. Severity assessed using the FEV 1 /FVC ratio is only in moderate agreement with the severity assessed using FEV 1 but is equally strongly associated with other outcomes. Severity assessed using the FEV 1 /FVC ratio is likely to be independent of ethnicity.

  8. A hybrid clustering and classification approach for predicting crash injury severity on rural roads.

    Science.gov (United States)

    Hasheminejad, Seyed Hessam-Allah; Zahedi, Mohsen; Hasheminejad, Seyed Mohammad Hossein

    2018-03-01

    As a threat for transportation system, traffic crashes have a wide range of social consequences for governments. Traffic crashes are increasing in developing countries and Iran as a developing country is not immune from this risk. There are several researches in the literature to predict traffic crash severity based on artificial neural networks (ANNs), support vector machines and decision trees. This paper attempts to investigate the crash injury severity of rural roads by using a hybrid clustering and classification approach to compare the performance of classification algorithms before and after applying the clustering. In this paper, a novel rule-based genetic algorithm (GA) is proposed to predict crash injury severity, which is evaluated by performance criteria in comparison with classification algorithms like ANN. The results obtained from analysis of 13,673 crashes (5600 property damage, 778 fatal crashes, 4690 slight injuries and 2605 severe injuries) on rural roads in Tehran Province of Iran during 2011-2013 revealed that the proposed GA method outperforms other classification algorithms based on classification metrics like precision (86%), recall (88%) and accuracy (87%). Moreover, the proposed GA method has the highest level of interpretation, is easy to understand and provides feedback to analysts.

  9. International Multidisciplinary Classification of Acute Pancreatitis Severity: The 2013 Spanish Edition

    NARCIS (Netherlands)

    Maraví-Poma, E.; Patchen Dellinger, E.; Forsmark, C. E.; Layer, P.; Lévy, P.; Shimosegawa, T.; Siriwardena, A. K.; Uomo, G.; Whitcomb, D. C.; Windsor, J. A.; Petrov, M. S.; Abu Hilal, M.; Abu-Zidan, F. M.; Acosta, J. M.; Ainsworth, A. P.; Aizcorbe Garralda, M.; Alagozlu, H.; Al'aref, S. J.; Albeniz Arbizu, E.; Alhajeri, A.; Almeida, J. L.; Ammori, B. J.; Andersson, R.; Ardengh, J. C.; Arroyo-Sanchez, A. S.; Arvanitakis, M.; Ashley, S. W.; Aygencel, G.; Ayoub, W. A.; Baillie, J.; Bala, M.; Ball, C. G.; Banks, P. A.; Baron, T. H.; Barreto, S. G.; Basaranoglu, M.; Beger, H. G.; Bernal Monterde, V.; Besselink, M. G.; Bharwani, N.; Bhasin, D. K.; Bong, J. J.; Botoi, G.; Bruennler, T.; Bruno, M. J.; Cairoli, E.; Carter, C. R.; Cernea, D.; Chari, S. T.; Chooklin, S.

    2014-01-01

    Objective: To develop a new classification of acute pancreatitis severity on the basis of a sound conceptual framework, comprehensive review of the published evidence, and worldwide consultation. Backgrounds: The Atlanta definitions of acute pancreatitis severity are ingrained in the lexicon of

  10. Tree mortality based fire severity classification for forest inventories: A Pacific Northwest national forests example

    Science.gov (United States)

    Thomas R. Whittier; Andrew N. Gray

    2016-01-01

    Determining how the frequency, severity, and extent of forest fires are changing in response to changes in management and climate is a key concern in many regions where fire is an important natural disturbance. In the USA the only national-scale fire severity classification uses satellite image changedetection to produce maps for large (>400 ha) fires, and is...

  11. [Multidisciplinar international classification of the severity of acute pancreatitis: Italian version 2013].

    Science.gov (United States)

    Uomo, G; Patchen Dellinger, E; Forsmark, C E; Layer, P; Lévy, P; Maravì-Poma, E; Shimosegawa, T; Siriwardena, A K; Whitcomb, D C; Windsor, J A; Petrov, M S

    2013-12-01

    The aim of this paper was to present the 2013 Italian edition of a new international classification of acute pancreatitis severity. The Atlanta definitions of acute pancreatitis severity are ingrained in the lexicon of pancreatologists but suboptimal because these definitions are based on empiric description of occurrences that are merely associated with severity. A personal invitation to contribute to the development of a new international classification of acute pancreatitis severity was sent to all surgeons, gastroenterologists, internists, intensivists, and radiologists who are currently active in clinical research on acute pancreatitis. A global web-based survey was conducted and a dedicated international symposium was organized to bring contributors from different disciplines together and discuss the concept and definitions. The new international classification is based on the actual local and systemic determinants of severity, rather than description of events that are correlated with severity. The local determinant relates to whether there is (peri)pancreatic necrosis or not, and if present, whether it is sterile or infected. The systemic determinant relates to whether there is organ failure or not, and if present, whether it is transient or persistent. The presence of one determinant can modify the effect of another such that the presence of both infected (peri)pancreatic necrosis and persistent organ failure have a greater effect on severity than either determinant alone. The derivation of a classification based on the above principles results in 4 categories of severity-mild, moderate, severe, and critical. This classification provides a set of concise up-to-date definitions of all the main entities pertinent to classifying the severity of acute pancreatitis in clinical practice and research.

  12. Investigating Perceived vs. Medical Weight Status Classification among College Students: Room for Improvement Exists among the Overweight and Obese

    Science.gov (United States)

    Duffrin, Christopher; Eakin, Angela; Bertrand, Brenda; Barber-Heidel, Kimberly; Carraway-Stage, Virginia

    2011-01-01

    The American College Health Association estimated that 31% of college students are overweight or obese. It is important that students have a correct perception of body weight status as extra weight has potential adverse health effects. This study assessed accuracy of perceived weight status versus medical classification among 102 college students.…

  13. The impact of weight classification on safety: timing steps to adapt to external constraints

    Science.gov (United States)

    Gill, S.V.

    2015-01-01

    Objectives: The purpose of the current study was to evaluate how weight classification influences safety by examining adults’ ability to meet a timing constraint: walking to the pace of an audio metronome. Methods: With a cross-sectional design, walking parameters were collected as 55 adults with normal (n=30) and overweight (n=25) body mass index scores walked to slow, normal, and fast audio metronome paces. Results: Between group comparisons showed that at the fast pace, those with overweight body mass index (BMI) had longer double limb support and stance times and slower cadences than the normal weight group (all psmetronome paces revealed that participants who were overweight had higher cadences at the slow and fast paces (all ps<0.05). Conclusions: Findings suggest that those with overweight BMI alter their gait to maintain biomechanical stability. Understanding how excess weight influences gait adaptation can inform interventions to improve safety for individuals with obesity. PMID:25730658

  14. A note on multi-criteria inventory classification using weighted linear optimization

    Directory of Open Access Journals (Sweden)

    Rezaei Jafar

    2010-01-01

    Full Text Available Recently, Ramanathan (R., Ramanathan, ABC inventory classification with multiple-criteria using weighted linear optimization, Computer and Operations Research, 33(3 (2006 695-700 introduced a simple DEA-like model to classify inventory items on the basis of multiple criteria. However, the classification results produced by Ramanathan are not consistent with the domination concept encouraged some researchers to extend his model. In this paper, we produce the correct results and compare them to the original results and those of the extended models. We also improve this model to rank items with an optimal score of 1 using a cross-efficiency technique. The classification results are considerably different from the original results. Despite the fact that the correct results are obtained in this paper, there is no significant difference between the original model and its extensions, while the original model is more simple and suitable for the situations in which decision-maker cannot assign specific weights to individual criteria.

  15. Using ELM-based weighted probabilistic model in the classification of synchronous EEG BCI.

    Science.gov (United States)

    Tan, Ping; Tan, Guan-Zheng; Cai, Zi-Xing; Sa, Wei-Ping; Zou, Yi-Qun

    2017-01-01

    Extreme learning machine (ELM) is an effective machine learning technique with simple theory and fast implementation, which has gained increasing interest from various research fields recently. A new method that combines ELM with probabilistic model method is proposed in this paper to classify the electroencephalography (EEG) signals in synchronous brain-computer interface (BCI) system. In the proposed method, the softmax function is used to convert the ELM output to classification probability. The Chernoff error bound, deduced from the Bayesian probabilistic model in the training process, is adopted as the weight to take the discriminant process. Since the proposed method makes use of the knowledge from all preceding training datasets, its discriminating performance improves accumulatively. In the test experiments based on the datasets from BCI competitions, the proposed method is compared with other classification methods, including the linear discriminant analysis, support vector machine, ELM and weighted probabilistic model methods. For comparison, the mutual information, classification accuracy and information transfer rate are considered as the evaluation indicators for these classifiers. The results demonstrate that our method shows competitive performance against other methods.

  16. Weight loss and severe jaundice in a patient with hyperthyroidism.

    Science.gov (United States)

    Breidert, M; Offensperger, S; Blum, H E; Fischer, R

    2011-09-01

    Thyrotoxicosis may significantly alter hepatic function and is associated with autoimmune disorders of the liver. We report the case of a thyrotoxic patient with Graves' disease and histologically established cholestatic hepatitis. Medical treatment of hyperthyroidism normalized liver function tests. In patients with elevated liver function parameters and jaundice of unknown origin, thyroid function should generally be tested. Moreover, medical treatment of hyperthyroidism with thyrostatics may cause severe hepatitis whereas untreated hyperthyroid patients are at risk of developing chronic liver failure. © Georg Thieme Verlag KG Stuttgart · New York.

  17. [International multidisciplinary classification of acute pancreatitis severity: the 2013 Spanish edition].

    Science.gov (United States)

    Maraví-Poma, E; Patchen Dellinger, E; Forsmark, C E; Layer, P; Lévy, P; Shimosegawa, T; Siriwardena, A K; Uomo, G; Whitcomb, D C; Windsor, J A; Petrov, M S

    2014-05-01

    To develop a new classification of acute pancreatitis severity on the basis of a sound conceptual framework, comprehensive review of the published evidence, and worldwide consultation. The Atlanta definitions of acute pancreatitis severity are ingrained in the lexicon of specialist in pancreatic diseases, but are suboptimal because these definitions are based on the empiric description of events not associated with severity. A personal invitation to contribute to the development of a new classification of acute pancreatitis severity was sent to all surgeons, gastroenterologists, internists, intensivists and radiologists currently active in the field of clinical acute pancreatitis. The invitation was not limited to members of certain associations or residents of certain countries. A global web-based survey was conducted, and a dedicated international symposium was organized to bring contributors from different disciplines together and discuss the concept and definitions. The new classification of severity is based on the actual local and systemic determinants of severity, rather than on the description of events that are non-causally associated with severity. The local determinant relates to whether there is (peri) pancreatic necrosis or not, and if present, whether it is sterile or infected. The systemic determinant relates to whether there is organ failure or not, and if present, whether it is transient or persistent. The presence of one determinant can modify the effect of another, whereby the presence of both infected (peri) pancreatic necrosis and persistent organ failure has a greater impact upon severity than either determinant alone. The derivation of a classification based on the above principles results in four categories of severity: mild, moderate, severe, and critical. This classification is the result of a consultative process among specialists in pancreatic diseases from 49 countries spanning North America, South America, Europe, Asia, Oceania and

  18. Dengue disease severity in Indonesian children: An evaluation of the World Health Organization classification system

    NARCIS (Netherlands)

    T.E. Setiati (Tatty); A.T.A. Mairuhu; P. Koraka (Penelope); M. Supriatna (Mohamad); M.R. Mac Gillavry (Melvin); D.P.M. Brandjes (Dees); A.D.M.E. Osterhaus (Albert); J.W.M. van der Meer (Jos); E.C.M. van Gorp (Eric); A. Soemantri (Augustinus)

    2007-01-01

    textabstractBackground: Dengue disease severity is usually classified using criteria set up by the World Health Organization (WHO). We aimed to assess the diagnostic accuracy of the WHO classification system and modifications to this system, and evaluated their potential practical usefulness.

  19. Focal liver lesions segmentation and classification in nonenhanced T2-weighted MRI.

    Science.gov (United States)

    Gatos, Ilias; Tsantis, Stavros; Karamesini, Maria; Spiliopoulos, Stavros; Karnabatidis, Dimitris; Hazle, John D; Kagadis, George C

    2017-07-01

    To automatically segment and classify focal liver lesions (FLLs) on nonenhanced T2-weighted magnetic resonance imaging (MRI) scans using a computer-aided diagnosis (CAD) algorithm. 71 FLLs (30 benign lesions, 19 hepatocellular carcinomas, and 22 metastases) on T2-weighted MRI scans were delineated by the proposed CAD scheme. The FLL segmentation procedure involved wavelet multiscale analysis to extract accurate edge information and mean intensity values for consecutive edges computed using horizontal and vertical analysis that were fed into the subsequent fuzzy C-means algorithm for final FLL border extraction. Texture information for each extracted lesion was derived using 42 first- and second-order textural features from grayscale value histogram, co-occurrence, and run-length matrices. Twelve morphological features were also extracted to capture any shape differentiation between classes. Feature selection was performed with stepwise multilinear regression analysis that led to a reduced feature subset. A multiclass Probabilistic Neural Network (PNN) classifier was then designed and used for lesion classification. PNN model evaluation was performed using the leave-one-out (LOO) method and receiver operating characteristic (ROC) curve analysis. The mean overlap between the automatically segmented FLLs and the manual segmentations performed by radiologists was 0.91 ± 0.12. The highest classification accuracies in the PNN model for the benign, hepatocellular carcinoma, and metastatic FLLs were 94.1%, 91.4%, and 94.1%, respectively, with sensitivity/specificity values of 90%/97.3%, 89.5%/92.2%, and 90.9%/95.6% respectively. The overall classification accuracy for the proposed system was 90.1%. Our diagnostic system using sophisticated FLL segmentation and classification algorithms is a powerful tool for routine clinical MRI-based liver evaluation and can be a supplement to contrast-enhanced MRI to prevent unnecessary invasive procedures. © 2017 American

  20. Impact of low-weight severity and menstrual status on bone in adolescent girls with anorexia nervosa.

    Science.gov (United States)

    Kandemir, Nurgun; Becker, Kendra; Slattery, Meghan; Tulsiani, Shreya; Singhal, Vibha; Thomas, Jennifer J; Coniglio, Kathryn; Lee, Hang; Miller, Karen K; Eddy, Kamryn T; Klibanski, Anne; Misra, Madhusmita

    2017-04-01

    Clinicians currently use different low-weight cut-offs both to diagnose anorexia nervosa (AN) and to determine AN severity in adolescent girls. The purpose of this study was to evaluate the clinical utility of existing cut-offs and severity criteria by determining which are most strongly associated with risk for low bone mineral density (BMD). Height adjusted BMD Z scores were calculated for 352 females: 262 with AN and 90 healthy controls (controls) (12-20.5 years), using data from the BMD in Childhood Study, for the lumbar spine, whole body less head, and total hip. For most cut-offs used to define low weight (5th or 10th BMI percentile, BMI of 17.5 or 18.5, and 85 or 90% of median BMI), AN had lower BMD Z scores than controls. AN at >85 or >90% expected body weight for height (EBW-Ht) did not differ in BMD Z scores from controls, but differed significantly from AN at ≤85 or ≤90% EBW-Ht. Among AN, any amenorrhea was associated with lower BMD. AN had lower BMD than controls across DSM-5 and The Society for Adolescent Health and Medicine (SAHM) severity categories. The SAHM moderate severity classification was differentiated from the mildly malnourished classification by lower BMD at hip and spine sites. Amenorrhea and %EBW-Ht ≤ 85 or ≤ 90% are markers of severity of bone loss within AN. Among severity categories, BMI Z scores (SAHM) may have the greatest utility in assessing the degree of malnutrition in adolescent girls that corresponds to lower BMD. © 2017 Wiley Periodicals, Inc.

  1. Incidence and severity of stage IV bronchopulmonary dysplasia in infants of very low birth weight

    International Nuclear Information System (INIS)

    Parker, B.R.; Stevens, S.K.; Northway, W.H.

    1989-01-01

    To evaluate the incidence and severity of stage IV bronchopulmonary dysplasia (BPD) in infants of very low birth weight, the authors reviewed the clinical course and chest radiographs of 138 such infants. In the lowest weight group ( 1500 g, 10%). However, the severity of BPD (graded by the Toce-Edwards Scale) was highest (6.3) in the < 1500-g group (< 900 g, 5.4; 1200-1500 g, 5.9). These data showed that, although the incidence of stage IV BVD significantly decreased as birth weight increased, the severity of chronic changes was independent of birth weight

  2. Learning Word Embeddings with Chi-Square Weights for Healthcare Tweet Classification

    Directory of Open Access Journals (Sweden)

    Sicong Kuang

    2017-08-01

    Full Text Available Twitter is a popular source for the monitoring of healthcare information and public disease. However, there exists much noise in the tweets. Even though appropriate keywords appear in the tweets, they do not guarantee the identification of a truly health-related tweet. Thus, the traditional keyword-based classification task is largely ineffective. Algorithms for word embeddings have proved to be useful in many natural language processing (NLP tasks. We introduce two algorithms based on an existing word embedding learning algorithm: the continuous bag-of-words model (CBOW. We apply the proposed algorithms to the task of recognizing healthcare-related tweets. In the CBOW model, the vector representation of words is learned from their contexts. To simplify the computation, the context is represented by an average of all words inside the context window. However, not all words in the context window contribute equally to the prediction of the target word. Greedily incorporating all the words in the context window will largely limit the contribution of the useful semantic words and bring noisy or irrelevant words into the learning process, while existing word embedding algorithms also try to learn a weighted CBOW model. Their weights are based on existing pre-defined syntactic rules while ignoring the task of the learned embedding. We propose learning weights based on the words’ relative importance in the classification task. Our intuition is that such learned weights place more emphasis on words that have comparatively more to contribute to the later task. We evaluate the embeddings learned from our algorithms on two healthcare-related datasets. The experimental results demonstrate that embeddings learned from the proposed algorithms outperform existing techniques by a relative accuracy improvement of over 9%.

  3. An anthropometric classification of body contour deformities after massive weight loss.

    Science.gov (United States)

    Iglesias, Martin; Butron, Patricia; Abarca, Leonardo; Perez-Monzo, Mario F; de Rienzo-Madero, Beatriz

    2010-08-01

    Deformities caused by massive weight loss were originally subsidized at the Instituto Nacional de Ciencias Médicas y Nutrición "Salvador Zubirán." This caused great economical losses, which led to the development of a classification to select patients with functional problems secondary to massive weight loss. The parameter used is the size of the pannus in relation to fixed anatomic structures within the following anatomic regions: abdomen, arms, thighs, mammary glands, lateral thoracic area, back, lumbar region, gluteal region, sacrum, and mons pubis. Grade 3 deformities are candidates for body contouring surgery because they constitute a functional problem. Grade 2 deformities reevaluated whether the patient has comorbidities. Lesser grades are considered aesthetic procedures and are not candidates for surgical rehabilitation at the Instituto Nacional de Ciencias Médicas y Nutrición "Salvador Zubirán." This classification allowed an improvement in communication between the different surgical-medical specialties; therefore, we suggest its application not only for surgical-administrative reasons but also for academic purposes.

  4. Crown-level tree species classification from AISA hyperspectral imagery using an innovative pixel-weighting approach

    Science.gov (United States)

    Liu, Haijian; Wu, Changshan

    2018-06-01

    Crown-level tree species classification is a challenging task due to the spectral similarity among different tree species. Shadow, underlying objects, and other materials within a crown may decrease the purity of extracted crown spectra and further reduce classification accuracy. To address this problem, an innovative pixel-weighting approach was developed for tree species classification at the crown level. The method utilized high density discrete LiDAR data for individual tree delineation and Airborne Imaging Spectrometer for Applications (AISA) hyperspectral imagery for pure crown-scale spectra extraction. Specifically, three steps were included: 1) individual tree identification using LiDAR data, 2) pixel-weighted representative crown spectra calculation using hyperspectral imagery, with which pixel-based illuminated-leaf fractions estimated using a linear spectral mixture analysis (LSMA) were employed as weighted factors, and 3) representative spectra based tree species classification was performed through applying a support vector machine (SVM) approach. Analysis of results suggests that the developed pixel-weighting approach (OA = 82.12%, Kc = 0.74) performed better than treetop-based (OA = 70.86%, Kc = 0.58) and pixel-majority methods (OA = 72.26, Kc = 0.62) in terms of classification accuracy. McNemar tests indicated the differences in accuracy between pixel-weighting and treetop-based approaches as well as that between pixel-weighting and pixel-majority approaches were statistically significant.

  5. Weight loss alters severity of individual nocturnal respiratory events depending on sleeping position

    International Nuclear Information System (INIS)

    Kulkas, A; Leppänen, T; Tiihonen, P; Mervaala, E; Töyräs, J; Sahlman, J; Seppä, J; Kokkarinen, J; Randell, J; Tuomilehto, H

    2014-01-01

    Weight loss is an effective treatment for obstructive sleep apnea (OSA). The mechanisms of how weight loss affects nocturnal breathing are not fully understood. The severity of OSA is currently estimated by the number of respiratory events per hour of sleep (i.e. apnea-hypopnea-index, AHI). AHI neglects duration and morphology of individual respiratory events, which describe the severity of individual events. In the current paper, we investigate the novel Adjusted-AHI parameter (incorporating individual event severity) and AHI after weight loss in relation to sleeping position. It was hypothesised that there are positional differences in individual event severity changes during weight loss. Altogether, 32 successful (> 5% of weight) and 34 unsuccessful weight loss patients at baseline and after 1 year follow-up were analysed. The results revealed that individual respiratory event severity was reduced differently in supine and non-supine positions during weight loss. During weight loss, AHI was reduced by 54% (p = 0.004) and 74% (p < 0.001), while Adjusted-AHI was reduced by 14% (p = 0.454) and 48% (p = 0.003) in supine and non-supine positions, respectively. In conclusion, the severity of individual respiratory events decreased more in the non-supine position. The novel Adjusted-AHI parameter takes these changes into account and might therefore contribute additional information to the planning of treatment of OSA patients. (paper)

  6. Accuracy of automated classification of major depressive disorder as a function of symptom severity.

    Science.gov (United States)

    Ramasubbu, Rajamannar; Brown, Matthew R G; Cortese, Filmeno; Gaxiola, Ismael; Goodyear, Bradley; Greenshaw, Andrew J; Dursun, Serdar M; Greiner, Russell

    2016-01-01

    Growing evidence documents the potential of machine learning for developing brain based diagnostic methods for major depressive disorder (MDD). As symptom severity may influence brain activity, we investigated whether the severity of MDD affected the accuracies of machine learned MDD-vs-Control diagnostic classifiers. Forty-five medication-free patients with DSM-IV defined MDD and 19 healthy controls participated in the study. Based on depression severity as determined by the Hamilton Rating Scale for Depression (HRSD), MDD patients were sorted into three groups: mild to moderate depression (HRSD 14-19), severe depression (HRSD 20-23), and very severe depression (HRSD ≥ 24). We collected functional magnetic resonance imaging (fMRI) data during both resting-state and an emotional-face matching task. Patients in each of the three severity groups were compared against controls in separate analyses, using either the resting-state or task-based fMRI data. We use each of these six datasets with linear support vector machine (SVM) binary classifiers for identifying individuals as patients or controls. The resting-state fMRI data showed statistically significant classification accuracy only for the very severe depression group (accuracy 66%, p = 0.012 corrected), while mild to moderate (accuracy 58%, p = 1.0 corrected) and severe depression (accuracy 52%, p = 1.0 corrected) were only at chance. With task-based fMRI data, the automated classifier performed at chance in all three severity groups. Binary linear SVM classifiers achieved significant classification of very severe depression with resting-state fMRI, but the contribution of brain measurements may have limited potential in differentiating patients with less severe depression from healthy controls.

  7. Effectiveness of a Low-Calorie Weight Loss Program in Moderately and Severely Obese Patients

    Directory of Open Access Journals (Sweden)

    Julia K. Winkler

    2013-10-01

    Full Text Available Aims: To compare effectiveness of a 1-year weight loss program in moderately and severely obese patients. Methods: The study sample included 311 obese patients participating in a weight loss program, which comprised a 12-week weight reduction phase (low-calorie formula diet and a 40-week weight maintenance phase. Body weight and glucose and lipid values were determined at the beginning of the program as well as after the weight reduction and the weight maintenance phase. Participants were analyzed according to their BMI class at baseline (30-34.9 kg/m2; 35-39.9 kg/m2; 40-44.9 kg/m2; 45-49.9 kg/m2; ≥50 kg/m2. Furthermore, moderately obese patients (BMI 2 were compared to severely obese participants (BMI ≥ 40 kg/m2. Results: Out of 311 participants, 217 individuals completed the program. Their mean baseline BMI was 41.8 ± 0.5 kg/m2. Average weight loss was 17.9 ± 0.6%, resulting in a BMI of 34.3 ± 0.4 kg/m2 after 1 year (p Conclusion: 1-year weight loss intervention improves body weight as well as lipid and glucose metabolism not only in moderately, but also in severely obese individuals.

  8. New classification of geometric ventricular patterns in severe aortic stenosis: Could it be clinically useful?

    Science.gov (United States)

    Di Nora, Concetta; Cervesato, Eugenio; Cosei, Iulian; Ravasel, Andreea; Popescu, Bogdan A; Zito, Concetta; Carerj, Scipione; Antonini-Canterin, Francesco; Popescu, Andreea C

    2018-04-16

    In severe aortic stenosis, different left ventricle (LV) remodeling patterns as a response to pressure overload have distinct hemodynamic profiles, cardiac function, and outcomes. The most common classification considers LV relative wall thickness and LV mass index to create 4 different groups. A new classification including also end-diastolic volume index has been recently proposed. To describe the prevalence of the newly identified remodeling patterns in patients with severe aortic stenosis and to evaluate their clinical relevance according to symptoms. We analyzed 286 consecutive patients with isolated severe aortic stenosis. Current guidelines were used for echocardiographic evaluation. Symptoms were defined as the presence of angina, syncope, or NYHA class III-IV. The mean age was 75 ± 9 years, 156 patients (54%) were men, while 158 (55%) were symptomatic. According to the new classification, the most frequent remodeling pattern was concentric hypertrophy (57.3%), followed by mixed (18.9%) and dilated hypertrophy (8.4%). There were no patients with eccentric remodeling; only 4 patients had a normalLV geometry. Symptomatic patients showed significantly more mixed hypertrophy (P < .05), while the difference regarding the prevalence of the other patterns was not statistically significant. When we analyzed the distribution of the classic 4 patterns stratified by the presence of symptoms, however, we did not find a significant difference (P = .157). The new classification had refined the description of different cardiac geometric phenotypes that develop as a response to pressure overload. It might be superior to the classic 4 patterns in terms of association with symptoms. © 2018 Wiley Periodicals, Inc.

  9. Support vector machine classification of Major Depressive Disorder using diffusion-weighted neuroimaging and graph theory

    Directory of Open Access Journals (Sweden)

    Matthew D Sacchet

    2015-02-01

    Full Text Available Recently there has been considerable interest in understanding brain networks in Major Depressive Disorder (MDD. Neural pathways can be tracked in the living brain using diffusion weighted imaging (DWI; graph theory can then be used to study properties of the resulting fiber networks. To date, global abnormalities have not been reported in tractography-based graph metrics in MDD, so we used a machine learning approach based on ‘support vector machines’ to differentiate depressed from healthy individuals based on multiple brain network properties. We also assessed how important specific graph metrics were for this differentiation. Finally, we conducted a local graph analysis to identify abnormal connectivity at specific nodes of the network. We were able to classify depression using whole-brain graph metrics. Small-worldness was the most useful graph metric for classification. The right pars orbitalis, right inferior parietal cortex, and left rostral anterior cingulate all showed abnormal network connectivity in MDD. This is the first use of structural global graph metrics to classify depressed individuals. These findings highlight the importance of future research to understand network properties in depression across imaging modalities, improve classification results, and relate network alterations to psychiatric symptoms, medication, and co-morbidities.

  10. Support vector machine classification of major depressive disorder using diffusion-weighted neuroimaging and graph theory.

    Science.gov (United States)

    Sacchet, Matthew D; Prasad, Gautam; Foland-Ross, Lara C; Thompson, Paul M; Gotlib, Ian H

    2015-01-01

    Recently, there has been considerable interest in understanding brain networks in major depressive disorder (MDD). Neural pathways can be tracked in the living brain using diffusion-weighted imaging (DWI); graph theory can then be used to study properties of the resulting fiber networks. To date, global abnormalities have not been reported in tractography-based graph metrics in MDD, so we used a machine learning approach based on "support vector machines" to differentiate depressed from healthy individuals based on multiple brain network properties. We also assessed how important specific graph metrics were for this differentiation. Finally, we conducted a local graph analysis to identify abnormal connectivity at specific nodes of the network. We were able to classify depression using whole-brain graph metrics. Small-worldness was the most useful graph metric for classification. The right pars orbitalis, right inferior parietal cortex, and left rostral anterior cingulate all showed abnormal network connectivity in MDD. This is the first use of structural global graph metrics to classify depressed individuals. These findings highlight the importance of future research to understand network properties in depression across imaging modalities, improve classification results, and relate network alterations to psychiatric symptoms, medication, and comorbidities.

  11. Resting and exercise energy metabolism in weight-reduced adults with severe obesity.

    Science.gov (United States)

    Hames, Kazanna C; Coen, Paul M; King, Wendy C; Anthony, Steven J; Stefanovic-Racic, Maja; Toledo, Frederico G S; Lowery, Jolene B; Helbling, Nicole L; Dubé, John J; DeLany, James P; Jakicic, John M; Goodpaster, Bret H

    2016-06-01

    To determine effects of physical activity (PA) with diet-induced weight loss on energy metabolism in adults with severe obesity. Adults with severe obesity (n = 11) were studied across 6 months of intervention, then compared with controls with less severe obesity (n = 7) or normal weight (n = 9). Indirect calorimetry measured energy metabolism during exercise and rest. Markers of muscle oxidation were determined by immunohistochemistry. Data were presented as medians. The intervention induced 7% weight loss (P = 0.001) and increased vigorous PA by 24 min/wk (P = 0.02). During exercise, energy expenditure decreased, efficiency increased (P ≤ 0.03), and fatty acid oxidation (FAO) did not change. Succinate dehydrogenase increased (P = 0.001), but fiber type remained the same. Post-intervention subjects' resting metabolism remained similar to controls. Efficiency was lower in post-intervention subjects compared with normal-weight controls exercising at 25 W (P ≤ 0.002) and compared with all controls exercising at 60% VO2peak (P ≤ 0.019). Resting and exercise FAO of post-intervention subjects remained similar to adults with less severe obesity. Succinate dehydrogenase and fiber type were similar across all body weight statuses. While metabolic adaptations to PA during weight loss occur in adults with severe obesity, FAO does not change. Resulting FAO during rest and exercise remains similar to adults with less severe obesity. © 2016 The Obesity Society.

  12. Postnatal weight gain modifies severity and functional outcome of oxygen-induced proliferative retinopathy.

    Science.gov (United States)

    Stahl, Andreas; Chen, Jing; Sapieha, Przemyslaw; Seaward, Molly R; Krah, Nathan M; Dennison, Roberta J; Favazza, Tara; Bucher, Felicitas; Löfqvist, Chatarina; Ong, Huy; Hellström, Ann; Chemtob, Sylvain; Akula, James D; Smith, Lois E H

    2010-12-01

    In clinical studies, postnatal weight gain is strongly associated with retinopathy of prematurity (ROP). However, animal studies are needed to investigate the pathophysiological mechanisms of how postnatal weight gain affects the severity of ROP. In the present study, we identify nutritional supply as one potent parameter that affects the extent of retinopathy in mice with identical birth weights and the same genetic background. Wild-type pups with poor postnatal nutrition and poor weight gain (PWG) exhibit a remarkably prolonged phase of retinopathy compared to medium weight gain or extensive weight gain pups. A high (r(2) = 0.83) parabolic association between postnatal weight gain and oxygen-induced retinopathy severity is observed, as is a significantly prolonged phase of proliferative retinopathy in PWG pups (20 days) compared with extensive weight gain pups (6 days). The extended retinopathy is concomitant with prolonged overexpression of retinal vascular endothelial growth factor in PWG pups. Importantly, PWG pups show low serum levels of nonfasting glucose, insulin, and insulin-like growth factor-1 as well as high levels of ghrelin in the early postoxygen-induced retinopathy phase, a combination indicative of poor metabolic supply. These differences translate into visual deficits in adult PWG mice, as demonstrated by impaired bipolar and proximal neuronal function. Together, these results provide evidence for a pathophysiological correlation between poor postnatal nutritional supply, slow weight gain, prolonged retinal vascular endothelial growth factor overexpression, protracted retinopathy, and reduced final visual outcome.

  13. A study of several CAD methods for classification of clustered microcalcifications

    Science.gov (United States)

    Wei, Liyang; Yang, Yongyi; Nishikawa, Robert M.; Jiang, Yulei

    2005-04-01

    In this paper we investigate several state-of-the-art machine-learning methods for automated classification of clustered microcalcifications (MCs), aimed to assisting radiologists for more accurate diagnosis of breast cancer in a computer-aided diagnosis (CADx) scheme. The methods we consider include: support vector machine (SVM), kernel Fisher discriminant (KFD), and committee machines (ensemble averaging and AdaBoost), most of which have been developed recently in statistical learning theory. We formulate differentiation of malignant from benign MCs as a supervised learning problem, and apply these learning methods to develop the classification algorithms. As input, these methods use image features automatically extracted from clustered MCs. We test these methods using a database of 697 clinical mammograms from 386 cases, which include a wide spectrum of difficult-to-classify cases. We use receiver operating characteristic (ROC) analysis to evaluate and compare the classification performance by the different methods. In addition, we also investigate how to combine information from multiple-view mammograms of the same case so that the best decision can be made by a classifier. In our experiments, the kernel-based methods (i.e., SVM, KFD) yield the best performance, significantly outperforming a well-established CADx approach based on neural network learning.

  14. Ancillary testing, diagnostic/classification criteria and severity grading in Behçet disease.

    Science.gov (United States)

    Okada, Annabelle A; Stanford, Miles; Tabbara, Khalid

    2012-12-01

    Since there is no pathognomonic clinical sign or laboratory test to distinguish Behçet disease from other uveitic entities, the diagnosis must be made based on characteristic ocular and systemic findings in the absence of evidence of other disease that can explain the findings. Ancillary tests, including ocular and brain imaging studies, are used to assess the severity of intraocular inflammation and systemic manifestations of Behçet disease, to identify latent infections and other medical conditions that might worsen with systemic treatment, and to monitor for adverse effects of drugs used. There are two diagnostic or classification criteria in general use by the uveitis community, one from Japan and one from an international group; both rely on a minimum number and/or combination of clinical findings to identify Behçet disease. Finally, several grading schemes have been proposed to assess severity of ocular disease and response to treatment.

  15. Multispectral imaging burn wound tissue classification system: a comparison of test accuracies between several common machine learning algorithms

    Science.gov (United States)

    Squiers, John J.; Li, Weizhi; King, Darlene R.; Mo, Weirong; Zhang, Xu; Lu, Yang; Sellke, Eric W.; Fan, Wensheng; DiMaio, J. Michael; Thatcher, Jeffrey E.

    2016-03-01

    The clinical judgment of expert burn surgeons is currently the standard on which diagnostic and therapeutic decisionmaking regarding burn injuries is based. Multispectral imaging (MSI) has the potential to increase the accuracy of burn depth assessment and the intraoperative identification of viable wound bed during surgical debridement of burn injuries. A highly accurate classification model must be developed using machine-learning techniques in order to translate MSI data into clinically-relevant information. An animal burn model was developed to build an MSI training database and to study the burn tissue classification ability of several models trained via common machine-learning algorithms. The algorithms tested, from least to most complex, were: K-nearest neighbors (KNN), decision tree (DT), linear discriminant analysis (LDA), weighted linear discriminant analysis (W-LDA), quadratic discriminant analysis (QDA), ensemble linear discriminant analysis (EN-LDA), ensemble K-nearest neighbors (EN-KNN), and ensemble decision tree (EN-DT). After the ground-truth database of six tissue types (healthy skin, wound bed, blood, hyperemia, partial injury, full injury) was generated by histopathological analysis, we used 10-fold cross validation to compare the algorithms' performances based on their accuracies in classifying data against the ground truth, and each algorithm was tested 100 times. The mean test accuracy of the algorithms were KNN 68.3%, DT 61.5%, LDA 70.5%, W-LDA 68.1%, QDA 68.9%, EN-LDA 56.8%, EN-KNN 49.7%, and EN-DT 36.5%. LDA had the highest test accuracy, reflecting the bias-variance tradeoff over the range of complexities inherent to the algorithms tested. Several algorithms were able to match the current standard in burn tissue classification, the clinical judgment of expert burn surgeons. These results will guide further development of an MSI burn tissue classification system. Given that there are few surgeons and facilities specializing in burn care

  16. Classification

    Science.gov (United States)

    Clary, Renee; Wandersee, James

    2013-01-01

    In this article, Renee Clary and James Wandersee describe the beginnings of "Classification," which lies at the very heart of science and depends upon pattern recognition. Clary and Wandersee approach patterns by first telling the story of the "Linnaean classification system," introduced by Carl Linnacus (1707-1778), who is…

  17. A Population Survey in Italy Based on the ICF Classification: Recognizing Persons with Severe Disability

    Directory of Open Access Journals (Sweden)

    Matilde Leonardi

    2012-01-01

    Full Text Available Aim of this paper is to describe functioning of subjects with “severe disability” collected with a protocol based on the International Classification of Functioning, Disability, and Health. It included sections on body functions and structures (BF and BS, activities and participation (A&P, and environmental factors (EF. In A&P, performance without personal support (WPS was added to standard capacity and performance. Persons with severe disability were those reporting a number of very severe/complete problems in BF or in A&P-capacity superior to mean + 1SD. Correlations between BF and A&P and differences between capacity, performance-WPS, and performance were assessed with Spearman's coefficient. Out of 1051, 200 subjects were considered as severely disabled. Mild to moderate correlations between BF and A&P were reported (between 0.148 and 0.394 when the full range of impairments/limitations was taken into account; between 0.198 and 0.285 when only the severe impairments/limitations were taken into account; performance-WPS was less similar to performance than to capacity. Our approach enabled identifying subjects with “severe disability” and separating the effect of personal support from that of devices, policies, and service provision.

  18. Classification

    DEFF Research Database (Denmark)

    Hjørland, Birger

    2017-01-01

    This article presents and discusses definitions of the term “classification” and the related concepts “Concept/conceptualization,”“categorization,” “ordering,” “taxonomy” and “typology.” It further presents and discusses theories of classification including the influences of Aristotle...... and Wittgenstein. It presents different views on forming classes, including logical division, numerical taxonomy, historical classification, hermeneutical and pragmatic/critical views. Finally, issues related to artificial versus natural classification and taxonomic monism versus taxonomic pluralism are briefly...

  19. COMPARISON OF OXYGEN UPTAKE KINETICS AND OXYGEN DEFICIT IN SEVERELY OVERWEIGHT AND NORMAL WEIGHT ADOLESCENT FEMALES

    Directory of Open Access Journals (Sweden)

    Mark Loftin

    2005-12-01

    Full Text Available The purpose of this study was to determine if differences in oxygen uptake kinetics and oxygen deficit existed between normal weight and severely overweight adolescent girls. Subjects included 10 normal weight and 8 severely overweight girls. The participants performed a leg cycling VO2 peak test and a constant load leg cycling test at 80% of the ventilatory threshold (T-vent. In the constant workload test O2 kinetics as indicated by Phase I (VO2 L at 20 sec and Phase II time constants (t were determined. Also, the O2 deficit (VO2 L was measured. As expected significant differences were noted in body composition and VO2 peak relative to mass with normal weight body mass averaging 55.3 ± 7.0 kg, severely overweight 90.5 ± 18.0 kg, % fat normal weight 27.3 ± 3.9%, severely overweight 49.7 ± 4.9% and VO2 peak (ml·kg-1·min-1 normal weight 32.0 ± 2.7 and severely overweight 22.0 ± 5.3. VO2 peak (l·min-1 and T-vent (%VO2 max were similar between groups. Results revealed similar O2 kinetic responses between groups; phase I kinetics normal weight 0.72 ± 0.15 L; severely overweight 0.75 ± 0.13L, phase II (t normal weight 41.5 ± 21.3 sec; severely overweight 33.9 ± 22.7 sec. However, the O2 deficit was significantly higher in the severely overweight (0.75 ± 0.15L when compared to the normal weight group (0.34 ± 0.13L. Correlations ranged from r = -0.15 to 0.51 between VO2 peak (L·min-1 or fat weight and phase I, t and O2 deficit. These data generally support previous research concerning the independence of O2 uptake response and body size

  20. Injury severity in ice skating: an epidemiologic analysis using a standardised injury classification system.

    Science.gov (United States)

    Ostermann, Roman C; Hofbauer, Marcus; Tiefenböck, Thomas M; Pumberger, Matthias; Tiefenböck, Michael; Platzer, Patrick; Aldrian, Silke

    2015-01-01

    Although injuries sustained during ice skating have been reported to be more serious than other forms of skating, the potential injury risks are often underestimated by skating participants. The purpose of this study was to give a descriptive overview of injury patterns occurring during ice skating. Special emphasis was put on injury severity by using a standardised injury classification system. Over a six month period, all patients treated with ice-skating-related injuries at Europe's largest hospital were included. Patient demographics were collected and all injuries categorised according to the Abbreviated Injury Scale (AIS) 2005. A descriptive statistic and logistic regression analysis was performed. Three hundred and forty-one patients (134 M, 207 F) were included in this study. Statistical analysis revealed that age had a significant influence on injury severity. People > 50 years had a higher risk of sustaining a more severe injury according to the AIS compared with younger skaters. Furthermore, the risk of head injury was significantly lower for people aged between 18 and 50 years than for people  50 years than for people aged between 18 and 50 years (p = 0.04). The severity of ice-skating injuries is associated with the patient's age, showing more severe injuries in older patients. Awareness should be raised among the public and physicians about the risks associated with this activity in order to promote further educational interventions and the use of protective gear.

  1. The role of diffusion-weighted magnetic resonance imaging in the classification of hepatic hydatid cysts

    Energy Technology Data Exchange (ETDEWEB)

    Çeçe, Hasan, E-mail: hasan_cece@yahoo.com [Harran University, Faculty of Medicine, Department of Radiology, 63300 Şanlıurfa (Turkey); Gündoğan, Mehmet, E-mail: drgundogan@hotmail.com [Harran University, Faculty of Medicine, Department of Radiology, 63300 Şanlıurfa (Turkey); Karakaş, Ömer, E-mail: dromerkarakas@hotmail.com [Harran University, Faculty of Medicine, Department of Radiology, 63300 Şanlıurfa (Turkey); Karakaş, Ekrem, E-mail: karakasekrem@yahoo.com [Harran University, Faculty of Medicine, Department of Radiology, 63300 Şanlıurfa (Turkey); Boyacı, Fatıma Nurefşan, E-mail: drnurefsan@yahoo.com [Harran University, Faculty of Medicine, Department of Radiology, 63300 Şanlıurfa (Turkey); Yıldız, Sema, E-mail: drsemayildiz@yahoo.com [Harran University, Faculty of Medicine, Department of Radiology, 63300 Şanlıurfa (Turkey); Özgönül, Abdullah, E-mail: drozgonul@yahoo.com.tr [Harran University, Faculty of Medicine, Department of General Surgery, Şanlıurfa (Turkey); Karakaş, Emel Yiğit, E-mail: e.ygtkarakas@yahoo.com.tr [Şanlıurfa Training and Research Hospital, Department of Internal Medicine, Şanlıurfa (Turkey); and others

    2013-01-15

    The aim of the study was to classify different types of hepatic hydatid cysts (HHCs) by measuring the mean apparent diffusion coefficient (ADC) using diffusion-weighted magnetic resonance imaging (DWI). This prospective study comprised 44 patients. The 44 HHCs were classified using Gharbi ultrasonographic classification (GUC) and then T2WIs and DWIs were obtained. The ADC values were measured of the hydatid cyst (HC) subtypes. The distribution of the ADC values in the cyst groups was compared using the Kruskal–Wallis test for multi groups and the Mann–Whitney U test for paired groups. To evaluate the efficacy of ADC values in cyst diagnosis, receiver operating characteristic (ROC) analysis was performed. According to the GUC, there were 15 type 1, 11 type 2, 7 type 3, 5 type 4 and 6 type 5 HHCs. According to the ADC values in the paired comparisons, while types 1, 2 and 5 HCs were statistically differentiated from all other groups except the type 3 group, the type 4 group was differentiated from all other groups and the type 3 group was only differentiated from the type 4 group. When two groups were formed from the HHC subtypes with types 1, 2, and 3 in one group and types 4 and 5 in the other, a statistically significant difference was determined in the mean ADC values of these new groups. In conclusion the measurement of ADC values can be considered a promising parameter as an alternative to ultrasonography in the determination of subtypes of HHCs.

  2. Impact of using the new GOLD classification on the distribution of COPD severity in clinical practice

    Directory of Open Access Journals (Sweden)

    Hernández M

    2018-01-01

    Full Text Available Marcos Hernández, Gabriel García, Jimena Falco, Agustín R García, Vanina Martín, Manuel Ibarrola, Silvia Quadrelli Department of Respiratory Medicine, Güemes Foundation, Buenos Aires, Argentina Objective: The objective of this study was to examine how COPD patients were classified by the Global Initiative for Chronic Obstructive Lung Disease (GOLD spirometry-based severity system and the distribution of COPD severity using the new GOLD 2011 assessment framework.Materials and methods: This was an observational, retrospective cohort study conducted in a single tertiary center on a prospective database, which aimed to evaluate the prevalence, incidence, severity, and comorbidities of COPD. Inclusion criteria were age ≥40 years and COPD diagnosis according to GOLD 2007 classification. Clinical factors were compared between the categories in GOLD 2007 and 2011 groups by using the χ2 test for categorical data and the analysis of variance for continuous data.Results: In total, 420 COPD patients were included in the analysis. The distribution of patients into GOLD 2007 categories was as follows: 6.4% (n=27 of them were classified into subgroup I, 42.1% (n=177 into subgroup II, 37.9% (n=159 into subgroup III, and 13.6% (n=57 into subgroup IV. The distribution of patients into GOLD 2011 categories was as follows: 16.4% (n=69 of them were classified into subgroup A (low risk and fewer symptoms, 32.1% (n=135 into subgroup B (low risk and more symptoms, 21.6% (n=91 into subgroup C (high risk and fewer symptoms, and 29.7% (n=125 into subgroup D (high risk and more symptoms. After the application of the new GOLD 2011 (modified Medical Research Council [mMRC] system, 22% (n=94 of patients were upgraded to a higher level than their spirometry level, and 16.2% (n=68 of them were downgraded in their severity category, meaning that almost 40% of patients changed their severity assessment category. In total, 22% of patients in stage I were allocated to

  3. [Body weight evolution and classification of body weight in relation to the results of bariatric surgery: roux-en-Y gastric bypass].

    Science.gov (United States)

    Novais, Patrícia Fátima Sousa; Rasera Junior, Irineu; Leite, Celso Vieira de Souza; Oliveira, Maria Rita Marques de

    2010-03-01

    The objective of this study was to assess the evolution and classification of body weight in relation to the results of bariatric surgery in women who underwent the procedure more than two years ago. A total of 141 women underwent banded Roux-en-Y gastric bypass (RYGB). The participants were divided according to the time elapsed since surgery and the percentage of excess weight lost (%EWL): 75. The women in the group with %EWL 75 (36.2%) ranged from normal to pre-obese and presented lower late weight gain than the women in the other groups. Weight evolution two or more years after surgery showed the expected reductions, with some individuals responding better to surgery than others. This shows that it is necessary to monitor, investigate and intervene to obtain the desired results.

  4. The present status of xeroderma pigmentosum in Japan and a tentative severity classification scale.

    Science.gov (United States)

    Nakano, Eiji; Masaki, Taro; Kanda, Fumio; Ono, Ryusuke; Takeuchi, Seiji; Moriwaki, Shinichi; Nishigori, Chikako

    2016-08-01

    Xeroderma pigmentosum (XP) is a rare autosomal recessive hereditary disease. Patients with XP have severe hypersensitivity to sunlight, resulting in skin cancers, and some patients have neurological symptoms. In Japan, XP complementation group A (XP-A) is the most common form, and it is associated with severe neurological symptoms. We performed a nationwide survey on XP to determine the present status of XP in Japan. The distribution of complementation groups in Japan was considerably different from that in other countries, but there was a higher frequency in group A and the variant type, which is similar to previous reports in Japan. Basal cell carcinoma was the most frequent skin cancer that patients with XP developed, followed by squamous cell carcinoma and malignant melanoma. The frequency of these skin cancers in patients with XP-A has decreased, and these skin cancers have been occurring in much older people than those previously observed. Diagnosing XP in patients at younger ages seems to encourage patients and their parents to use sun protection, which helps prevent skin cancer. We also created a tentative scale for classifying the severity of XP, and we evaluated the neurological symptoms of XP-A using this severity scale. Our classification correlated well with patients' age, suggesting that it may be useful and feasible in clinical practice to assess the progression of symptoms of each patient with XP and evaluate the effects of treatment in the future. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  5. Meal replacements as a weight loss tool in a population with severe mental illness.

    Science.gov (United States)

    Gelberg, Hollie A; Kwan, Crystal L; Mena, Shirley J; Erickson, Zachary D; Baker, Matthew R; Chamberlin, Valery; Nguyen, Charles; Rosen, Jennifer A; Shah, Chandresh; Ames, Donna

    2015-12-01

    Weight gain and worsening metabolic parameters are often side effects of antipsychotic medications used by individuals with severe mental illness. To address this, a randomized, controlled research study of a behavioral weight management program for individuals with severe mental illness was undertaken to assess its efficacy. Patients unable to meet weight loss goals during the first portion of the year-long study were given the option of using meal replacement shakes in an effort to assist with weight loss. Specific requirements for use of meal replacement shakes were specified in the study protocol; only five patients were able to use the shakes in accordance with the protocol and lose weight while improving metabolic parameters. Case studies of two subjects are presented, illustrating the challenges and obstacles they faced, as well as their successes. Taking responsibility for their own weight loss, remaining motivated through the end of the study, and incorporating the meal replacement shakes into a daily routine were factors found in common with these patients. Use of meal replacements shakes with this population may be effective. Published by Elsevier Ltd.

  6. A new reliability allocation weight for reducing the occurrence of severe failure effects

    International Nuclear Information System (INIS)

    Kim, Kyungmee O.; Yang, Yoonjung; Zuo, Ming J.

    2013-01-01

    A reliability allocation weight is used during the early design stage of a system to apportion the system reliability requirement to its individual subsystems. Since some failures have serious effects on public safety, cost and environmental issues especially in a mission critical system, the failure effect must be considered as one of the important factors in determining the allocation weight. Previously, the risk priority number or the criticality number was used to consider the failure effect in the allocation weight. In this paper, we identify the limitations of the previous approach and propose a new allocation weight based on the subsystem failure severity and its relative frequency. An example is given to illustrate that the proposed method is more effective than the previous method for reducing the occurrence of the unacceptable failure effects in a newly designed system

  7. Reliability assessment of AOSpine thoracolumbar spine injury classification system and Thoracolumbar Injury Classification and Severity Score (TLICS) for thoracolumbar spine injuries: results of a multicentre study.

    Science.gov (United States)

    Kaul, Rahul; Chhabra, Harvinder Singh; Vaccaro, Alexander R; Abel, Rainer; Tuli, Sagun; Shetty, Ajoy Prasad; Das, Kali Dutta; Mohapatra, Bibhudendu; Nanda, Ankur; Sangondimath, Gururaj M; Bansal, Murari Lal; Patel, Nishit

    2017-05-01

    The aim of this multicentre study was to determine whether the recently introduced AOSpine Classification and Injury Severity System has better interrater and intrarater reliability than the already existing Thoracolumbar Injury Classification and Severity Score (TLICS) for thoracolumbar spine injuries. Clinical and radiological data of 50 consecutive patients admitted at a single centre with a diagnosis of an acute traumatic thoracolumbar spine injury were distributed to eleven attending spine surgeons from six different institutions in the form of PowerPoint presentation, who classified them according to both classifications. After time span of 6 weeks, cases were randomly rearranged and sent again to same surgeons for re-classification. Interobserver and intraobserver reliability for each component of TLICS and new AOSpine classification were evaluated using Fleiss Kappa coefficient (k value) and Spearman rank order correlation. Moderate interrater and intrarater reliability was seen for grading fracture type and integrity of posterior ligamentous complex (Fracture type: k = 0.43 ± 0.01 and 0.59 ± 0.16, respectively, PLC: k = 0.47 ± 0.01 and 0.55 ± 0.15, respectively), and fair to moderate reliability (k = 0.29 ± 0.01 interobserver and 0.44+/0.10 intraobserver, respectively) for total score according to TLICS. Moderate interrater (k = 0.59 ± 0.01) and substantial intrarater reliability (k = 0.68 ± 0.13) was seen for grading fracture type regardless of subtype according to AOSpine classification. Near perfect interrater and intrarater agreement was seen concerning neurological status for both the classification systems. Recently proposed AOSpine classification has better reliability for identifying fracture morphology than the existing TLICS. Additional studies are clearly necessary concerning the application of these classification systems across multiple physicians at different level of training and trauma centers to evaluate not

  8. Apparent diffusion coefficient value of gastric cancer by diffusion-weighted imaging: Correlations with the histological differentiation and Lauren classification

    International Nuclear Information System (INIS)

    Liu, Song; Guan, Wenxian; Wang, Hao; Pan, Liang; Zhou, Zhuping; Yu, Haiping; Liu, Tian; Yang, Xiaofeng; He, Jian; Zhou, Zhengyang

    2014-01-01

    Highlights: • Gastric cancers’ ADC values were significantly lower than normal gastric wall. • Gastric adenocarcinomas with different differentiation had different ADC values. • Gastric adenocarcinomas’ ADC values correlated with histologic differentiations. • Gastric cancers’ ADC values correlated with Lauren classifications. • Mean ADC value was better than min ADC value in characterizing gastric cancers. - Abstract: Objective: The purpose of this study was to evaluate the correlations between histological differentiation and Lauren classification of gastric cancer and the apparent diffusion coefficient (ADC) value of diffusion weighted imaging (DWI). Materials and methods: Sixty-nine patients with gastric cancer lesions underwent preoperative magnetic resonance imaging (MRI) (3.0T) and surgical resection. DWI was obtained with a single-shot, echo-planar imaging sequence in the axial plane (b values: 0 and 1000 s/mm 2 ). Mean and minimum ADC values were obtained for each gastric cancer and normal gastric walls by two radiologists, who were blinded to the histological findings. Histological type, degree of differentiation and Lauren classification of each resected specimen were determined by one pathologist. Mean and minimum ADC values of gastric cancers with different histological types, degrees of differentiation and Lauren classifications were compared. Correlations between ADC values and histological differentiation and Lauren classification were analyzed. Results: The mean and minimum ADC values of gastric cancers, as a whole and separately, were significantly lower than those of normal gastric walls (all p values <0.001). There were significant differences in the mean and minimum ADC values among gastric cancers with different histological types, degrees of differentiation and Lauren classifications (p < 0.05). Mean and minimum ADC values correlated significantly (all p < 0.001) with histological differentiation (r = 0.564, 0.578) and Lauren

  9. [Classification of severely injured patients in the G-DRG System 2008].

    Science.gov (United States)

    Juhra, C; Franz, D; Roeder, N; Vordemvenne, T; Raschke, M J

    2009-05-01

    Since the introduction of a per-case reimbursement system in Germany (German Diagnosis-Related Groups, G-DRG), the correct reimbursement for the treatment of severely injured patients has been much debated. While the classification of a patient in a polytrauma DRG follows different rules than the usual clinical definition, leading to a high number of patients not grouped as severely injured by the system, the system was also criticized in 2005 for its shortcomings in financing the treatment of severely injured patients. The development of financial reimbursement will be discussed in this paper. 167 patients treated in 2006 and 2007 due to a severe injury at the University-Hospital Münster and grouped into a polytrauma-DRG were included in this study. For each patient, cost-equivalents were estimated. For those patients treated in 2007 (n=110), exact costs were calculated following the InEK cost-calculation method. The reimbursement was calculated using the G-DRG-Systems of 2007, 2008 and 2009. Cost-equivalents/costs and clinical parameters were correlated. A total of 167 patients treated in 2006 and 2007 for a severe injury at the Münster University Hospital and grouped into a polytrauma DRG were included in this study. Cost equivalents were estimated for each patient. For those patients treated in 2007 (n=110), exact costs were calculated following the InEK (Institute for the Hospital Remuneration System) cost calculation method. Reimbursement was calculated using the G-DRG systems of 2007, 2008 and 2009. Cost equivalents/costs and clinical parameters were correlated. With the ongoing development of the G-DRG system, reimbursement for the treatment of severely injured patient has improved, but the amount of underfinancing remains substantial. As treatment of severely injured patients must be reimbursed using the G-DRG system, this system must be further adapted to better meet the needs of severely injured patients. Parameters such as total surgery time, injury

  10. Birth weight classification in gestational diabetes: is there an ideal chart?

    Directory of Open Access Journals (Sweden)

    Livia Silveira Mastella

    2017-01-01

    Full Text Available Introduction: Gestational diabetes mellitus (GDM is associated to increased rates of large for gestational age newborns and macrosomia. Several charts are used to classify birth weight. Is there an ideal chart to classify newborns of GDM mothers? Methods: We evaluated adequacy of birth weight of 332 neonates born to GDM mothers at Hospital de Clínicas de Porto Alegre, Brazil. Newborns were classified according to gestational age as small (SGA, adequate or large (LGA based on four charts: Alexander, Pedreira, INTERGROWTH 21st Project and SINASC-2012. The latter was built using data from a large national registry of 2012, the Born Alive National Surveillance System (Sistema de Informações de Nascidos Vivos – SINASC, which included 2.905,789 birth certificates. Frequencies of SGA and LGA and Kappa agreement were calculated. Results: In non-gender adjusted curves, SGA rates (95% confidence interval varied from 8% (5-11 to 9% (6-13; LGA rates, from 11% (8-15 to 17% (13-21. For males, SGA rates varied from 3% (1-6% to 6% (3-11%, and LGA rates, from 18% (13-24% to 31% (24-38%; for female, SGA rates were from 3% (1-7% to 10% (6-16% and LGA rates, from 11% (6-16% to 19% (13-26%. Kappa results were: ALEXANDER vs. SINASC-2012: 0.80 (0.73-0.88; INTERGROWTH 21st vs. SINASC-2012 (adjusted by sex: 0.62 (0.53-0.71; INTERGROWTH 21st vs. PEDREIRA: 0.71 (0.62-0.79; SINASC-2012 (by sex vs. PEDREIRA: 0.86 (0.79-0.93. Conclusions: Misclassification has to be taken into account when evaluating newborns of GDM mothers, as LGA rates can almost double depending on the chart used to classify birth weight.

  11. Using multiclass classification to automate the identification of patient safety incident reports by type and severity.

    Science.gov (United States)

    Wang, Ying; Coiera, Enrico; Runciman, William; Magrabi, Farah

    2017-06-12

    Approximately 10% of admissions to acute-care hospitals are associated with an adverse event. Analysis of incident reports helps to understand how and why incidents occur and can inform policy and practice for safer care. Unfortunately our capacity to monitor and respond to incident reports in a timely manner is limited by the sheer volumes of data collected. In this study, we aim to evaluate the feasibility of using multiclass classification to automate the identification of patient safety incidents in hospitals. Text based classifiers were applied to identify 10 incident types and 4 severity levels. Using the one-versus-one (OvsO) and one-versus-all (OvsA) ensemble strategies, we evaluated regularized logistic regression, linear support vector machine (SVM) and SVM with a radial-basis function (RBF) kernel. Classifiers were trained and tested with "balanced" datasets (n_ Type  = 2860, n_ SeverityLevel  = 1160) from a state-wide incident reporting system. Testing was also undertaken with imbalanced "stratified" datasets (n_ Type  = 6000, n_ SeverityLevel =5950) from the state-wide system and an independent hospital reporting system. Classifier performance was evaluated using a confusion matrix, as well as F-score, precision and recall. The most effective combination was a OvsO ensemble of binary SVM RBF classifiers with binary count feature extraction. For incident type, classifiers performed well on balanced and stratified datasets (F-score: 78.3, 73.9%), but were worse on independent datasets (68.5%). Reports about falls, medications, pressure injury, aggression and blood products were identified with high recall and precision. "Documentation" was the hardest type to identify. For severity level, F-score for severity assessment code (SAC) 1 (extreme risk) was 87.3 and 64% for SAC4 (low risk) on balanced data. With stratified data, high recall was achieved for SAC1 (82.8-84%) but precision was poor (6.8-11.2%). High risk incidents (SAC2) were confused

  12. The Dysexecutive Questionnaire advanced: item and test score characteristics, 4-factor solution, and severity classification.

    Science.gov (United States)

    Bodenburg, Sebastian; Dopslaff, Nina

    2008-01-01

    The Dysexecutive Questionnaire (DEX, , Behavioral assessment of the dysexecutive syndrome, 1996) is a standardized instrument to measure possible behavioral changes as a result of the dysexecutive syndrome. Although initially intended only as a qualitative instrument, the DEX has also been used increasingly to address quantitative problems. Until now there have not been more fundamental statistical analyses of the questionnaire's testing quality. The present study is based on an unselected sample of 191 patients with acquired brain injury and reports on the data relating to the quality of the items, the reliability and the factorial structure of the DEX. Item 3 displayed too great an item difficulty, whereas item 11 was not sufficiently discriminating. The DEX's reliability in self-rating is r = 0.85. In addition to presenting the statistical values of the tests, a clinical severity classification of the overall scores of the 4 found factors and of the questionnaire as a whole is carried out on the basis of quartile standards.

  13. Effect of inhaled corticosteroid use on weight (BMI) in pediatric patients with moderate-severe asthma.

    Science.gov (United States)

    Han, Jennifer; Nguyen, John; Kim, Yuna; Geng, Bob; Romanowski, Gale; Alejandro, Lawrence; Proudfoot, James; Xu, Ronghui; Leibel, Sydney

    2018-04-19

    Assess the relationship between inhaled corticosteroid use (ICS) and weight (BMI) in pediatric patients with moderate-severe asthma. Assess if the number of emergency department (ED) visits correlates with overall BMI trajectory. Assess the trend of prescribing biologic therapy in pediatric patients with moderate-severe asthma and determine its relationship with weight (BMI). A retrospective chart review was performed on 93 pediatric patients with moderate-severe asthma to determine the relationship between ICS use and weight (BMI), biologic therapy and BMI, and number of ED visits and BMI trajectory. A mixed effects model was employed with the correlation between repeated measures accounted for through the random effects. There is a statistically significant increase of 0.369 kg/m 2 in BMI trajectory per year in subjects on high-dose steroids compared to an increase of 0.195 kg/m 2 in the low dose group (p BMI of subjects initiated on biologic therapy (omalizumab or mepolizumab) had a statistically significant decrease in BMI trajectory of 0.818 kg/m 2 per year (p BMI trajectory (p BMI trajectory; the higher the dose, the greater the projected BMI increase per year. Initiation of biologic therapy decreased BMI trajectory over time. Lastly, those with frequent ED visits had a higher BMI trend. Future prospective studies are warranted that further evaluate the potential metabolic impacts of ICS and assess the effects of biologic therapy on BMI.

  14. Increasing illness severity in very low birth weight infants over a 9-year period

    Directory of Open Access Journals (Sweden)

    Locke Robert G

    2006-02-01

    Full Text Available Abstract Background Recent reports have documented a leveling-off of survival rates in preterm infants through the 1990's. The objective of this study was to determine temporal changes in illness severity in very low birth weight (VLBW infants in relationship to the outcomes of death and/or severe IVH. Methods Cohort study of 1414 VLBW infants cared for in a single level III neonatal intensive care unit in Delaware from 1993–2002. Infants were divided into consecutive 3-year cohorts. Illness severity was measured by two objective methods: the Score for Neonatal Acute Physiology (SNAP, based on data from the 1st day of life, and total thyroxine (T4, measured on the 5th day of life. Death before hospital discharge and severe intraventricular hemorrhage (IVH were investigated in the study sample in relation to illness severity. The fetal death rate was also investigated. Statistical analyses included both univariate and multivariate analysis. Results Illness severity, as measured by SNAP and T4, increased steadily over the 9-year study period with an associated increase in severe IVH and the combined outcome of death and/or severe IVH. During the final 3 years of the study, the observed increase in illness severity accounted for 86% (95% CI 57–116% of the variability in the increase in death and/or severe IVH. The fetal death rate dropped from 7.8/1000 (1993–1996 to 5.3/1000 (1999–2002, p = .01 over the course of the study. Conclusion These data demonstrate a progressive increase in illness in VLBW infants over time, associated with an increase in death and/or severe IVH. We speculate that the observed decrease in fetal death, and the increase in neonatal illness, mortality and/or severe IVH over time represent a shift of severely compromised patients that now survive the fetal time period and are presented for care in the neonatal unit.

  15. A New Weighted Injury Severity Scoring System: Better Predictive Power for Pediatric Trauma Mortality.

    Science.gov (United States)

    Shi, Junxin; Shen, Jiabin; Caupp, Sarah; Wang, Angela; Nuss, Kathryn E; Kenney, Brian; Wheeler, Krista K; Lu, Bo; Xiang, Henry

    2018-05-02

    An accurate injury severity measurement is essential for the evaluation of pediatric trauma care and outcome research. The traditional Injury Severity Score (ISS) does not consider the differential risks of the Abbreviated Injury Scale (AIS) from different body regions nor is it pediatric specific. The objective of this study was to develop a weighted injury severity scoring (wISS) system for pediatric blunt trauma patients with better predictive power than ISS. Based on the association between mortality and AIS from each of the six ISS body regions, we generated different weights for the component AIS scores used in the calculation of ISS. The weights and wISS were generated using the National Trauma Data Bank (NTDB). The Nationwide Emergency Department Sample (NEDS) was used to validate our main results. Pediatric blunt trauma patients less than 16 years were included, and mortality was the outcome. Discrimination (areas under the receiver operating characteristic curve, sensitivity, specificity, positive predictive value, negative predictive value, concordance) and calibration (Hosmer-Lemeshow statistic) were compared between the wISS and ISS. The areas under the receiver operating characteristic curves from the wISS and ISS are 0.88 vs. 0.86 in ISS=1-74 and 0.77 vs. 0.64 in ISS=25-74 (ppredictive value, negative predictive value, and concordance when they were compared at similar levels of sensitivity. The wISS had better calibration (smaller Hosmer-Lemeshow statistic) than the ISS (11.6 versus 19.7 for ISS=1-74 and 10.9 versus 12.6 for ISS= 25-74). The wISS showed even better discrimination with the NEDS. By weighting the AIS from different body regions, the wISS had significantly better predictive power for mortality than the ISS, especially in critically injured children.Level of Evidence and study typeLevel IV Prognostic/Epidemiological.

  16. Occupancy classification of position weight matrix-inferred transcription factor binding sites.

    Directory of Open Access Journals (Sweden)

    Hollis Wright

    Full Text Available BACKGROUND: Computational prediction of Transcription Factor Binding Sites (TFBS from sequence data alone is difficult and error-prone. Machine learning techniques utilizing additional environmental information about a predicted binding site (such as distances from the site to particular chromatin features to determine its occupancy/functionality class show promise as methods to achieve more accurate prediction of true TFBS in silico. We evaluate the Bayesian Network (BN and Support Vector Machine (SVM machine learning techniques on four distinct TFBS data sets and analyze their performance. We describe the features that are most useful for classification and contrast and compare these feature sets between the factors. RESULTS: Our results demonstrate good performance of classifiers both on TFBS for transcription factors used for initial training and for TFBS for other factors in cross-classification experiments. We find that distances to chromatin modifications (specifically, histone modification islands as well as distances between such modifications to be effective predictors of TFBS occupancy, though the impact of individual predictors is largely TF specific. In our experiments, Bayesian network classifiers outperform SVM classifiers. CONCLUSIONS: Our results demonstrate good performance of machine learning techniques on the problem of occupancy classification, and demonstrate that effective classification can be achieved using distances to chromatin features. We additionally demonstrate that cross-classification of TFBS is possible, suggesting the possibility of constructing a generalizable occupancy classifier capable of handling TFBS for many different transcription factors.

  17. Multilevel Weighted Support Vector Machine for Classification on Healthcare Data with Missing Values.

    Directory of Open Access Journals (Sweden)

    Talayeh Razzaghi

    Full Text Available This work is motivated by the needs of predictive analytics on healthcare data as represented by Electronic Medical Records. Such data is invariably problematic: noisy, with missing entries, with imbalance in classes of interests, leading to serious bias in predictive modeling. Since standard data mining methods often produce poor performance measures, we argue for development of specialized techniques of data-preprocessing and classification. In this paper, we propose a new method to simultaneously classify large datasets and reduce the effects of missing values. It is based on a multilevel framework of the cost-sensitive SVM and the expected maximization imputation method for missing values, which relies on iterated regression analyses. We compare classification results of multilevel SVM-based algorithms on public benchmark datasets with imbalanced classes and missing values as well as real data in health applications, and show that our multilevel SVM-based method produces fast, and more accurate and robust classification results.

  18. Definitions for warning signs and signs of severe dengue according to the WHO 2009 classification: Systematic review of literature.

    Science.gov (United States)

    Morra, Mostafa Ebraheem; Altibi, Ahmed M A; Iqtadar, Somia; Minh, Le Huu Nhat; Elawady, Sameh Samir; Hallab, Asma; Elshafay, Abdelrahman; Omer, Omer Abedlbagi; Iraqi, Ahmed; Adhikari, Purushottam; Labib, Jonair Hussein; Elhusseiny, Khaled Mosaad; Elgebaly, Ahmed; Yacoub, Sophie; Huong, Le Thi Minh; Hirayama, Kenji; Huy, Nguyen Tien

    2018-04-24

    Since warning signs and signs of severe dengue are defined differently between studies, we conducted a systematic review on how researchers defined these signs. We conducted an electronic search in Scopus to identify relevant articles, using key words including dengue, "warning signs," "severe dengue," and "classification." A total of 491 articles were identified through this search strategy and were subsequently screened by 2 independent reviewers for definitions of any of the warning or severe signs in the 2009 WHO dengue classification. We included all original articles published in English after 2009, classifying dengue by the 2009 WHO classification or providing the additional definition or criterion of warning signs and severity (besides the information of 2009 WHO). Analysis of the extracted data from 44 articles showed wide variations among definitions and cutoff values used by physicians to classify patients diagnosed with dengue infection. The establishment of clear definitions for warning signs and severity is essential to prevent unnecessary hospitalization and harmonizing the interpretation and comparability of epidemiological studies dedicated to dengue infection. Copyright © 2018 John Wiley & Sons, Ltd.

  19. Respiratory severity score and extubation readiness in very low birth weight infants

    Directory of Open Access Journals (Sweden)

    Maroun J. Mhanna

    2017-12-01

    Full Text Available Background: The respiratory severity score (RSS is a byproduct of mean airway pressure (MAP and fraction of inspired oxygen (FiO2. We sought to determine whether RSS could be used as a screening tool to predict extubation readiness in very low birth weight (VLBW infants. Methods: In a retrospective cohort study, medical records of all VLBW infants admitted to our unit (6/1/09–2/28/12 were reviewed for infants' demographics, prenatal characteristics, and medication use. Also, records were reviewed for unplanned vs. planned extubation, blood gas, ventilator parameters and signs of severe respiratory failure [RF, defined as partial pressure of carbon dioxide (pCO2 > 65, pH  50%, and MAP > 10 cm] on the day of extubation. Results: During the study period 31% (45/147 failed extubation. Overall, infants who failed extubation had a lower birth weight (BW and gestational age (GA, and on the day of extubation had a higher RSS and percentage of having one or more signs of severe RF. In a logistic regression model, adjusting for BW, GA, RSS and RF, RSS remained the only risk factor associated with extubation failure [adjusted OR 1.63 (95% CI: 1.10–2.40; p = 0.01]. RSS had a sensitivity of 0.86 (95% CI: 0.72–0.94 at a cutoff of 1.26 and a specificity of 0.88 (95% CI: 0.80–0.94 at a cutoff of 2.5. There was no difference in extubation failure between unplanned vs. planned extubation [41% (9/22 vs. 29% (36/125; p = 0.25]. Conclusion: An elevated RSS is associated with extubation failure. Successful unplanned extubation is common in VLBW infants. Key Words: very low birth weight, extubation, mechanical ventilation, respiratory severity score

  20. Classification of Several Optically Complex Waters in China Using in Situ Remote Sensing Reflectance

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    Qian Shen

    2015-11-01

    Full Text Available Determining the dominant optically active substances in water bodies via classification can improve the accuracy of bio-optical and water quality parameters estimated by remote sensing. This study provides four robust centroid sets from in situ remote sensing reflectance (Rrs (λ data presenting typical optical types obtained by plugging different similarity measures into fuzzy c-means (FCM clustering. Four typical types of waters were studied: (1 highly mixed eutrophic waters, with the proportion of absorption of colored dissolved organic matter (CDOM, phytoplankton, and non-living particulate matter at approximately 20%, 20%, and 60% respectively; (2 CDOM-dominated relatively clear waters, with approximately 45% by proportion of CDOM absorption; (3 nonliving solids-dominated waters, with approximately 88% by proportion of absorption of nonliving particulate matter; and (4 cyanobacteria-composed scum. We also simulated spectra from seven ocean color satellite sensors to assess their classification ability. POLarization and Directionality of the Earth's Reflectances (POLDER, Sentinel-2A, and MEdium Resolution Imaging Spectrometer (MERIS were found to perform better than the rest. Further, a classification tree for MERIS, in which the characteristics of Rrs (709/Rrs (681, Rrs (560/Rrs (709, Rrs (560/Rrs (620, and Rrs (709/Rrs (761 are integrated, is also proposed in this paper. The overall accuracy and Kappa coefficient of the proposed classification tree are 76.2% and 0.632, respectively.

  1. Eighty Kilograms Weight Reduction in a Case of Obstructive Sleep Apnea with Several Comorbidities: Did the Conditions Improve?

    Directory of Open Access Journals (Sweden)

    Moein Foroughi

    2016-05-01

    Full Text Available Obstructive sleep apnea (OSA together with metabolic disorders is common in severely obese patients. Weight reduction is considered as a treatment modality in these cases while few of them can succeed in considerable weight loss. Here, we present a severely obese man with body mass index of 54 suffered from OSA, type 2 diabetes, hypothyroidism, and hypertension. He intentionally lost 80 kilograms weight during the 2-year follow-up. Diabetes and hypertension completely resolved with considerable improvement in OSA syndrome after this huge weight reduction.

  2. Diffusion-weighted MR and apparent diffusion coefficient in the evaluation of severe brain injury

    International Nuclear Information System (INIS)

    Nakahara, M.; Ericson, K.; Bellander, B.M.

    2001-01-01

    Purpose: To study apparent diffusion coefficient (ADC) maps in severely brain-injured patients. Material and Methods: Four deeply comatose patients with severe brain injury were investigated with single-shot, diffusion-weighted, spin-echo echo planar imaging. The tetrahedral diffusion gradient configuration and four iterations of a set of b-values (one time of 0 mm2/s, and four times of 1000 mm2/s) were used to create isotropic ADC maps with high signal-to-noise ratio. ADC values of gray and white matter were compared among patients and 4 reference subjects. Results: one patient was diagnosed as clinically brain dead after the MR examination. The patient's ADC values of gray and white matter were significantly lower than those of 3 other brain-injured patients. In addition the ADC value of white matter was significantly lower than that of gray matter. Conclusion: The patient with fatal outcome shortly after MR examination differed significantly from other patients with severe brain injury but non-fatal outcome, with regard to ADC values in gray and white matter. This might indicate a prognostic value of ADC maps in the evaluation of traumatic brain injury

  3. Hypothalamic obesity in patients with craniopharyngioma: Profound changes of several weight regulatory circuits

    Directory of Open Access Journals (Sweden)

    Christian eRoth

    2011-10-01

    Full Text Available One of the most striking examples of dysfunctional hypothalamic signaling of energy homeostasis is observed in patients with hypothalamic lesions leading to hypothalamic obesity (HO. This drastic condition is frequently seen in patients with craniopharyngioma (CP, an embryological tumor located in the hypothalamic and/or pituitary region, frequently causing not only hypopituitarism, but also leading to damage of medial hypothalamic nuclei due to the tumor and its treatment. HO syndrome in CP patients is characterized by fatigue, decreased physical activity, uncontrolled appetite, and morbid obesity, and is associated with insulin and leptin resistance. Mechanisms leading to the profoundly disturbed energy homeostasis are complex. This review summarizes different aspects of important clinical studies as well as data obtained in rodent studies. In addition a model is provided describing how medial hypothalamic lesion can interact simultaneously with several weight regulating circuitries.

  4. Transport package response to severe thermal events, part 2: legal weight truck cask

    International Nuclear Information System (INIS)

    Greiner, M.; Faulkner, R.J.; Jin, Y.Y.

    1998-01-01

    The response of intact and damaged versions of the GA-4 Legal Weight Truck Cask to a range of severe thermal events is simulated using finite element computer analysis. The minimum fire durations that cause the containment seals and fuel cladding to reach their respective temperature limits are evaluated for a range of hydrocarbon fire temperatures. Containment seals reach their temperature limit in shorter duration fires as compared to the cladding, for both an undamaged package and a cask whose impact limiter is destroyed moments before the fire begins. However, if the neutron shield is destroyed, the cladding reaches its limit first in high temperature fires. A margin of safety exists between the conditions of the IAEA regulatory fire test and all of the performance envelopes calculated in this work. (author)

  5. Management of severe subarachnoid hemorrhage (SAH) with diffusion-weighted imaging in acute stage

    International Nuclear Information System (INIS)

    Shamoto, Hiroshi; Shimizu, Hiroaki; Matsumoto, Yasushi; Fujiwara, Satoru; Tominaga, Teiji

    2007-01-01

    Determining the treatment strategy of severe subarachnoid hemorrhage (SAH) (Hunt and Kosnik Grade 4 and 5) requires objective evaluation to represent severity. In the present study, we investigated the role of diffusion-weighted imaging (DWI) in the acute stage as an objective tool. DWI was performed within 48 hours after the onset and preoperatively in 36 patients who fulfilled following the inclusion criteria: admission Hunt and Kosnik Grade 4 or 5, and Fischer Group 3. Twelve of 14 patients without abnormal findings in DWI underwent surgery in the acute stage. Although 2 of 14 patients with high age were supposed to undergo surgery in the chronic stage, 1 patient died in aneurysmal re-rupture. Glasgow outcome scales (GOS) were good recovery (GR) in 5, moderate disability (MD) in 6, standard deviation (SD) in 1 and D in 2 patients. Thirteen of 22 patients with DWI abnormality had small lesions less than 10 mm in diameter. Twelve of 13 patients underwent surgery in the acute stage, and 1 died of aneurysmal re-rupture while waiting for surgery in the chronic stage. GOS were GR in 3, MD in 4, SD in 3 and D in 3 patients. Although 5 patients with diffuse DWI lesions underwent surgery in the acute stage, 2 were SD and 3 were D. Four patients were supposed to undergo delayed surgery. However, 2 of them died of recurrent hemorrhage while waiting. GOS were SD in 2 and D in 2 patients. The present study indicates that DWI may provide objective evaluation of brain damage in severe SAH. However, since there were varieties of DWI findings and clinical courses, careful decisions must be taken in management of severe SAH patients. (author)

  6. Impact of weight loss achieved through a multidisciplinary intervention on appetite in patients with severe obesity

    DEFF Research Database (Denmark)

    Coutinho, Silvia R; Rehfeld, Jens F; Holst, Jens J

    2018-01-01

    The impact of lifestyle-induced weight loss (WL) on appetite in patients with obesity remains controversial. This study aimed was to assess the short- and long-term impact of WL achieved by diet and exercise, on appetite in patients with obesity. Thirty-five (22 females) adults with severe obesity......), in the fasting and postprandial states, were measured at baseline (B), week 4 (W4), 1 and 2-years (and average values for all fasting and postprandial time points computed). BW was significantly reduced and VO2max (ml/kg/min) increased at all time points compared with B (3.5, 8.1 and 8.4 % WL and 7, 11 and 8...... compared with B. Average GLP-1 was reduced at W4 and CCK increased at 2y. After lifestyle-induced WL, patients with severe obesity will, therefore, have to deal with increased hunger in the long-term. In conclusion, sustained WL at 2y achieved with diet and exercise is associated with increased hunger...

  7. A comparison of perceived and calculated weight status classification congruence between pre- and post-bariatric surgery patients.

    Science.gov (United States)

    Ferriby, Megan; Pratt, Keeley; Noria, Sabrena; Needleman, Bradley

    2017-08-01

    One prominent reason patients undergo bariatric surgery is to reduce their excess weight and body mass index. Weight status classifications (WSCs), based on calculated body mass index, organize patients into distinct groups (underweight, healthy weight, overweight, class I obesity, class II obesity, and class III obesity) for treatment recommendations, including surgery for patients with obesity. Bariatric patients' perceptions of their WSC is important to consider, because patients who accurately perceive their WSC presurgery have greater motivation for health behavior changes; alternatively, incongruence between perceived and calculated WSC could deter motivation and ultimately their health changes postsurgery. This study seeks to understand the congruence between patients' perceived and calculated WSC, and to determine if there are differences in congruence between groups of pre- or postsurgery, male and female, and emerging/early adulthood and middle/late adulthood patients. University Hospital. Self-report measures. Results indicate the presurgery patients were more congruent in their perceptions of WSC compared with their postsurgery peers and emerging/early adulthood patients were more congruent in their perceptions of WSC compared with middle/late adulthood patients. No gender differences emerged in the full sample, but when divided by surgical status, presurgery females reported more congruent perceptions of WSC compared with their postsurgery peers. Males did not differ in their rates of congruence. These rates of incongruence may suggest a need for assessment of patients' perceived WSC, particularly postsurgery. Published by Elsevier Inc.

  8. Severe Impairments of Social Interaction and Associated Abnormalities in Children: Epidemiology and Classification.

    Science.gov (United States)

    Wing, Lorna; Gould, Judith

    1979-01-01

    The prevalence of severe impairments of social interaction, language abnormalities, and repetitive stereotyped behaviors was investigated in a group of 132 children under 15 years old, consisting of a socially impaired group (more than half of whom were severely retarded) and a comparison group of sociable severely mentally retarded. Author/DLS)

  9. Fluid mechanics based classification of the respiratory efficiency of several nasal cavities.

    Science.gov (United States)

    Lintermann, Andreas; Meinke, Matthias; Schröder, Wolfgang

    2013-11-01

    The flow in the human nasal cavity is of great importance to understand rhinologic pathologies like impaired respiration or heating capabilities, a diminished sense of taste and smell, and the presence of dry mucous membranes. To numerically analyze this flow problem a highly efficient and scalable Thermal Lattice-BGK (TLBGK) solver is used, which is very well suited for flows in intricate geometries. The generation of the computational mesh is completely automatic and highly parallelized such that it can be executed efficiently on High Performance Computers (HPCs). An evaluation of the functionality of nasal cavities is based on an analysis of pressure drop, secondary flow structures, wall-shear stress distributions, and temperature variations from the nostrils to the pharynx. The results of the flow fields of three completely different nasal cavities allow their classification into ability groups and support the a priori decision process on surgical interventions. © 2013 Elsevier Ltd. All rights reserved.

  10. Characterizing severe obesity in children and youth referred for weight management.

    Science.gov (United States)

    Salawi, Hebah A; Ambler, Kathryn A; Padwal, Rajdeep S; Mager, Diana R; Chan, Catherine B; Ball, Geoff D C

    2014-06-19

    Severe obesity (SO) in pediatrics has become increasing prevalent in recent decades.The objective of our study was to examine differences in demographic, anthropometric, cardiometabolic, and lifestyle variables in children and youth with SO versus their less overweight/obese (OW/OB) peers. A retrospective medical record review of 6-19 year old participants enrolled in an outpatient pediatric weight management clinic was conducted. SO (body mass index [BMI] ≥99(th) percentile) and OW/OB (BMI ≥85(th) and $50,000/year (65.7%). The SO group (n = 161) had lower HDL-cholesterol and higher liver enzymes, insulin resistance and blood pressure than the OW/OB group (n = 184; all p youth in the SO group failed to meet moderate-to-vigorous physical activity (48.4% vs 31.9%) and leisure-time-screen-time recommendations (43.4% vs 28.3%; both p youth with SO have a worse cardiometabolic profile and less favorable lifestyle habits than their OW/OB peers. These differences emphasize the heightened obesity-related health risks associated with SO in the pediatric years.

  11. Mortality in severe trauma patients attended by emergency services in Navarre, Spain: validation of a new prediction model and comparison with the Revised Injury Severity Classification Score II.

    Science.gov (United States)

    Ali Ali, Bismil; Lefering, Rolf; Fortún Moral, Mariano; Belzunegui Otano, Tomás

    2018-01-01

    To validate the Mortality Prediction Model of Navarre (MPMN) to predict death after severe trauma and compare it to the Revised Injury Severity Classification Score II (RISCII). Retrospective analysis of a cohort of severe trauma patients (New Injury Severity Score >15) who were attended by emergency services in the Spanish autonomous community of Navarre between 2013 and 2015. The outcome variable was 30-day all-cause mortality. Risk was calculated with the MPMN and the RISCII. The performance of each model was assessed with the area under the receiver operating characteristic (ROC) curve and precision with respect to observed mortality. Calibration was assessed with the Hosmer-Lemeshow test. We included 516 patients. The mean (SD) age was 56 (23) years, and 363 (70%) were males. Ninety patients (17.4%) died within 30 days. The 30-day mortality rates predicted by the MPMN and RISCII were 16.4% and 15.4%, respectively. The areas under the ROC curves were 0.925 (95% CI, 0.902-0.952) for the MPMN and 0.941 (95% CI, 0.921-0.962) for the RISCII (P=0.269, DeLong test). Calibration statistics were 13.6 (P=.09) for the MPMN and 8.9 (P=.35) for the RISCII. Both the MPMN and the RISCII show good ability to discriminate risk and predict 30-day all-cause mortality in severe trauma patients.

  12. Weight-Related Correlates of Psychological Dysregulation in Adolescent and Young Adult (AYA) Females with Severe Obesity

    Science.gov (United States)

    Gowey, Marissa A.; Reiter-Purtill, Jennifer; Becnel, Jennifer; Peugh, James; Mitchell, James E.; Zeller, Meg H.

    2016-01-01

    Objective Severe obesity is the fastest growing pediatric subgroup of excess weight levels. Psychological dysregulation (i.e., impairments in regulating cognitive, emotional, and/or behavioral processes) has been associated with obesity and poorer weight loss outcomes. The present study explored associations of dysregulation with weight-related variables among adolescent and young adult (AYA) females with severe obesity. Methods Fifty-four AYA females with severe obesity (MBMI=48.71 kg/m2; Mage=18.29, R=15–21 years; 59.3% White) completed self-report measures of psychological dysregulation and weight-related constructs including meal patterns, problematic eating behaviors, and body and weight dissatisfaction, as non-surgical comparison participants in a multi-site study of adolescent bariatric surgery outcomes. Pearson and bivariate correlations were conducted and stratified by age group to analyze associations between dysregulation subscales (affective, behavioral, cognitive) and weight-related variables. Results Breakfast was the most frequently skipped meal (consumed 3–4 times/week). Eating out was common (4–5 times/week) and mostly occurred at fast-food restaurants. Evening hyperphagia (61.11%) and eating in the absence of hunger (37.04%) were commonly endorsed, while unplanned eating (29.63%), a sense of loss of control over eating (22.22%), eating beyond satiety (22.22%), night eating (12.96%), and binge eating (11.11%) were less common. Almost half of the sample endorsed extreme weight dissatisfaction. Dysregulation was associated with most weight-related attitudes and behaviors of interest in young adults but select patterns emerged for adolescents. Conclusions Higher levels of psychological dysregulation are associated with greater BMI, problematic eating patterns and behaviors, and body dissatisfaction in AYA females with severe obesity. These findings have implications for developing novel intervention strategies for severe obesity in AYAs that may

  13. Classification of hematopoietic regions in out-of-phase T{sub 1}-weighted images. A quantitative comparison study with T{sub 1}-weighted and STIR images

    Energy Technology Data Exchange (ETDEWEB)

    Amano, Yasuo; Amano, Maki; Kijima, Tetsuji; Kumazaki, Tatsuo [Nippon Medical School, Tokyo (Japan)

    1995-07-01

    The hematopoietic regions were classified into two groups on the basis of out-of-phase T{sub 1}-weighted images (op-TlWI): regions with lower intensity than that of muscle (LH) and regions with intensity equal to or higher than that of muscle (HH). We quantitatively evaluated the differences in signal intensity between LH and HH in order to examine this classification. Forty-two hematopoietic areas in aplastic anemia were classified into two groups of 23 LH and 19 HH. The signal ratios of hematopoietic areas to muscle on TlWI and STIR were calculated, and the differences between LH and HH were statistically evaluated. The signal ratios of LH were significantly higher on TlWI and lower on STIR than those of HH (unpaired t-test, p<0.05). This result indicated that LH consisted of more hypocellular marrow than HH. Op-TlWI were useful in differentiating between LH and HH and defining the degree of hematopoiesis in aplastic anemia. (author).

  14. Classification of hematopoietic regions in out-of-phase T1-weighted images. A quantitative comparison study with T1-weighted and STIR images

    International Nuclear Information System (INIS)

    Amano, Yasuo; Amano, Maki; Kijima, Tetsuji; Kumazaki, Tatsuo

    1995-01-01

    The hematopoietic regions were classified into two groups on the basis of out-of-phase T 1 -weighted images (op-TlWI): regions with lower intensity than that of muscle (LH) and regions with intensity equal to or higher than that of muscle (HH). We quantitatively evaluated the differences in signal intensity between LH and HH in order to examine this classification. Forty-two hematopoietic areas in aplastic anemia were classified into two groups of 23 LH and 19 HH. The signal ratios of hematopoietic areas to muscle on TlWI and STIR were calculated, and the differences between LH and HH were statistically evaluated. The signal ratios of LH were significantly higher on TlWI and lower on STIR than those of HH (unpaired t-test, p<0.05). This result indicated that LH consisted of more hypocellular marrow than HH. Op-TlWI were useful in differentiating between LH and HH and defining the degree of hematopoiesis in aplastic anemia. (author)

  15. A case of severe anorexia, excessive weight loss and high peptide YY levels after sleeve gastrectomy.

    Science.gov (United States)

    Pucci, Andrea; Cheung, Wui Hang; Jones, Jenny; Manning, Sean; Kingett, Helen; Adamo, Marco; Elkalaawy, Mohamed; Jenkinson, Andrew; Finer, Nicholas; Doyle, Jacqueline; Hashemi, Majid; Batterham, Rachel L

    2015-01-01

    Sleeve gastrectomy (SG) is the second most commonly performed bariatric procedure worldwide. Altered circulating gut hormones have been suggested to contribute post-operatively to appetite suppression, decreased caloric intake and weight reduction. In the present study, we report a 22-year-old woman who underwent laparoscopic SG for obesity (BMI 46 kg/m(2)). Post-operatively, she reported marked appetite reduction, which resulted in excessive weight loss (1-year post-SG: BMI 22 kg/m(2), weight loss 52%, >99th centile of 1-year percentage of weight loss from 453 SG patients). Gastrointestinal (GI) imaging, GI physiology/motility studies and endoscopy revealed no anatomical cause for her symptoms, and psychological assessments excluded an eating disorder. Despite nutritional supplements and anti-emetics, her weight loss continued (BMI 19 kg/m(2)), and she required nasogastric feeding. A random gut hormone assessment revealed high plasma peptide YY (PYY) levels. She underwent a 3 h meal study following an overnight fast to assess her subjective appetite and circulating gut hormone levels. Her fasted nausea scores were high, with low hunger, and these worsened with nutrient ingestion. Compared to ten other post-SG female patients, her fasted circulating PYY and nutrient-stimulated PYY and active glucagon-like peptide 1 (GLP1) levels were markedly elevated. Octreotide treatment was associated with suppressed circulating PYY and GLP1 levels, increased appetite, increased caloric intake and weight gain (BMI 22 kg/m(2) after 6 months). The present case highlights the value of measuring gut hormones in patients following bariatric surgery who present with anorexia and excessive weight loss and suggests that octreotide treatment can produce symptomatic relief and weight regain in this setting. Roux-en-Y gastric bypass and SG produce marked sustained weight reduction. However, there is a marked individual variability in this reduction, and post-operative weight loss

  16. Severe obesity and comorbid condition impact on the weight-related quality of life of the adolescent patient.

    Science.gov (United States)

    Zeller, Meg H; Inge, Thomas H; Modi, Avani C; Jenkins, Todd M; Michalsky, Marc P; Helmrath, Michael; Courcoulas, Anita; Harmon, Carroll M; Rofey, Dana; Baughcum, Amy; Austin, Heather; Price, Karin; Xanthakos, Stavra A; Brandt, Mary L; Horlick, Mary; Buncher, Ralph

    2015-03-01

    To assess links between comorbid health status, severe excess weight, and weight-related quality of life (WRQOL) in adolescents with severe obesity and undergoing weight-loss surgery (WLS) to inform clinical care. Baseline (preoperative) data from Teen Longitudinal Assessment of Bariatric Surgery, a prospective multicenter observational study of 242 adolescents with severe obesity (MedianBMI = 50.5 kg/m(2); Meanage = 17.1; 75.6% female; 71.9% white) undergoing WLS, were used to examine the impact of demographics, body mass index (BMI), presence/absence of 16 comorbid conditions, and a cumulative comorbidity load (CLoad) index on WRQOL scores (Impact of Weight on Quality of Life-Kids). WRQOL was significantly lower than reference samples of healthy weight, overweight, and obese samples. Of 16 comorbid conditions, the most prevalent were dyslipidemia (74.4%), chronic pain (58.3%), and obstructive sleep apnea (56.6%). Male subjects had a greater CLoad (P = .01) and BMI (P = .01), yet less impairment in total WRQOL (P conditions (eg, stress urinary incontinence) also emerged as contributors to lower WRQOL. WRQOL impairment is substantial for adolescents with severe obesity undergoing WLS, with predictors varying by sex. These patient-data highlight targets for education, support, and adjunctive care referrals before WLS. Furthermore, they provide a comprehensive empirical base for understanding heterogeneity in adolescent WRQOL outcomes after WLS, as weight and comorbidity profiles change over time. Copyright © 2015 Elsevier Inc. All rights reserved.

  17. APPLICATION OF MULTIPLE LOGISTIC REGRESSION, BAYESIAN LOGISTIC AND CLASSIFICATION TREE TO IDENTIFY THE SIGNIFICANT FACTORS INFLUENCING CRASH SEVERITY

    Directory of Open Access Journals (Sweden)

    MILAD TAZIK

    2017-11-01

    Full Text Available Identifying cases in which road crashes result in fatality or injury of drivers may help improve their safety. In this study, datasets of crashes happened in TehranQom freeway, Iran, were examined by three models (multiple logistic regression, Bayesian logistic and classification tree to analyse the contribution of several variables to fatal accidents. For multiple logistic regression and Bayesian logistic models, the odds ratio was calculated for each variable. The model which best suited the identification of accident severity was determined based on AIC and DIC criteria. Based on the results of these two models, rollover crashes (OR = 14.58, %95 CI: 6.8-28.6, not using of seat belt (OR = 5.79, %95 CI: 3.1-9.9, exceeding speed limits (OR = 4.02, %95 CI: 1.8-7.9 and being female (OR = 2.91, %95 CI: 1.1-6.1 were the most important factors in fatalities of drivers. In addition, the results of the classification tree model have verified the findings of the other models.

  18. Angiogenic, neurotrophic, and inflammatory system SNPs moderate the association between birth weight and ADHD symptom severity

    NARCIS (Netherlands)

    Smith, T.F.; Anastopoulos, A.D.; Garrett, M.E.; Arias Vasquez, A.; Franke, B.; Oades, R.D.; Sonuga-Barke, E.; Asherson, P.; Gill, M.; Buitelaar, J.K.; Sergeant, J.A.; Kollins, S.H.; Faraone, S.V.; Ashley-Koch, A.; Consortium, I.

    2014-01-01

    Low birth weight is associated with increased risk for Attention-Deficit/Hyperactivity Disorder (ADHD); however, the etiological underpinnings of this relationship remain unclear. This study investigated if genetic variants in angiogenic, dopaminergic, neurotrophic, kynurenine, and cytokine-related

  19. The Effectiveness of a Nondiet Multidisciplinary Weight Reduction Program for Severe Overweight Patients with Psychological Comorbidities

    Directory of Open Access Journals (Sweden)

    Bettina Bannert

    2011-01-01

    Full Text Available Objective. For successful sustainable weight reduction, a multimodal program including behaviour therapy is needed. Lifestyle modification is mostly used for obesity BMI 40 kg/m2 with psychological comorbidity. Research Methods and Procedere. A retrospective data analysis of 99 participants who passed the program based on moderate activity, healthy and regular food intake over metabolic rate and behaviour therapy was conducted. Results. 64 had a BMI >40 kg/m2 (mean value 49.99±8.74. The relative weight reduction was −6.9 ± 3.9%; (Friedman test P40 kg/m2 may achieve significant changes of weight reduction and psychological symptoms. However, the primary outcome should not be weight reduction. It is necessary to identify the benefits of lifestyle modification on changing risk profiles and emotional regulation of food intake.

  20. [Vocal cord paralysis associated with tracheal intubation: incidence, risk analysis, and classification of severity].

    Science.gov (United States)

    Kikura, Mutsuhito; Suzuki, Yuji; Itagaki, Taiga; Sato, Tsunehisa; Nishino, Junko

    2015-01-01

    Vocal cord paralysis after tracheal intubation is rare. It causes severe hoarseness and aspiration, and delays recovery and discharge. Arytenoid cartilage dislocation and recurrent nerve paralysis are main causes of vocal cord paralysis. Physical stimulation of the tracheal tube as well as patient and surgical characteristics also contribute. Vocal cord paralysis occurs in 1 (0.07%) of 1,500 general surgery patients and on the left side in 70% of cases. It is associated with surgery/anesthesia time (two-fold, 3-6 hours; 15-fold, over 6 hours), age (three-fold, over 50 years), and diabetes mellitus or hypertension (two-fold). Symptoms resolve in 2-3 months. In adult cardiovascular surgery, vocal cord paralysis occurs in 1 (0.7-2%) of 50-100 cardiac surgery patients and 1 (8.6-32%) of 3-10 thoracic aortic surgery patients. In pediatric cardiac surgery, vocal cord paralysis occurs in 1 (0.1-0.5%) of 200-1,000 patients. We classified the severity of vocal cord paralysis as I, severe hoarseness; II, aspiration or dysphagia; and III, bilateral vocal cord paralysis, aspiration pneumonia, or the need for tracheal re-intubation or tracheotomy. We discuss the importance of informed consent for the patient and family.

  1. Detection and severity classification of extracardiac interference in {sup 82}Rb PET myocardial perfusion imaging

    Energy Technology Data Exchange (ETDEWEB)

    Orton, Elizabeth J., E-mail: eorton@physics.carleton.ca; Kemp, Robert A. de; Glenn Wells, R. [Division of Cardiology, Department of Medicine, University of Ottawa Heart Institute, 40 Ruskin Street, Ottawa, Ontario K1Y 4W7 (Canada); Department of Physics, Carleton University, 1125 Colonel By Drive, Ottawa, Ontario K1S 5B6 (Canada); Al Harbi, Ibraheem [Division of Cardiology, Department of Medicine, University of Ottawa Heart Institute, 40 Ruskin Street, Ottawa, Ontario K1Y 4W7 (Canada); Department of Medicine (Cardiology), King Fahad Hospital, Medina 42351 (Saudi Arabia); Klein, Ran [Division of Cardiology, Department of Medicine, University of Ottawa Heart Institute, 40 Ruskin Street, Ottawa, Ontario K1Y 4W7 (Canada); Department of Biomedical Engineering, Carleton University, 1125 Colonel By Drive, Ottawa, Ontario K1S 5B6 (Canada); Beanlands, Rob S. B. [Division of Cardiology, Department of Medicine, University of Ottawa Heart Institute, 40 Ruskin Street, Ottawa, Ontario K1Y 4W7 (Canada)

    2014-10-15

    Purpose: Myocardial perfusion imaging (MPI) is used for diagnosis and prognosis of coronary artery disease. When MPI studies are performed with positron emission tomography (PET) and the radioactive tracer rubidium-82 chloride ({sup 82}Rb), a small but non-negligible fraction of studies (∼10%) suffer from extracardiac interference: high levels of tracer uptake in structures adjacent to the heart which mask the true cardiac tracer uptake. At present, there are no clinically available options for automated detection or correction of this problem. This work presents an algorithm that detects and classifies the severity of extracardiac interference in {sup 82}Rb PET MPI images and reports the accuracy and failure rate of the method. Methods: A set of 200 {sup 82}Rb PET MPI images were reviewed by a trained nuclear cardiologist and interference severity reported on a four-class scale, from absent to severe. An automated algorithm was developed that compares uptake at the external border of the myocardium to three thresholds, separating the four interference severity classes. A minimum area of interference was required, and the search region was limited to that facing the stomach wall and spleen. Maximizing concordance (Cohen’s Kappa) and minimizing failure rate for the set of 200 clinician-read images were used to find the optimal population-based constants defining search limit and minimum area parameters and the thresholds for the algorithm. Tenfold stratified cross-validation was used to find optimal thresholds and report accuracy measures (sensitivity, specificity, and Kappa). Results: The algorithm was capable of detecting interference with a mean [95% confidence interval] sensitivity/specificity/Kappa of 0.97 [0.94, 1.00]/0.82 [0.66, 0.98]/0.79 [0.65, 0.92], and a failure rate of 1.0% ± 0.2%. The four-class overall Kappa was 0.72 [0.64, 0.81]. Separation of mild versus moderate-or-greater interference was performed with good accuracy (sensitivity

  2. A risk prediction model for severe intraventricular hemorrhage in very low birth weight infants and the effect of prophylactic indomethacin.

    Science.gov (United States)

    Luque, M J; Tapia, J L; Villarroel, L; Marshall, G; Musante, G; Carlo, W; Kattan, J

    2014-01-01

    Develop a risk prediction model for severe intraventricular hemorrhage (IVH) in very low birth weight infants (VLBWI). Prospectively collected data of infants with birth weight 500 to 1249 g born between 2001 and 2010 in centers from the Neocosur Network were used. Forward stepwise logistic regression model was employed. The model was tested in the 2011 cohort and then applied to the population of VLBWI that received prophylactic indomethacin to analyze its effect in the risk of severe IVH. Data from 6538 VLBWI were analyzed. The area under ROC curve for the model was 0.79 and 0.76 when tested in the 2011 cohort. The prophylactic indomethacin group had lower incidence of severe IVH, especially in the highest-risk groups. A model for early severe IVH prediction was developed and tested in our population. Prophylactic indomethacin was associated with a lower risk-adjusted incidence of severe IVH.

  3. Weight-related correlates of psychological dysregulation in adolescent and young adult (AYA) females with severe obesity.

    Science.gov (United States)

    Gowey, Marissa A; Reiter-Purtill, Jennifer; Becnel, Jennifer; Peugh, James; Mitchell, James E; Zeller, Meg H

    2016-04-01

    Severe obesity is the fastest growing pediatric subgroup of excess weight levels. Psychological dysregulation (i.e., impairments in regulating cognitive, emotional, and/or behavioral processes) has been associated with obesity and poorer weight loss outcomes. The present study explored associations of dysregulation with weight-related variables among adolescent and young adult (AYA) females with severe obesity. Fifty-four AYA females with severe obesity (MBMI = 48.71 kg/m(2); Mage = 18.29, R = 15-21 years; 59.3% White) completed self-report measures of psychological dysregulation and weight-related constructs including meal patterns, problematic eating behaviors, and body and weight dissatisfaction, as non-surgical comparison participants in a multi-site study of adolescent bariatric surgery outcomes. Pearson and bivariate correlations were conducted and stratified by age group to analyze associations between dysregulation subscales (affective, behavioral, cognitive) and weight-related variables. Breakfast was the most frequently skipped meal (consumed 3-4 times/week). Eating out was common (4-5 times/week) and mostly occurred at fast-food restaurants. Evening hyperphagia (61.11%) and eating in the absence of hunger (37.04%) were commonly endorsed, while unplanned eating (29.63%), a sense of loss of control over eating (22.22%), eating beyond satiety (22.22%), night eating (12.96%), and binge eating (11.11%) were less common. Almost half of the sample endorsed extreme weight dissatisfaction. Dysregulation was associated with most weight-related attitudes and behaviors of interest in young adults but select patterns emerged for adolescents. Higher levels of psychological dysregulation are associated with greater BMI, problematic eating patterns and behaviors, and body dissatisfaction in AYA females with severe obesity. These findings have implications for developing novel intervention strategies for severe obesity in AYAs that may have a multidimensional

  4. Severe obesity and cardiometabolic risk in children: comparison from two international classification systems.

    Directory of Open Access Journals (Sweden)

    Giuliana Valerio

    Full Text Available There is no agreed-upon definition for severe obesity (Sev-OB in children. We compared estimates of Sev-OB as defined by different cut-points of body mass index (BMI from the Centers for Disease Control and Prevention (CDC or the World Health Organization (WHO curves and the ability of each set of cut-points to screen for the presence of cardiometabolic risk factors.Cross-sectional, multicenter study involving 3,340 overweight/obese young subjects. Sev-OB was defined as BMI ≥ 99(th percentile or ≥ 1.2 times the 95(th percentile of the CDC or the WHO curves. High blood pressure, hypertriglyceridemia, low High Density Lipoprotein -cholesterol and impaired fasting glucose were considered as cardiometabolic risk factors.The estimated prevalence of Sev-OB varied widely between the two reference systems. Either using the cut-point ≥ 99(th percentile or ≥ 1.2 times the 95(th percentile, less children were defined as Sev-OB by CDC than WHO (46.8 vs. 89.5%, and 63.3 vs. 80.4%, respectively p<0.001. The CDC 99(th percentile had lower sensitivity (58.5 vs 94.2, higher specificity (57.6 vs 12.3 and higher positive predictive value (34.4 vs 28.9 than WHO in identifying obese children with ≥ 2 cardiometabolic risk factors. These differences were mitigated using the 1.2 times the 95(th percentile (sensitivity 73.9 vs. 88.1; specificity 40.7 vs. 22.5; positive predictive value 32.1 vs. 30.1. Substantial agreement between growth curves was found using the 1.2 times the 95(th percentile, in particular in children ≤ 10 years.Estimates of Sev-OB and cardiometabolic risk as defined by different cut-points of BMI are influenced from the reference systems used. The 1.2 times the 95(th percentile of BMI of either CDC or WHO standard has a discriminatory advantage over the 99(th percentile for identifying severely obese children at increased cardiometabolic risk, particularly under 10 years of age.

  5. Total motile sperm count: a better indicator for the severity of male factor infertility than the WHO sperm classification system.

    Science.gov (United States)

    Hamilton, J A M; Cissen, M; Brandes, M; Smeenk, J M J; de Bruin, J P; Kremer, J A M; Nelen, W L D M; Hamilton, C J C M

    2015-05-01

    Does the prewash total motile sperm count (TMSC) have a better predictive value for spontaneous ongoing pregnancy (SOP) than the World Health Organization (WHO) classification system? The prewash TMSC shows a better correlation with the spontaneous ongoing pregnancy rate (SOPR) than the WHO 2010 classification system. According to the WHO classification system, an abnormal semen analysis can be diagnosed as oligozoospermia, astenozoospermia, teratozoospermia or combinations of these and azoospermia. This classification is based on the fifth percentile cut-off values of a cohort of 1953 men with proven fertility. Although this classification suggests accuracy, the relevance for the prognosis of an infertile couple and the choice of treatment is questionable. The TMSC is obtained by multiplying the sample volume by the density and the percentage of A and B motility spermatozoa. We analyzed data from a longitudinal cohort study among unselected infertile couples who were referred to three Dutch hospitals between January 2002 and December 2006. Of the total cohort of 2476 infertile couples, only the couples with either male infertility as a single diagnosis or unexplained infertility were included (n = 1177) with a follow-up period of 3 years. In all couples a semen analysis was performed. Based on the best semen analysis if more tests were performed, couples were grouped according to the WHO classification system and the TMSC range, as described in the Dutch national guidelines for male infertility. The primary outcome measure was the SOPR, which occurred before, during or after treatments, including expectant management, intrauterine insemination, in vitro fertilization or intracytoplasmic sperm injection. After adjustment for the confounding factors (female and male age, duration and type of infertility and result of the postcoital test) the odd ratios (ORs) for risk of SOP for each WHO and TMSC group were calculated. The couples with unexplained infertility were

  6. Early corticosteroid treatment does not affect severity of unconjugated hyperbilirubinemia in extreme low birth weight preterm infants

    NARCIS (Netherlands)

    Hulzebos, Christian V.; Bos, Arend F.; Anttila, Eija; Hallman, Mikko; Verkade, Henkjan J.

    Aim: To determine the relationship between early postnatal dexamethasone (DXM) treatment and the severity of hyperbilirubinemia in extreme low birth weight (ELBW) preterm infants. Methods: In 54 ELBW preterm infants, total serum bilirubin concentrations (TSB) and phototherapy (PT) data during the

  7. [Nordic accident classification system used in the Danish National Hospital Registration System to register causes of severe traumatic brain injury].

    Science.gov (United States)

    Engberg, Aase Worsaa; Penninga, Elisabeth Irene; Teasdale, Thomas William

    2007-11-05

    The purpose was to illustrate the use of the accident classification system worked out by the Nordic Medico-Statistical Committee (NOMESCO). In particular, registration of causes of severe traumatic brain injury according to the system as part of the Danish National Hospital Registration System was studied. The study comprised 117 patients with very severe traumatic brain injury (TBI) admitted to the Brain Injury Unit of the University Hospital in Hvidovre, Copenhagen, from 1 October 2000 to 30 September 2002. Prospective NOMESCO coding at discharge was compared to independent retrospective coding based on hospital records, and to coding from other wards in the Danish National Hospital Registration System. Furthermore, sets of codes in the Danish National Hospital Registration System for consecutive admissions after a particular accident were compared. Identical results of prospective and independent retrospective coding were found for 65% of 588 single codes, and complete sets of codes for the same accident were identical only in 28% of cases. Sets of codes for the first admission in a hospital course corresponded to retrospective coding at the end of the course in only 17% of cases. Accident code sets from different wards, based on the same injury, were identical in only 7% of cases. Prospective coding by the NOMESCO accident classification system proved problematic, both with regard to correctness and completeness. The system--although logical--seems too complicated compared to the resources invested in the coding. The results of this investigation stress the need for better management and for better instruction to those who carry out the registration.

  8. Estimation of utility weights for human papilloma virus-related health states according to disease severity.

    Science.gov (United States)

    Ock, Minsu; Park, Jeong-Yeol; Son, Woo-Seung; Lee, Hyeon-Jeong; Kim, Seon-Ha; Jo, Min-Woo

    2016-11-28

    A cost-utility study of a human papilloma virus (HPV) vaccine requires that the utility weights for HPV-related health states (i.e., cervical intraepithelial neoplasia (CIN), cervical cancer, and condyloma) be evaluated. The aim of the present study was to determine the utility weights for HPV-related health states. Hypothetical standardised health states related to HPV were developed based on patient education material and previous publications. To fully reflect disease progression from diagnosis to prognosis, each health state comprised four parts (diagnosis, symptoms, treatment, and progression and prognosis). Nine-hundred members from the Korean general population evaluated the HPV-related health states using a visual analogue scale (VAS) and a standard gamble (SG) approach, which were administered face-to-face via computer-assisted interview. The mean utility values were calculated for each HPV-related health state. According to the VAS, the highest utility (0.73) was HPV-positive status, followed by condyloma (0.66), and CIN grade I (0.61). The lowest utility (0.18) was cervical cancer requiring chemotherapy without surgery, followed by cervical cancer requiring chemoradiation therapy (0.42). SG revealed that the highest utility (0.83) was HPV-positive status, followed by condyloma (0.78), and CIN grade I (0.77). The lowest utility (0.43) was cervical cancer requiring chemotherapy without surgery, followed by cervical cancer requiring chemoradiation therapy (0.60). This study was based on a large sample derived from the general Korean population; therefore, the calculated utility weights might be useful for evaluating the economic benefit of cancer screening and HPV vaccination programs.

  9. Severe posterior reversible encephalopathy in pheochromocytoma: Importance of susceptibility-weighted MRI

    Energy Technology Data Exchange (ETDEWEB)

    Serter, Asil; Alkan, Alpay; Aralasmak, Ayse; Kocakoc, Ercan [Dept. of Radiology, Bezmialem Vakif University School of Medicine, Istanbul (Turkmenistan)

    2013-10-15

    Pheochromocytoma is a rare cause of hypertension in children. Hypertension is one of the common reasons of posterior reversible encephalopathy. Intracerebral hemorrhage is a serious and unexpected complication of hypertensive encephalopathy due to pheochromocytoma, and very rarely seen in the childhood. Intracerebral hemorrhages should be searched if there are hypertensive reversible signal changes on the brain. Susceptibility weighted imaging (SWI) is a more sensitive method than conventional MRI when demonstrating cerebral microhemorrhagic foci. This is the first report of SWI findings on intracerebral hemorrhages in basal ganglia, brain stem and periventricular white matter due to hypertensive encephalopathy in a child with pheochromocytoma.

  10. SPECTRUM WEIGHTED RESPONSES OF SEVERAL DETECTORS IN MIXED FIELDS OF FAST AND THERMAL NEUTRONS

    Directory of Open Access Journals (Sweden)

    SANG IN KIM

    2014-04-01

    Full Text Available The spectrum weighted responses of various detectors were calculated to provide guidance on the proper selection and use of survey instruments on the basis of their energy response characteristics on the neutron fields. To yield the spectrum weighted response, the detector response functions of 17 neutron-measuring devices were numerically folded with each of the produced calibration neutron spectra through the in-house developed software ‘K-SWR’. The detectors’ response functions were taken from the IAEA Technical Reports Series No. 403 (TRS-403. The reference neutron fields of 21 kinds with 2 spectra groups with different proportions of thermal and fast neutrons have been produced using neutrons from the 241Am-Be sources held in a graphite pile, a bare 241Am-Be source, and a DT neutron generator. Fluence-average energy (Eave varied from 3.8 MeV to 16.9 MeV, and the ambient-dose-equivalent rate [H*(10/h] varied from 0.99 to 16.5 mSv/h.

  11. Genetic variants associated with severe retinopathy of prematurity in extremely low birth weight infants.

    Science.gov (United States)

    Hartnett, M Elizabeth; Morrison, Margaux A; Smith, Silvia; Yanovitch, Tammy L; Young, Terri L; Colaizy, Tarah; Momany, Allison; Dagle, John; Carlo, Waldemar A; Clark, Erin A S; Page, Grier; Murray, Jeff; DeAngelis, Margaret M; Cotten, C Michael

    2014-08-12

    To determine genetic variants associated with severe retinopathy of prematurity (ROP) in a candidate gene cohort study of US preterm infants. Preterm infants in the discovery cohort were enrolled through the Eunice Kennedy Shriver National Institute of Child Health and Human Development Neonatal Research Network, and those in the replication cohort were from the University of Iowa. All infants were phenotyped for ROP severity. Because of differences in the durations of enrollment between cohorts, severe ROP was defined as threshold disease in the discovery cohort and as threshold disease or type 1 ROP in the replication cohort. Whole genome amplified DNA from stored blood spot samples from the Neonatal Research Network biorepository was genotyped using an Illumina GoldenGate platform for candidate gene single nucleotide polymorphisms (SNPs) involving angiogenic, developmental, inflammatory, and oxidative pathways. Three analyses were performed to determine significant epidemiologic variables and SNPs associated with levels of ROP severity. Analyses controlled for multiple comparisons, ancestral eigenvalues, family relatedness, and significant epidemiologic variables. Single nucleotide polymorphisms significantly associated with ROP severity from the discovery cohort were analyzed in the replication cohort and in meta-analysis. Eight hundred seventeen infants in the discovery cohort and 543 in the replication cohort were analyzed. Severe ROP occurred in 126 infants in the discovery and in 14 in the replication cohort. In both cohorts, ventilation days and seizure occurrence were associated with severe ROP. After controlling for significant factors and multiple comparisons, two intronic SNPs in the gene BDNF (rs7934165 and rs2049046, P large candidate gene study of infants with threshold ROP. Copyright 2014 The Association for Research in Vision and Ophthalmology, Inc.

  12. One-Year Behavioral Treatment of Obesity: Comparison of Moderate and Severe Caloric Restriction and the Effects of Weight Maintenance Therapy.

    Science.gov (United States)

    Wadden, Thomas A.; And Others

    1994-01-01

    Compared weight losses of 49 obese women assigned to 52-week behavioral program combined with moderate or severe caloric restriction. Those in severe caloric restriction group lost significantly more weight during first 26 weeks but regained some weight. Reports of binge eating declined in both groups, and no relationship was observed between…

  13. Grading Dysphagia as a Toxicity of Head and Neck Cancer: Differences in Severity Classification Based on MBS DIGEST and Clinical CTCAE Grades.

    Science.gov (United States)

    Goepfert, Ryan P; Lewin, Jan S; Barrow, Martha P; Warneke, Carla L; Fuller, Clifton D; Lai, Stephen Y; Weber, Randal S; Hutcheson, Katherine A

    2018-04-01

    Clinician-reported toxicity grading through common terminology criteria for adverse events (CTCAE) stages dysphagia based on symptoms, diet, and tube dependence. The new dynamic imaging grade of swallowing toxicity (DIGEST) tool offers a similarly scaled five-point ordinal summary grade of pharyngeal swallowing as determined through results of a modified barium swallow (MBS) study. This study aims to inform clinicians on the similarities and differences between dysphagia severity according to clinical CTCAE and MBS-derived DIGEST grading. A cross-sectional sample of 95 MBS studies was randomly selected from a prospectively-acquired MBS database among patients treated with organ preservation strategies for head and neck cancer. MBS DIGEST and clinical CTCAE dysphagia grades were compared. DIGEST and CTCAE dysphagia grades had "fair" agreement per weighted κ of 0.358 (95% CI .231-.485). Using a threshold of DIGEST ≥ 3 as reference, CTCAE had an overall sensitivity of 0.50, specificity of 0.84, and area under the curve (AUC) of 0.67 to identify severe MBS-detected dysphagia. At less than 6 months, sensitivity was 0.72, specificity was 0.76, and AUC was 0.75 while at greater than 6 months, sensitivity was 0.22, specificity was 0.90, and AUC was 0.56 for CTCAE to detect dysphagia as determined by DIGEST. Classification of pharyngeal dysphagia on MBS using DIGEST augments our understanding of dysphagia severity according to the clinically-derived CTCAE while maintaining the simplicity of an ordinal scale. DIGEST likely complements CTCAE toxicity grading through improved specificity for physiologic dysphagia in the acute phase and improved sensitivity for dysphagia in the late-phase.

  14. Association between the Family Nutrition and Physical Activity Screening Tool and obesity severity in youth referred to weight management.

    Science.gov (United States)

    Tucker, Jared M; Howard, Kathleen; Guseman, Emily H; Yee, Kimbo E; Saturley, Heather; Eisenmann, Joey C

    The Family Nutrition and Physical Activity Screening Tool (FNPA) evaluates family behavioural and environmental factors associated with pediatric obesity, but it is unknown if FNPA scores differ among youth across obesity severities. Our aim was to determine the association between the FNPA and obesity severity in youth referred to weight management. Upon initiating treatment, height, weight, and the FNPA were collected according to standard procedures. Cut-points for overweight/obesity, severe obesity (SO) class 2, and SO class 3 were calculated. FNPA scores were compared across weight status groups using analysis of covariance, and odds of SO across FNPA quartiles were evaluated with multiple logistic regression. Participants included 564 5-18year old who initiated treatment and completed the FNPA. After adjustment, FNPA scores differed by weight status with higher/healthier scores in youth with overweight/obesity (56.6±8.5) when compared to those with SO class 2 (55.0±7.1; p=0.015) or SO class 3 (53.6±9.0; p<0.001). Compared to those in the highest FNPA quartile, youth in the 2nd quartile had 1.8 (95% CI: 1.1, 2.9) times higher odds of SO, and those in the lowest FNPA quartile had 2.1 (95% CI: 1.3, 3.4) times higher odds of SO. Youth with SO had unhealthier subscale scores among 6 of 10 constructs, including nutritional, physical activity, sedentary, and sleep behaviours. Results suggest a consistent inverse relationship between the FNPA and adiposity among youth presenting for weight management. The FNPA is a useful metric for programs and clinicians targeting family behaviours and the home environment to combat obesity. Copyright © 2016 Asia Oceania Association for the Study of Obesity. Published by Elsevier Ltd. All rights reserved.

  15. High incidence of rickets in extremely low birth weight infants with severe parenteral nutrition-associated cholestasis and bronchopulmonary dysplasia.

    Science.gov (United States)

    Lee, Soon Min; Namgung, Ran; Park, Min Soo; Eun, Ho Sun; Park, Kook In; Lee, Chul

    2012-12-01

    Risk factors for rickets of prematurity have not been re-examined since introduction of high mineral formula, particularly in ELBW infants. We analyzed the incidence and the risk factors of rickets in extremely low birth weight (ELBW) infants. As a retrospective case-control study from 2004 to 2008, risk factors were analyzed in 24 patients with rickets versus 31 patients without. The frequency of rickets in ELBW infants was 24/55 (44%). Infants with rickets were diagnosed at 48.2 ± 16.1 days of age, and improved by 85.3 ± 25.3 days. By radiologic evaluation, 29% were grade 1 rickets, 58% grade 2 and 13% grade 3. In univariate analysis, infants with rickets had significantly higher incidence of patent ductus arteriosus, parenteral nutrition associated cholestasis (PNAC), severe PNAC and moderate/severe bronchopulmonary dysplasia (BPD). In multiple regression analysis, after adjustment for gestation and birth weight, rickets significantly correlated with severe PNAC and with moderate/severe BPD. Serum peak alkaline phosphatase levels were significantly elevated in rickets (P rickets of prematurity remains high and the incidence of severe PNAC and moderate/severe BPD was significantly increased 18 and 3 times, respectively.

  16. Psychological Outcomes and Predictors of Initial Weight Loss Outcomes among Severely Obese Adolescents Receiving Laparoscopic Adjustable Gastric Banding

    Science.gov (United States)

    Sysko, Robyn; Devlin, Michael J.; Hildebrandt, Tom B.; Brewer, Stephanie K.; Zitsman, Jeffrey L.; Walsh, B. Timothy

    2013-01-01

    Objective Elevated rates of psychopathology are noted among severely obese youth presenting for weight loss surgery. The role of mental health providers in this population is not well defined, and the selection of candidates is often the result of clinical judgment alone. The purpose of this study was to comprehensively evaluate psychiatric symptoms among a large sample of adolescents receiving laparoscopic adjustable gastric banding (LAGB) by: (1) examining changes in depressive symptoms and quality of life in the year following surgery, (2) evaluating the interaction between patterns of change in depression, quality of life, and weight post-surgery, and (3) identifying pre-surgical psychological predictors of initial weight change. Method Participants were 101 severely obese adolescents aged 14 to 18. Measures of height, weight, depressive symptoms, and quality of life were obtained in the first year following surgery. Changes in the Beck Depression Inventory (BDI), Pediatric Quality of Life Inventory (PedsQL), and body mass index were analyzed using latent growth curve modeling. Results Significant changes in total BDI [βslope=−0.885 SE=0.279, psurgery (pAdolescents experienced notable improvements in initial depressive symptoms and quality of life after LAGB, and measures of pre-operative binge eating and family conflict affected post-surgery body mass index among youth. PMID:23140654

  17. Comparison of STIR turbo SE imaging and diffusion-weighted imaging of the lung: capability for detection and subtype classification of pulmonary adenocarcinomas

    Energy Technology Data Exchange (ETDEWEB)

    Koyama, Hisanobu; Ohno, Yoshiharu; Onishi, Yumiko; Matsumoto, Keiko; Nogami, Munenobu; Takenaka, Daisuke; Sugimura, Kazuro [Kobe University Graduate School of Medicine, Department of Radiology, Kobe, Hyogo (Japan); Aoyama, Nobukazu [Kobe University Hospital, Division of Radiology, Kobe (Japan); Nishio, Wataru [Kobe University Graduate School of Medicine, Division of Cardiovascular, Thoracic and Pediatric Surgery, Kobe (Japan); Ohbayashi, Chiho [Hyogo Cancer Center, Division of Pathology, Akashi (Japan)

    2010-04-15

    The aim of the study was to evaluate the diagnostic performance of diffusion-weighted imaging (DWI) for detection and subtype classification in pulmonary adenocarcinomas through comparison with short TI inversion recovery turbo spin-echo imaging sequence (STIR). Thirty-two patients (mean age, 65.2 years) with 33 adenocarcinomas (mean diameter, 27.6 mm) were enrolled in this study. The detection rates of both sequences were compared. The ADC values on DWI and the contrast ratio (CR) between cancer and muscle on STIR were measured and those were compared across subtype classifications. Finally, ROC-based positive tests were performed to differentiate subtype classifications, and differentiation capabilities were compared. The DWI detection rate [85% (28/33)] was significantly lower than that of STIR [100% (33/33), P < 0.05]. The ADC values showed no significant difference regarding subtype classification; however, the CRs of bronchio-alveolar carcinomas (BACs) were significantly lower than those of other types (P < 0.05). When threshold values for differentiating BACs from others were adapted, the sensitivity and accuracy of DWI were significantly lower than those of STIR (P < 0.05). For differentiating adenocarcinomas with mixed subtypes from those with no BA component, there were no significant differences between the two sequences. STIR is more sensitive for detection and subtype classification than DWI. (orig.)

  18. Assessing the Feasibility of a Social Media to Promote Weight Management Engagement in Adolescents with Severe Obesity: Pilot Study.

    Science.gov (United States)

    Prout Parks, Elizabeth; Moore, Reneé H; Li, Ziyi; Bishop-Gilyard, Chanelle T; Garrett, Andrew R; Hill, Douglas L; Bruton, Yasmeen P; Sarwer, David B

    2018-03-19

    Severe obesity in adolescents has deleterious physical and psychological complications necessitating frequent multi-disciplinary clinic visits. Greater treatment engagement has been equated with weight-loss. However, traditional medical weight-loss programs for adolescents have high attrition rates. Social media is widely used by adolescents and may enhance medical weight management engagement and success. The first objective was to examine the acceptability and feasibility of using a private social media group as an adjunct to medical weight management in youth ages 14 to 20 years with severe obesity [body mass index (BMI) ≥ 35 kg/m2]. The second objective was to pilot test the use of social media to improve treatment engagement and decrease attrition rates. In this single arm, 12 week pre-post study, participants attended individual clinic visits and participated in a moderated private social media group that received nutrition, exercise, and behavior change social media communications or "posts" 3 to 4 times/week. Youth commented and/or liked posts from the moderator and each other. Social media engagement was measured with the number of likes and comments on social media. Clinic attrition was compared, measuring clinic visit attendance 12 weeks prior, during, and after the intervention with mixed linear regression models. Correlations of social media engagement with changes from baseline for BMI, BMI-z score, and psychosocial measures were fit. All 13 enrolled youth completed the study and reported that the group was enjoyable, helpful, reinforced their weight management program, and would recommend using social media to support other youth. The pilot trial was acceptable and feasible. Youth mean weekly engagement (likes + comments) in social media was greater than once a day (8.6 ±3.6). Compared to 12 weeks prior to the intervention, there was no significant decrease in clinic visit attendance at the end of the intervention (M=.231, P=.69) or 12 weeks at

  19. Identification and application of the valid wavelength bands for burnt area detection and fire severity classification using Landsat/TM data

    International Nuclear Information System (INIS)

    Maki, M.; Tamura, M.

    2003-01-01

    Firstly, by using Landsat Thematic Mapper (TM) imagery before and after forest fire, the valid wavelength bands for detecting burnt areas were examined and compared to NDVI. Secondly, by using the valid wavelength bands, mapping of burnt area and classification of fire severity were examined. The results show that (a) channel 4 and 7 were more sensitive than other channels for detecting burnt area, (b) BAI (Burnt Area Index) [(ch. 4-ch. 7)/(ch. 4+ch. 7)] was more useful than NDVI for detecting burnt areas, and (c) BAI imagery was more useful for classification of burn severity than NDVI imagery

  20. Severity classification of repeated isoflurane anesthesia in C57BL/6JRj mice-Assessing the degree of distress.

    Directory of Open Access Journals (Sweden)

    Katharina Hohlbaum

    Full Text Available According to the EU Directive 2010/63, the severity of a procedure has to be classified as mild, moderate or severe. General anesthesia is thought to be mild, but the Directive does not differentiate between single and repeated anesthesia. Therefore, we investigated the impact of repeated administration of isoflurane, the most commonly used inhalation anesthetic, on the well-being of adult C57BL/6JRj mice, in comparison to single administrations and to untreated animals, when applied six times for 45 min at an interval of 3-4 days. For the animals anesthetized, excitations, phases of anesthesia, and vital parameters were monitored. Well-being after anesthesia was assessed using a behavioral test battery including luxury behavior like burrowing and nest building behavior, the Mouse Grimace Scale (MGS, the free exploratory paradigm for anxiety-related behavior, home cage activity and the rotarod test for activity, as well as food intake and body weight. Additionally, hair corticosterone and fecal corticosterone metabolites were measured. Our results show that nest building behavior, home cage activity, body weight, and corticosterone concentrations were not influenced by anesthesia, whereas changes in burrowing behavior, the MGS, food intake, and the free exploratory behavior indicated that the well-being of the mice was more affected by repeated than single isoflurane anesthesia. This effect depended on the sex of the animals, with female mice being more susceptible than male mice. However, repeated isoflurane anesthesia caused only short-term mild distress and impairment of well-being, mainly in the immediate postanesthetic period. Well-being stabilized at 8 days after the last anesthesia, at the latest. Therefore, we conclude that when using our anesthesia protocol, the severity of both single and repeated isoflurane anesthesia in C57BL/6JRj mice can be classified as mild. However, within the mild severity category, repeated isoflurane

  1. Two year reduction in sleep apnea symptoms and associated diabetes incidence after weight loss in severe obesity.

    Science.gov (United States)

    Grunstein, Ronald R; Stenlöf, Kaj; Hedner, Jan A; Peltonen, Markku; Karason, Kristjan; Sjöström, Lars

    2007-06-01

    To evaluate the effect of bariatric surgery on sleep apnea symptoms and obesity-associated morbidity in patients with severe obesity. Prospective study. University hospitals and community centers in Sweden. We investigated the influence of weight loss surgery (n=1729) on sleep apnea symptoms and obesity-related morbidity using a conservatively treated group (n=1748) as a control. Baseline BMI in surgical group (42.2+/-4.4 kg/m(2)) and control group (40.1+/-4.6 kg/m(2)) changed -9.7+/-5 kg/m(2) and 0+/-3 kg/m(2), respectively, at 2-year follow-up. In the surgery group, there was a marked improvement in all obstructive sleep apnea (OSA) symptoms compared with the control group (P sleep apnea symptoms at 2 years. Despite adjustment for weight change and baseline central obesity, subjects reporting loss of OSA symptoms had a lower 2-year incidence of diabetes and hypertriglyceridemia. Improvement in OSA in patients losing weight may provide health benefits in addition to weight loss alone.

  2. Inter-Labeler and Intra-Labeler Variability of Condition Severity Classification Models Using Active and Passive Learning Methods

    Science.gov (United States)

    Nissim, Nir; Shahar, Yuval; Boland, Mary Regina; Tatonetti, Nicholas P; Elovici, Yuval; Hripcsak, George; Moskovitch, Robert

    2018-01-01

    Background and Objectives Labeling instances by domain experts for classification is often time consuming and expensive. To reduce such labeling efforts, we had proposed the application of active learning (AL) methods, introduced our CAESAR-ALE framework for classifying the severity of clinical conditions, and shown its significant reduction of labeling efforts. The use of any of three AL methods (one well known [SVM-Margin], and two that we introduced [Exploitation and Combination_XA]) significantly reduced (by 48% to 64%) condition labeling efforts, compared to standard passive (random instance-selection) SVM learning. Furthermore, our new AL methods achieved maximal accuracy using 12% fewer labeled cases than the SVM-Margin AL method. However, because labelers have varying levels of expertise, a major issue associated with learning methods, and AL methods in particular, is how to best to use the labeling provided by a committee of labelers. First, we wanted to know, based on the labelers’ learning curves, whether using AL methods (versus standard passive learning methods) has an effect on the Intra-labeler variability (within the learning curve of each labeler) and inter-labeler variability (among the learning curves of different labelers). Then, we wanted to examine the effect of learning (either passively or actively) from the labels created by the majority consensus of a group of labelers. Methods We used our CAESAR-ALE framework for classifying the severity of clinical conditions, the three AL methods and the passive learning method, as mentioned above, to induce the classifications models. We used a dataset of 516 clinical conditions and their severity labeling, represented by features aggregated from the medical records of 1.9 million patients treated at Columbia University Medical Center. We analyzed the variance of the classification performance within (intra-labeler), and especially among (inter-labeler) the classification models that were induced by

  3. Inter-labeler and intra-labeler variability of condition severity classification models using active and passive learning methods.

    Science.gov (United States)

    Nissim, Nir; Shahar, Yuval; Elovici, Yuval; Hripcsak, George; Moskovitch, Robert

    2017-09-01

    Labeling instances by domain experts for classification is often time consuming and expensive. To reduce such labeling efforts, we had proposed the application of active learning (AL) methods, introduced our CAESAR-ALE framework for classifying the severity of clinical conditions, and shown its significant reduction of labeling efforts. The use of any of three AL methods (one well known [SVM-Margin], and two that we introduced [Exploitation and Combination_XA]) significantly reduced (by 48% to 64%) condition labeling efforts, compared to standard passive (random instance-selection) SVM learning. Furthermore, our new AL methods achieved maximal accuracy using 12% fewer labeled cases than the SVM-Margin AL method. However, because labelers have varying levels of expertise, a major issue associated with learning methods, and AL methods in particular, is how to best to use the labeling provided by a committee of labelers. First, we wanted to know, based on the labelers' learning curves, whether using AL methods (versus standard passive learning methods) has an effect on the Intra-labeler variability (within the learning curve of each labeler) and inter-labeler variability (among the learning curves of different labelers). Then, we wanted to examine the effect of learning (either passively or actively) from the labels created by the majority consensus of a group of labelers. We used our CAESAR-ALE framework for classifying the severity of clinical conditions, the three AL methods and the passive learning method, as mentioned above, to induce the classifications models. We used a dataset of 516 clinical conditions and their severity labeling, represented by features aggregated from the medical records of 1.9 million patients treated at Columbia University Medical Center. We analyzed the variance of the classification performance within (intra-labeler), and especially among (inter-labeler) the classification models that were induced by using the labels provided by seven

  4. High Adherence to CPAP Treatment Does Not Prevent the Continuation of Weight Gain among Severely Obese OSAS Patients

    Science.gov (United States)

    Myllylä, Minna; Kurki, Samu; Anttalainen, Ulla; Saaresranta, Tarja; Laitinen, Tarja

    2016-01-01

    Study Objectives: Obstructive sleep apnea syndrome (OSAS) patients benefit from continuous positive airway pressure (CPAP) treatment in a dose-response manner. We determined adherence and weight control, as well as their predictors, among long-term CPAP users. Methods: Cohort of 1,023 OSAS patients had used CPAP on average of 6.6 ± 1.2 years. BMI was determined at baseline and at follow-up visits. There were 7.4 ± 1.7 BMI and 6.5 ± 1.8 CPAP usage measurements per patient on average. Using the Bayesian hierarchical model, we determined the patients' individual trends of BMI and adherence development. Patients with significantly increasing or decreasing trends were identified at the posterior probability level of > 90%. Results: The mean age in the cohort was 55.6 ± 9.8 years, BMI 33.5 ± 6.4 kg/m2, apnea-hypopnea index 33.7 ± 23.1, and CPAP usage 6.0 ± 1.8 h/day. The majority of patients had no significant change in BMI (mean annual weight gain 0.04 ± 0.29 kg/m2) or CPAP adherence (mean annual increase 11.4 ± 7.0 min/day). However, at the individual level, 10% of the patients showed significant annual weight gain (0.63 ± 0.35 kg/m2) during the 5-year follow-up period. At baseline these patients were already more severely obese (mean BMI 40.0 ± 5.9 kg/m2) despite being younger (mean 50.9 ± 9.5 years) than the rest of the cohort. Conclusions: In the majority of CPAP-treated OSAS patients, weight did not significantly change but gained slightly slower than in age-matched population in general. However, in 10% of patients, high adherence to CPAP treatment did not prevent the continuation of weight gain. These patients present a high-risk group for OSAS-related multimorbidity later in life. Citation: Myllylä M, Kurki S, Anttalainen U, Saaresranta T, Laitinen T. High adherence to CPAP treatment does not prevent the continuation of weight gain among severely obese OSAS patients. J Clin Sleep Med 2016;12(4):519–528. PMID:26888588

  5. Appropriateness of clinical severity classification of new WHO childhood pneumonia guidance: a multi-hospital, retrospective, cohort study.

    Science.gov (United States)

    Agweyu, Ambrose; Lilford, Richard J; English, Mike

    2018-01-01

    Management of pneumonia in many low-income and middle-income countries is based on WHO guidelines that classify children according to clinical signs that define thresholds of risk. We aimed to establish whether some children categorised as eligible for outpatient treatment might have a risk of death warranting their treatment in hospital. We did a retrospective cohort study of children aged 2-59 months admitted to one of 14 hospitals in Kenya with pneumonia between March 1, 2014, and Feb 29, 2016, before revised WHO pneumonia guidelines were adopted in the country. We modelled associations with inpatient mortality using logistic regression and calculated absolute risks of mortality for presenting clinical features among children who would, as part of revised WHO pneumonia guidelines, be eligible for outpatient treatment (non-severe pneumonia). We assessed 16 162 children who were admitted to hospital in this period. 832 (5%) of 16 031 children died. Among groups defined according to new WHO guidelines, 321 (3%) of 11 788 patients with non-severe pneumonia died compared with 488 (14%) of 3434 patients with severe pneumonia. Three characteristics were strongly associated with death of children retrospectively classified as having non-severe pneumonia: severe pallor (adjusted risk ratio 5·9, 95% CI 5·1-6·8), mild to moderate pallor (3·4, 3·0-3·8), and weight-for-age Z score (WAZ) less than -3 SD (3·8, 3·4-4·3). Additional factors that were independently associated with death were: WAZ less than -2 to -3 SD, age younger than 12 months, lower chest wall indrawing, respiratory rate of 70 breaths per min or more, female sex, admission to hospital in a malaria endemic region, moderate dehydration, and an axillary temperature of 39°C or more. In settings of high mortality, WAZ less than -3 SD or any degree of pallor among children with non-severe pneumonia was associated with a clinically important risk of death. Our data suggest that admission to hospital

  6. Severe aortic stenosis patients with preserved ejection fraction according to flow and gradient classification: Prevalence and outcomes.

    Science.gov (United States)

    González Gómez, Ariana; Fernández-Golfín, Covadonga; Monteagudo, Juan Manuel; Izurieta, Carlos; Hinojar, Rocío; García, Ana; Casas, Eduardo; Jiménez-Nacher, José Julio; Moya, José Luis; Ruiz, Soledad; Zamorano, José Luis

    2017-12-01

    Clinicians often encounter patients with apparently discordant echocardiographic findings, severe aortic stenosis (SAS) defined by aortic valve area (AVA) despite a low mean gradient. A new classification according to flow state and pressure gradient has been proposed. We sought to assess the prevalence, characteristics and outcomes of patients with asymptomatic SAS with preserved left-ventricular ejection fraction (LVEF) according to flow and gradient. In total 442 patients with SAS (AVAigradient (≥ or Gradient (LF/LG): 21.3%(n=94); Normal Flow/Low Gradient (NF/LG): 32.1%(n=142); Low Flow/High Gradient (LF/HG): 6.8%(n=30); Normal Flow/High Gradient (NF/HG): 39,8%(n=176). Mean follow-up time was 20.5months (SD=10.3). Primary combined endpoint was cardiovascular mortality and hospital admission for SAS related symptom, secondary endpoint was aortic valve replacement (AVR), comparing HG group to LF/LG group. During follow-up 17 (18%) of LF/LG patients and 21 (10.2%) of HG patients met the primary endpoint. A lower free of event survival (cardiovascular mortality and hospital admission) was observed in patients with LF/LG AS (Breslow, p=0.002). Significant differences were noted between groups with a lower AVR free survival in the LF/LG group compared to HG groups (Breslow, p=0.002). Our study confirms the high prevalence and worse prognosis of LF/LG SAS. Clinicians must be aware of this entity to ensure appropriate patient management. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

  7. Non-invasive classification of severe sepsis and systemic inflammatory response syndrome using a nonlinear support vector machine: a preliminary study

    International Nuclear Information System (INIS)

    Tang, Collin H H; Savkin, Andrey V; Chan, Gregory S H; Middleton, Paul M; Bishop, Sarah; Lovell, Nigel H

    2010-01-01

    Sepsis has been defined as the systemic response to infection in critically ill patients, with severe sepsis and septic shock representing increasingly severe stages of the same disease. Based on the non-invasive cardiovascular spectrum analysis, this paper presents a pilot study on the potential use of the nonlinear support vector machine (SVM) in the classification of the sepsis continuum into severe sepsis and systemic inflammatory response syndrome (SIRS) groups. 28 consecutive eligible patients attending the emergency department with presumptive diagnoses of sepsis syndrome have participated in this study. Through principal component analysis (PCA), the first three principal components were used to construct the SVM feature space. The SVM classifier with a fourth-order polynomial kernel was found to have a better overall performance compared with the other SVM classifiers, showing the following classification results: sensitivity = 94.44%, specificity = 62.50%, positive predictive value = 85.00%, negative predictive value = 83.33% and accuracy = 84.62%. Our classification results suggested that the combinatory use of cardiovascular spectrum analysis and the proposed SVM classification of autonomic neural activity is a potentially useful clinical tool to classify the sepsis continuum into two distinct pathological groups of varying sepsis severity

  8. Relationships between World Health Organization "International Classification of Functioning, Disability and Health" Constructs and Participation in Adults with Severe Mental Illness

    Science.gov (United States)

    Sánchez, Jennifer; Rosenthal, David A.; Chan, Fong; Brooks, Jessica; Bezyak, Jill L.

    2016-01-01

    Purpose: To examine the World Health Organization "International Classification of Functioning, Disability and Health" (ICF) constructs as correlates of community participation of people with severe mental illnesses (SMI). Methods: Quantitative descriptive research design using multiple regression and correlational techniques was used to…

  9. Effect of adjuvant low-molecular-weight heparin therapy on placental hypoxia and cell apoptosis in puerperae with severe preeclampsia

    Directory of Open Access Journals (Sweden)

    Miao Zhou1

    2017-04-01

    Full Text Available Objective: To study the effect of adjuvant low-molecular-weight heparin therapy on placental hypoxia and cell apoptosis in puerperae with severe preeclampsia. Methods: A total of 94 puerperae with severe preeclampsia who received treatment and safely gave birth in our hospital between May 2014 and May 2016 were selected as the research subjects and randomly divided into the LMWH group who received low-molecular-weight heparin combined with conventional symptomatic treatment and the control group who received conventional symptomatic treatment. Before and after treatment, serum was collected respectively to determine the levels of placental hypoxia-related cytokines, and after delivery, the placentas were collected to detect oxidative stress indexes and cell apoptosis indexes. Results: After treatment, serum PLGF and PAPP-A levels of both groups were significantly higher than those before treatment while sFlt-1 and sEng levels were significantly lower than those before treatment, and after treatment, serum PLGF and PAPP-A levels of LMWH group were significantly higher than those of control group while sFlt-1 and sEng levels were significantly lower than those of control group; ROS and RNS levels as well as Fas, FasL, caspase-3 and caspase-8 protein expression in placenta tissue of LMWH group were significantly lower than those of control group while GPx-1, SOD-1 and Trx levels as well as Survivin, XIAP and Bcl-2 protein expression were significantly higher than those of control group. Conclusion: Adjuvant low-molecular-weight heparin therapy can relieve the placental hypoxia, improve oxidative stress reaction and inhibit cell apoptosis in puerperae with severe preeclampsia.

  10. Examining Spatial Variation in the Effects of Japanese Red Pine (Pinus densiflora on Burn Severity Using Geographically Weighted Regression

    Directory of Open Access Journals (Sweden)

    Hyun-Joo Lee

    2017-05-01

    Full Text Available Burn severity has profound impacts on the response of post-fire forest ecosystems to fire events. Numerous previous studies have reported that burn severity is determined by variables such as meteorological conditions, pre-fire forest structure, and fuel characteristics. An underlying assumption of these studies was the constant effects of environmental variables on burn severity over space, and these analyses therefore did not consider the spatial dimension. This study examined spatial variation in the effects of Japanese red pine (Pinus densiflora on burn severity. Specifically, this study investigated the presence of spatially varying relationships between Japanese red pine and burn severity due to changes in slope and elevation. We estimated conventional ordinary least squares (OLS and geographically weighted regression (GWR models and compared them using three criteria; the coefficients of determination (R2, Akaike information criterion for small samples (AICc, and Moran’s I-value. The GWR model performed considerably better than the OLS model in explaining variation in burn severity. The results provided strong evidence that the effect of Japanese red pine on burn severity was not constant but varied spatially. Elevation was a significant factor in the variation in the effects of Japanese red pine on burn severity. The influence of red pine on burn severity was considerably higher in low-elevation areas but became less important than the other variables in high-elevation areas. The results of this study can be applied to location-specific strategies for forest managers and can be adopted to improve fire simulation models to more realistically mimic the nature of fire behavior.

  11. Direct Kernel Perceptron (DKP): ultra-fast kernel ELM-based classification with non-iterative closed-form weight calculation.

    Science.gov (United States)

    Fernández-Delgado, Manuel; Cernadas, Eva; Barro, Senén; Ribeiro, Jorge; Neves, José

    2014-02-01

    The Direct Kernel Perceptron (DKP) (Fernández-Delgado et al., 2010) is a very simple and fast kernel-based classifier, related to the Support Vector Machine (SVM) and to the Extreme Learning Machine (ELM) (Huang, Wang, & Lan, 2011), whose α-coefficients are calculated directly, without any iterative training, using an analytical closed-form expression which involves only the training patterns. The DKP, which is inspired by the Direct Parallel Perceptron, (Auer et al., 2008), uses a Gaussian kernel and a linear classifier (perceptron). The weight vector of this classifier in the feature space minimizes an error measure which combines the training error and the hyperplane margin, without any tunable regularization parameter. This weight vector can be translated, using a variable change, to the α-coefficients, and both are determined without iterative calculations. We calculate solutions using several error functions, achieving the best trade-off between accuracy and efficiency with the linear function. These solutions for the α coefficients can be considered alternatives to the ELM with a new physical meaning in terms of error and margin: in fact, the linear and quadratic DKP are special cases of the two-class ELM when the regularization parameter C takes the values C=0 and C=∞. The linear DKP is extremely efficient and much faster (over a vast collection of 42 benchmark and real-life data sets) than 12 very popular and accurate classifiers including SVM, Multi-Layer Perceptron, Adaboost, Random Forest and Bagging of RPART decision trees, Linear Discriminant Analysis, K-Nearest Neighbors, ELM, Probabilistic Neural Networks, Radial Basis Function neural networks and Generalized ART. Besides, despite its simplicity and extreme efficiency, DKP achieves higher accuracies than 7 out of 12 classifiers, exhibiting small differences with respect to the best ones (SVM, ELM, Adaboost and Random Forest), which are much slower. Thus, the DKP provides an easy and fast way

  12. Long-term effects of weight reduction on the severity of psoriasis in a cohort derived from a randomized trial

    DEFF Research Database (Denmark)

    Jensen, Peter; Christensen, Robin; Zachariae, Claus

    2016-01-01

    randomized phase with an LED for 8 wk and 8 wk of normal food intake combined with 2 LED products/d, followed by a 48-wk period of weight maintenance with the latter diet. After the randomization phase, the control group received the same 8 + 8-wk LED intervention, and all patients were then followed for 48...... who were allocated to a control group or a low-energy diet (LED) group. Here we followed the participants for an additional 48-wk period. In total, 56 patients with psoriasis [mean ± SD body mass index (in kg/m(2)): 34.4 ± 5.3] underwent a 64-wk weight-loss program consisting of an initial 16-wk...... wk while on the weight-loss maintenance diet. The main outcome was the Psoriasis Area and Severity Index (PASI), and secondary outcome was the Dermatology Life Quality Index (DLQI). RESULTS: For the present study, 56 patients were eligible, 38 agreed to participate, and 32 completed. After the 16-wk...

  13. Body weight loss by very-low-calorie diet program improves small artery reactive hyperemia in severely obese patients.

    Science.gov (United States)

    Merino, J; Megias-Rangil, I; Ferré, R; Plana, N; Girona, J; Rabasa, A; Aragonés, G; Cabré, A; Bonada, A; Heras, M; Masana, L

    2013-01-01

    Endothelial dysfunction is a major underlying mechanism for the elevated cardiovascular risk associated with increased body weight. We aimed to assess the impact of weight loss induced by an intensive very-low-calorie diet (VLCD) on arterial wall function in severely obese patients (SOP). Thirty-four SOP were admitted to the metabolic ward of the hospital for a 3-week period. A VLCD characterized by a liquid diet providing 800 kcal/day was administered. The small artery reactivity to postischemic hyperemia index (saRHI), a surrogate marker of endothelial function, was assessed before and 1 week after hospital discharge. Anthropometry and biochemical parameters were also measured. Obese and non-obese age- and gender-matched groups were recruited for baseline comparisons. SOP had significantly lower saRHI compared with obese and non-obese individuals. SaRHI significantly increased after the intervention in SOP (1.595 ± 0.236 vs. 1.737 ± 0.417, p = 0.015). A significant improvement in glucose (p = 0.026), systolic blood pressure (p = 0.049), LDLc (p reactivity, and it was associated with the amelioration of metabolic and inflammation markers. Endothelial dysfunction may be softened by body weight loss interventions and useful in the management of cardiovascular risk factors in SOP.

  14. Serum cortisol values, superior vena cava flow and illness severity scores in very low birth weight infants.

    LENUS (Irish Health Repository)

    Miletin, J

    2012-02-01

    OBJECTIVE: Recent evidence suggests that high cortisol concentrations are associated with increased morbidity and mortality in very low birth weight (VLBW) infants. Neonatal illness severity and mortality risk scores are reliable in predicting morbidity and mortality. The objectives were (i) to assess the correlation between serum cortisol levels and clinical assessment of multi-organ dysfunction\\/illness severity scores (CRIB II, SNAPPE-II and neonatal multiple organ dysfunction score (NEOMOD)) in first 24 h in VLBW infants and (ii) to assess the relationship between surrogates of end organ blood flow and serum cortisol levels. STUDY DESIGN: A prospective observational cohort study. Neonates with birth weight <1500 g were eligible for enrollment. Echocardiography evaluation of superior vena cava (SVC) flow was carried out in the first 24 h life. Cortisol levels were measured simultaneously and appropriate clinical scores were calculated. RESULT: A total of 54 VLBW neonates were enrolled following parental consent. Two patients were excluded because of congenital malformations. In 14 babies the cortisol value was not simultaneously obtained. The mean birth weight was 1.08 kg, mean gestational age was 27.8 weeks. There was a significant correlation between cortisol and NEOMOD score (P=0.006). There was no correlation between cortisol and CRIB II score (P=0.34), SVC flow (P=0.49) and mean arterial blood pressure respectively (P=0.35). CONCLUSION: There was no correlation between SVC flow and cortisol values or between cortisol and mean blood pressure values. There was a significant correlation between cortisol levels and neonatal organ dysfunction score evaluated suggesting that stressed VLBW infants do mount a cortisol response.

  15. Total motile sperm count: a better indicator for the severity of male factor infertility than the WHO sperm classification system

    NARCIS (Netherlands)

    Hamilton, J.A.; Cissen, M.; Brandes, M.; Smeenk, J.M.; Bruin, J.P. de; Kremer, J.A.M.; Nelen, W.L.D.M.; Hamilton, C.J.C.M.

    2015-01-01

    STUDY QUESTION: Does the prewash total motile sperm count (TMSC) have a better predictive value for spontaneous ongoing pregnancy (SOP) than the World Health Organization (WHO) classification system? SUMMARY ANSWER: The prewash TMSC shows a better correlation with the spontaneous ongoing pregnancy

  16. Weight classification does not influence the short-term endocrine or metabolic effects of high-fructose corn syrup-sweetened beverages.

    Science.gov (United States)

    Heden, Timothy D; Liu, Ying; Kearney, Monica L; Kanaley, Jill A

    2014-05-01

    Obesity and high-fructose corn syrup (HFCS)-sweetened beverages are associated with an increased risk of chronic disease, but it is not clear whether obese (Ob) individuals are more susceptible to the detrimental effects of HFCS-sweetened beverages. The purpose of this study was to examine the endocrine and metabolic effects of consuming HFCS-sweetened beverages, and whether weight classification (normal weight (NW) vs. Ob) influences these effects. Ten NW and 10 Ob men and women who habitually consumed ≤355 mL per day of sugar-sweetened beverages were included in this study. Initially, the participants underwent a 4-h mixed-meal test after a 12-h overnight fast to assess insulin sensitivity, pancreatic and gut endocrine responses, insulin secretion and clearance, and glucose, triacylglycerol, and cholesterol responses. Next, the participants consumed their normal diet ad libitum, with 1065 mL per day (117 g·day(-1)) of HFCS-sweetened beverages added for 2 weeks. After the intervention, the participants repeated the mixed-meal test. HFCS-sweetened beverages did not significantly alter body weight, insulin sensitivity, insulin secretion or clearance, or endocrine, glucose, lipid, or cholesterol responses in either NW or Ob individuals. Regardless of previous diet, Ob individuals, compared with NW individuals, had ∼28% lower physical activity levels, 6%-9% lower insulin sensitivity, 12%-16% lower fasting high-density-lipoprotein cholesterol concentrations, 84%-144% greater postprandial triacylglycerol concentrations, and 46%-79% greater postprandial insulin concentrations. Greater insulin responses were associated with reduced insulin clearance, and there were no differences in insulin secretion. These findings suggest that weight classification does not influence the short-term endocrine and metabolic effects of HFCS-sweetened beverages.

  17. Interaction Effect Of Irradiation And Fertilization On Grain Yield, Kernel Weight And Severity Of Wheat To Septoria Tritici Blotch

    International Nuclear Information System (INIS)

    Arabi, M. A.; Jawhar, M.

    2004-01-01

    Field research was undertaken, for two growing seasons, to investigate the effects of soil fertilization with potassium (K 2 SO 4 , 36% K) and nitrogen (urea, 46% N), seed irradiation with gamma rays (0, 5, 10 and 15 Gy) and their combinations on the grain yield, 1000-kernel weight and severity of Mycosphaerella graminicola on wheat. Two Syrian wheat cultivars; Bohuth 6 (Triticum aestivum L.) and Bohuth 5 (T. turgidum var durum Desf.) were used in this study. Plants were inoculated with a mixture of 15 virulent isolates of the pathogen at the growth stage (GS) 33-34. Results indicated that the average response to fertilizer application and irradiation treatments was dependent on the susceptibility level of cultivars compared with the control. The level of infection of the combined NK and 15 Gy treatment was reduced by 9 and 46 % in 1998 and by 6 and 42 % in 1999 for Bohuth 5 and Bohuth 6, respectively. This was associated with increased grain yield by 68 and 59% in 1998 and 59 and 33% in 1999, respectively. Highest yield losses from M. graminicola occurred in the treatment of nil fertilization and irradiation. Grain weight was increased by various treatments applied, but such an increase was highest in the combined NK and 15 Gy treatment. This combined treatment appeared to be more effective on calcareous soils, which are typical of Mediterranean environments. (Authors)

  18. Severe cerebral hypovolemia on perfusion CT and lower body weight are associated with parenchymal haemorrhage after thrombolysis

    Energy Technology Data Exchange (ETDEWEB)

    Tsetsou, S.; Eskandari, A.; Michel, P. [Centre Hospitalier Universitaire Vaudois and University of Lausanne CHUV, Department of Neurology, Lausanne (Switzerland); Amiguet, M. [Centre Hospitalier Universitaire Vaudois and University of Lausanne, Institute of Social and Preventive Medicine, Lausanne (Switzerland); Meuli, R.; Maeder, P. [Centre Hospitalier Universitaire Vaudois and University of Lausanne, Department of Radiology, Lausanne (Switzerland); Jiang, B.; Wintermark, M. [Stanford University and Medical Center, Department of Radiology, Neuroradiology Division, Stanford, CA (United States)

    2017-01-15

    Haemorrhagic transformation of acute ischemic stroke (AIS) and particularly parenchymal haemorrhage (PH) remains a feared complication of intravenous thrombolysis (IVT). We aimed to identify clinical and perfusion CT (PCT) variables which are independently associated with PHs. In this observational cohort study, based on the Acute Stroke Registry Analysis of Lausanne (ASTRAL) from 2003 to December 2013, we selected patients with AIS involving the middle cerebral artery (MCA) territory who were thrombolysed within 4.5 h of symptoms' onset and who had a good quality baseline PCT at the beginning of IVT. In addition to demographic, clinical, laboratory and non-contrast CT data, volumes of salvageable tissue and ischemic core on PCT, as well as absolute CBF and CBV values within the ischemic regions were compared in patients with and without PH in multivariate analysis. Of the 190 included patients, 24 (12.6%) presented a PH (11 had PH1 and 13 had PH2). In multivariate analysis of the clinical and radiological variables, the lowest CBV in the core and lower body weight was both significantly associated with PH (p = 0.009 and p = 0.024, respectively). In thrombolysed MCA strokes, maximal hypoperfusion severity depicted by lowest CBV values in the core region and lower body weight are independently correlated with PH. This information, if confirmed in other case series, may add to the stratification of revascularisation decisions in patients with a perceived high PH risk. (orig.)

  19. Early corticosteroid treatment does not affect severity of unconjugated hyperbilirubinemia in extreme low birth weight preterm infants.

    Science.gov (United States)

    Hulzebos, Christian V; Bos, Arend F; Anttila, Eija; Hallman, Mikko; Verkade, Henkjan J

    2011-02-01

    To determine the relationship between early postnatal dexamethasone (DXM) treatment and the severity of hyperbilirubinemia in extreme low birth weight (ELBW) preterm infants. In 54 ELBW preterm infants, total serum bilirubin concentrations (TSB) and phototherapy (PT) data during the first 10 days were evaluated retrospectively. ELBW infants had participated in a randomized controlled trial of early DXM treatment which aimed to assess effects on chronic lung disease. Infants had been treated with DXM (0.25 mg/kg twice daily at postnatal day 1 and 2) or with placebo (normal saline). Analysis was performed on an intention to treat basis. Twenty-five Infants had been randomized into the DXM group; 29 into the placebo group. Mean (±SD) TSB [120 (±19) μmol/L vs. 123 (±28) μmol/L, DXM versus placebo, respectively] and maximum TSB [178 (±23) μmol/L vs. 176 (±48), DXM versus placebo, respectively] concentrations were similar. TSB concentrations peaked 30 h earlier in the DXM group (p ≤ 0.05). The need for PT as well as the duration of PT was similar in both groups. Early DXM treatment does not affect the severity of neonatal hyperbilirubinemia in ELBW preterm infants. Our results seem compatible with the concept that factors other than bilirubin conjugation capacity are important for the pathophysiology of neonatal jaundice in ELBW preterm infants. © 2010 The Author(s)/Acta Paediatrica © 2010 Foundation Acta Paediatrica.

  20. Exercise training with weight loss and either a high or low glycemic diet reduces metabolic syndrome severity in older adults

    Science.gov (United States)

    Malin, Steven K.; Niemi, Nicole; Solomon, Thomas P.J.; Haus, Jacob M.; Kelly, Karen R.; Filion, Julianne; Rocco, Michael; Kashyap, Sangeeta R.; Barkoukis, Hope; Kirwan, John P.

    2012-01-01

    Background The efficacy of combining carbohydrate quality with exercise on metabolic syndrome risk is unclear. Thus, we determined the effects of exercise training with a low or high glycemic diet on metabolic syndrome severity (Z-score). Methods Twenty-one adults (66.2 ± 1.1 yr; BMI = 35.3 ± 0.9 kg/m2) with metabolic syndrome were randomized to 12 weeks of exercise (60 minutes/d for 5 d/week at ~85% HRmax) and provided a low-glycemic (n=11; LoGIx) or high glycemic (n=10; HiGIx) diet. Z-scores were determined from: blood pressure, triglycerides (TG), high-density lipoproteins (HDL), fasting plasma glucose (FPG), and waist circumference (WC) before and after the intervention. Body composition, aerobic fitness, insulin resistance, and non-esterfied fatty acid (NEFA) suppression were also assessed. Results LoGIx and HiGIx decreased body mass and insulin resistance and increased aerobic fitness comparably (p exercise with weight loss reduces metabolic syndrome severity whether individuals were randomized to a high or low glycemic index diet. PMID:23036993

  1. Burke-Fahn-Marsden dystonia severity, Gross Motor, Manual Ability, and Communication Function Classification scales in childhood hyperkinetic movement disorders including cerebral palsy: a 'Rosetta Stone' study.

    Science.gov (United States)

    Elze, Markus C; Gimeno, Hortensia; Tustin, Kylee; Baker, Lesley; Lumsden, Daniel E; Hutton, Jane L; Lin, Jean-Pierre S-M

    2016-02-01

    Hyperkinetic movement disorders (HMDs) can be assessed using impairment-based scales or functional classifications. The Burke-Fahn-Marsden Dystonia Rating Scale-movement (BFM-M) evaluates dystonia impairment, but may not reflect functional ability. The Gross Motor Function Classification System (GMFCS), Manual Ability Classification System (MACS), and Communication Function Classification System (CFCS) are widely used in the literature on cerebral palsy to classify functional ability, but not in childhood movement disorders. We explore the concordance of these three functional scales in a large sample of paediatric HMDs and the impact of dystonia severity on these scales. Children with HMDs (n=161; median age 10y 3mo, range 2y 6mo-21y) were assessed using the BFM-M, GMFCS, MACS, and CFCS from 2007 to 2013. This cross-sectional study contrasts the information provided by these scales. All four scales were strongly associated (all Spearman's rank correlation coefficient rs >0.72, pdisorders including cerebral palsy can be effectively evaluated using these scales. © 2015 Mac Keith Press.

  2. Impact of two myostatin (MSTN mutations on weight gain and lamb carcass classification in Norwegian White Sheep (Ovis aries

    Directory of Open Access Journals (Sweden)

    Blichfeldt Thor

    2010-01-01

    Full Text Available Abstract Background Our aim was to estimate the effect of two myostatin (MSTN mutations in Norwegian White Sheep, one of which is close to fixation in the Texel breed. Methods The impact of two known MSTN mutations was examined in a field experiment with Norwegian White Sheep. The joint effect of the two MSTN mutations on live weight gain and weaning weight was studied on 644 lambs. Carcass weight gain from birth to slaughter, carcass weight, carcass conformation and carcass fat classes were calculated in a subset of 508 lambs. All analyses were carried out with a univariate linear animal model. Results The most significant impact of both mutations was on conformation and fat classes. The largest difference between the genotype groups was between the wild type for both mutations and the homozygotes for the c.960delG mutation. Compared to the wild types, these mutants obtained a conformation score 5.1 classes higher and a fat score 3.0 classes lower, both on a 15-point scale. Conclusions Both mutations reduced fatness and increased muscle mass, although the effect of the frameshift mutation (c.960delG was more important as compared to the 3'-UTR mutation (c.2360G>A. Lambs homozygous for the c.960delG mutation grew more slowly than those with other MSTN genotypes, but had the least fat and the largest muscle mass. Only c.960delG showed dominance effects.

  3. Comparison of severity classification in Japanese patients with antineutrophil cytoplasmic antibody-associated vasculitis in a nationwide, prospective, inception cohort study.

    Science.gov (United States)

    Sada, Ken-Ei; Harigai, Masayoshi; Amano, Koichi; Atsumi, Tatsuya; Fujimoto, Shouichi; Yuzawa, Yukio; Takasaki, Yoshinari; Banno, Shogo; Sugihara, Takahiko; Kobayashi, Masaki; Usui, Joichi; Yamagata, Kunihiro; Homma, Sakae; Dobashi, Hiroaki; Tsuboi, Naotake; Ishizu, Akihiro; Sugiyama, Hitoshi; Okada, Yasunori; Arimura, Yoshihiro; Matsuo, Seiichi; Makino, Hirofumi

    2016-09-01

    To compare disease severity classification systems for six-month outcome prediction in patients with antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV). Patients with newly diagnosed AAV from 53 tertiary institutions were enrolled. Six-month remission, overall survival, and end-stage renal disease (ESRD)-free survival were evaluated. According to the European Vasculitis Study Group (EUVAS)-defined disease severity, the 321 enrolled patients were classified as follows: 14, localized; 71, early systemic; 170, generalized; and 66, severe disease. According to the rapidly progressive glomerulonephritis (RPGN) clinical grading system, the patients were divided as follows: 60, grade I; 178, grade II; 66, grade III; and 12, grade IV. According to the Five-Factor Score (FFS) 2009, 103, 109, and 109 patients had ≤1, 2, and ≥3 points, respectively. No significant difference in remission rates was found in any severity classification. The overall and ESRD-free survival rates significantly differed between grades I/II, III, and IV, regardless of renal involvement. Severe disease was a good predictor of six-month overall and ESRD-free survival. The FFS 2009 was useful to predict six-month ESRD-free survival but not overall survival. The RPGN grading system was more useful to predict six-month overall and ESRD-free survival than the EUVAS-defined severity or FFS 2009.

  4. The stratification of severity of acute radiation proctopathy after radiotherapy for cervical carcinoma using diffusion-weighted MRI

    Energy Technology Data Exchange (ETDEWEB)

    Li, Xiang Sheng, E-mail: lxsheng500@163.com [Department of Radiology, Air Force General Hospital of People' s Liberation Army, Beijing 100142 (China); Fang, Hong, E-mail: hongfang196808@sina.com [Department of Radiology, Air Force General Hospital of People' s Liberation Army, Beijing 100142 (China); Song, Yunlong, E-mail: yunlongsong010@sina.com [Department of Radiology, Air Force General Hospital of People' s Liberation Army, Beijing 100142 (China); Li, Dechang, E-mail: dechangli1972@sina.com [Department of Pathology, Air Force General Hospital of People' s Liberation Army, Beijing 100142 (China); Wang, Yingjie, E-mail: wangyj19710813@sina.com [Department of Radiotherapy, Air Force General Hospital of People' s Liberation Army, Beijing 100142 (China); Zhu, Hongxian, E-mail: hongxian0102@sina.cn [Department of Radiology, Air Force General Hospital of People' s Liberation Army, Beijing 100142 (China); Meng, Limin, E-mail: liminmeng1977@sina.com [Department of Radiology, Air Force General Hospital of People' s Liberation Army, Beijing 100142 (China); Wang, Ping, E-mail: pingwang1978@sina.com [Department of Radiology, Air Force General Hospital of People' s Liberation Army, Beijing 100142 (China); Wang, Dong, E-mail: dongwang1964@sina.com [Department of Radiology, Air Force General Hospital of People' s Liberation Army, Beijing 100142 (China); Fan, Hongxia, E-mail: fanhongxia1975@sina.com [Department of Radiology, Air Force General Hospital of People' s Liberation Army, Beijing 100142 (China)

    2017-02-15

    Objective: To determine whether diffusion-weighted imaging (DWI) can be used for quantitatively evaluating severity of acute radiation proctopathy after radiotherapy for cervical carcinoma. Materials and methods: One hundred and twenty-four patients with cervical carcinoma underwent MR examination including DWI before and after radiotherapy. Acute radiation proctopathy was classified into three groups (grade 0, grade I–II and grade III–IV) according to Toxicity Criteria of the Radiation Therapy Oncology Group (RTOG). The pretreatment ADC (ADC{sub pre}), ADC after treatment (ADC{sub post}) and ADC change (ΔADC) were compared among three groups. In addition, acute radiation proctopathy was classified into good-prognosis group and poor-prognosis group. ADC{sub pre}, ADC{sub post} and ΔADC were compared between two groups. For DWI parameter that had significant difference, discriminatory capability of the parameter was determined using receiver operating characteristics (ROC) analysis. Results: ADC{sub post} and ΔADC were higher in grade I–II group than in grade 0 group (p < 0.05), yielding a sensitivity of 79.3% and specificity of 69.4% for ADC{sub post}, and 85.1%, 72.3% for ΔADC for discrimination between two groups. ADC{sub post} and ΔADC were higher in grade III–IV group than in grade I–II group (p < 0.05), yielding a sensitivity of 80.3% and specificity of 72.5% for ADC{sub post}, and 84.1%, 74.5% for ΔADC for discrimination between two groups. ADC{sub post} and ΔADC were higher in poor-prognosis group than in good-prognosis group (p < 0.05), yielding a sensitivity of 79.5% and specificity of 73.4% for ADC{sub post}, and 87.2%, 78.3% for ΔADC for discrimination between two groups. Conclusion: Diffusion-weighted MRI can be used for quantitative stratification of severity of acute radiation proctopathy, which serves as an important basis for appropriate timely adjustment of radiotherapy for cervical carcinoma in order to maximally reduce the

  5. STABLE AND CRITICAL GESTICULATION RECOGNITION IN CHILDREN AND PREGNANT WOMEN BY WEIGHTED NAÏVE BAYES CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    N. Ravindran

    2014-12-01

    Full Text Available The healthcare monitoring on a remote care taking base involves many implicit observations between the subjects and the care takers. Any deficit in domain knowledge and carelessness leads to unpleasant situations thereafter. A wearable attire system can precisely interpret the implicit communication of the state of the subject and pass it to the care takers or to an automated aid device. Casual and conventional movements of subjects during play and living condition can be used for the above purpose. The proposed system suggests a novel way of identifying safe and unsafe conditions of playing for the children where a rapid warning assistance is required. The same system is used in the case of the normal and contraction time identification of pregnant women. Naive Bayes classifier was applied on features created by different algorithms and on the combinations of features constructed by algorithms like Fractal Dimension, Fast Fourier Transformation, Singular Value Decomposition. The result shows in general that the combinational features with point system results in better classification. Especially the FFT and SVD were more supportive in all three sets of experiments and better classified by Navie Bayes classifier than the other combinations and individual features. But the complexity is high when going through the point system. When a priori based point system is introduced with a reduced complexity to replace the conventional point system, the enhanced results show a well-distinguished realization of different body movement activities using a wearable attire array and the interpretation consistently results in significant and identifiable thresholds.

  6. Weight Management

    Science.gov (United States)

    ... Health Information Weight Management English English Español Weight Management Obesity is a chronic condition that affects more ... Liver (NASH) Heart Disease & Stroke Sleep Apnea Weight Management Topics About Food Portions Bariatric Surgery for Severe ...

  7. A new classification for 'Pistol Grip Deformity'. Correlation between the severity of the deformity and the grade of osteoarthritis of the hip

    International Nuclear Information System (INIS)

    Ipach, Ingmar; Mittag, F.; Sachsenmaier, S.; Kluba, T.; Heinrich, P.

    2011-01-01

    Purpose: Two types of femoroacetabular impingement (FAI) are described as reasons for the early development of osteoarthritis of the hip. Cam impingement develops from contact between an abnormal head-neck junction and the acetabular rim. Pincer impingement is characterized by local or general overcoverage of the femoral head by the acetabular rim. Both forms might cause early osteoarthritis of the hip. A decreased head/neck offset has been recognized on AP pelvic views and labeled as 'pistol grip deformity'. The aim of the study was to develop a classification for this deformity with regard to the stage of osteoarthritis of the hip. Materials and Methods: 76 pelvic and axial views were analyzed for alpha angle and head ratio. 22 of them had a normal shape in the head-neck region and no osteoarthritis signs, 27 had a 'pistol grip deformity' and osteoarthritis I and 27 had a 'pistol grip deformity' and osteoarthritis II -IV . The CART method was used to develop a classification. Results: There was a statistically significant correlation between alpha angle and head ratio. A statistically significant difference in alpha angle and head ratio was seen between the three groups. Using the CART method, we developed a three-step classification system for the 'pistol grip deformity' with very high accuracy. This deformity was aggravated by increasing age. Conclusion: Using this model it is possible to differentiate between normal shapes of the head-neck junction and different severities of the pistol grip deformity. (orig.)

  8. Does weight loss improve semen quality and reproductive hormones? Results from a cohort of severely obese men

    DEFF Research Database (Denmark)

    Håkonsen, Linn Berger; Thulstrup, Ane Marie; Aggerholm, Anette Skærbech

    2011-01-01

    A high body mass index (BMI) has been associated with reduced semen quality and male subfecundity, but no studies following obese men losing weight have yet been published. We examined semen quality and reproductive hormones among morbidly obese men and studied if weight loss improved...

  9. Psychological Factors Associated with Weight Loss in Obese and Severely Obese Women in a Behavioral Physical Activity Intervention

    Science.gov (United States)

    Annesi, James J.; Whitaker, Ann C.

    2010-01-01

    The behavioral processes of weight reduction are poorly understood, and responses to treatments based primarily on caloric restriction have been unfavorable. A theory-based path derived from proposed relations of physical activity, changes in psychological factors, and weight loss was separately tested with women with Class I and Class II obesity…

  10. Severe obesity and diabetes self-care attitudes, behaviours and burden : Implications for weight management from a matched case-controlled study. Results from Diabetes MILES-Australia

    NARCIS (Netherlands)

    Dixon, J.B.; Browne, J.L.; Mosely, K.G.; Jones, K.M.; Pouwer, F.; Speight, J.

    2014-01-01

    Aims To investigate whether diabetes self-care attitudes, behaviours and perceived burden, particularly related to weight management, diet and physical activity, differ between adults with Type 2 diabetes who are severely obese and matched non-severely obese control subjects. Methods The 1795

  11. Non-severe hypoglycaemia is associated with weight gain in patients with type 1 diabetes: Results from the Diabetes Control and Complication Trial.

    Science.gov (United States)

    Bumbu, Anisoara; Moutairou, Abdul; Matar, Odette; Fumeron, Frédéric; Velho, Gilberto; Riveline, Jean-Pierre; Gautier, Jean-François; Marre, Michel; Roussel, Ronan; Potier, Louis

    2018-05-01

    It is unclear whether the frequent non-severe episodes of hypoglycaemia observed during intensive glucose control in individuals with type 1 diabetes (T1D) are associated with subsequent weight gain. We analysed the association between non-severe hypoglycaemia and weight gain in 1441 Diabetes Control and Complication Trial (DCCT) participants. Non-severe hypoglycaemia was assessed by hypo-score (ie, number of blood glucose values gain. The annual weight gain by hypo-score tertiles was 0.8 ± 1.2 (T1), 1.3 ± 1.5 (T2) and 1.4 ± 1.3 kg/y (T3), P gain of 1.8 kg/y was 2.14 (95% CI, 1.56-2.93) for T2, and 2.53 (95%CI, 1.85-3.45) for T3 vs T1. These differences in weight gain and in risk of weight gain remained significant after adjustment for sex, age, duration of diabetes, HbA1c at baseline and treatment arms. In conclusion, our analysis shows a significant association between non-severe hypoglycaemia and weight gain in individuals with T1D from the DCCT. © 2017 John Wiley & Sons Ltd.

  12. A Mixed Application of Geographically Weighted Regression and Unsupervised Classification for Analyzing Latex Yield Variability in Yunnan, China

    Directory of Open Access Journals (Sweden)

    Oh Seok Kim

    2017-05-01

    Full Text Available This paper introduces a mixed method approach for analyzing the determinants of natural latex yields and the associated spatial variations and identifying the most suitable regions for producing latex. Geographically Weighted Regressions (GWR and Iterative Self-Organizing Data Analysis Technique (ISODATA are jointly applied to the georeferenced data points collected from the rubber plantations in Xishuangbanna (in Yunnan province, south China and other remotely-sensed spatial data. According to the GWR models, Age of rubber tree, Percent of clay in soil, Elevation, Solar radiation, Population, Distance from road, Distance from stream, Precipitation, and Mean temperature turn out statistically significant, indicating that these are the major determinants shaping latex yields at the prefecture level. However, the signs and magnitudes of the parameter estimates at the aggregate level are different from those at the lower spatial level, and the differences are due to diverse reasons. The ISODATA classifies the landscape into three categories: high, medium, and low potential yields. The map reveals that Mengla County has the majority of land with high potential yield, while Jinghong City and Menghai County show lower potential yield. In short, the mixed method can offer a means of providing greater insights in the prediction of agricultural production.

  13. Comprehensive eight-month intervention reduces weight and improves depression and anxiety levels in severe and morbid obesity

    Directory of Open Access Journals (Sweden)

    Alfonso Cofre-Lizama

    2017-04-01

    Conclusion: The comprehensive eight-month intervention had significant benefits for participants in weight loss and improved levels of anxiety and depression. For this reason, the intervention performed may be recommended for the treatment of this condition.

  14. Ghrelin and PYY levels in adolescents with severe obesity: effects of weight loss induced by long-term exercise training and modified food habits.

    Science.gov (United States)

    Gueugnon, Carine; Mougin, Fabienne; Nguyen, Nhu Uyen; Bouhaddi, Malika; Nicolet-Guénat, Marie; Dumoulin, Gilles

    2012-05-01

    This study investigated (a) changes in ghrelin and peptide YY (PYY) concentrations during a weight reduction programme and (b) baseline ghrelin and PYY levels as predictors of weight loss in 32 severely obese adolescents (BMI z score = 4.1). Subjects spent an academic year in an institution for childhood obesity. Fasting ghrelin and PYY, leptin, insulin levels and insulin resistance were measured at baseline (month 0) and during the programme (months 3, 6, 9). In addition, 15 normal-weight teenagers served as reference for the baseline assessments. At baseline, obese teenagers had lower ghrelin and PYY concentrations than normal-weight adolescents (P modification, there was a significant decrease in body weight among obese teenagers, associated with an increase in ghrelin (apparent from month 6; P modification. However, higher baseline PYY tended to correlate with greater anthropometrical changes (P < 0.1). In adolescents with severe obesity, a long-term combination of supervised aerobic exercises and a balanced diet led to weight reduction and increased ghrelin concentrations, without any change in PYY concentrations. Moreover, baseline PYY concentrations might be considered as predictors of weight loss.

  15. A new classification of spin in systematic reviews and meta-analyses was developed and ranked according to the severity

    DEFF Research Database (Denmark)

    Yavchitz, Amélie; Ravaud, Philippe; Altman, Douglas G

    2016-01-01

    Objectives We aimed to (1) identify and classify spin (i.e., a description that overstates efficacy and/or understates harm) in systematic reviews and (2) rank spin in abstracts of systematic reviews according to their severity (i.e., the likelihood of distorting readers' interpretation......, 28 from the main text and 21 from the abstract; 13 were specific to the systematic review design. Spin was classified into three categories: (1) misleading reporting, (2) misleading interpretation, and (3) inappropriate extrapolation. Spin ranked as the most severe by the 122 people who participated...... avoid spin in reports of systematic reviews. © 2016 Elsevier Inc....

  16. A comparison of symptom severity and bolus retention with Chicago classification esophageal pressure topography metrics in patients with achalasia

    NARCIS (Netherlands)

    Nicodem, Fredec; de Ruigh, Annemijn; Xiao, Yinglian; Rajeswaran, Shankar; Teitelbaum, Ezra N.; Hungness, Eric S.; Kahrilas, Peter J.; Pandolfino, John E.

    2013-01-01

    We compared findings from timed barium esophagrams (TBEs) and esophageal pressure topography studies among achalasia subtypes and in relation to symptom severity. We analyzed data from 50 patients with achalasia (31 men; age, 20-79 y) who underwent high-resolution manometry (HRM), had TBE after a

  17. Classification of the severe trauma patient with the Abbreviated Injury Scale: degree of correlation between versions 98 and 2005 (2008 update).

    Science.gov (United States)

    Abajas Bustillo, Rebeca; Leal Costa, César; Ortego Mate, María Del Carmen; Zonfrillo, Mark R; Seguí Gómez, María; Durá Ros, María Jesús

    2018-02-01

    To explore differences in severity classifications according to 2 versions of the Abbreviated Injury Scale (AIS): version 2005 (the 2008 update) and the earlier version 98. To determine whether possible differences might have an impact on identifying severe trauma patients. Descriptive study and cross-sectional analysis of a case series of patients admitted to two spanish hospitals with out-of-hospital injuries between February 2012 and February 2013. For each patient we calculated the Injury Severity Score (ISS), the New Injury Severity Score (NISS), and the AIS scores according to versions 98 and 2005. The sample included 699 cases. The mean Severity (SD) age of patients was 52.7 (29.2) years, and 388 (55.5%) were males. Version 98 of the AIS correlated more strongly with both the ISS (2.6%) and the NISS (2.9%). The 2008 update of the AIS (version 2005) classified fewer trauma patients than version 98 at the severity levels indicated by the ISS and NISS.

  18. Integration of 3D imaging data in the assessment of aortic stenosis: impact on classification of disease severity.

    Science.gov (United States)

    O'Brien, Bridget; Schoenhagen, Paul; Kapadia, Samir R; Svensson, Lars G; Rodriguez, Leonardo; Griffin, Brian P; Tuzcu, E Murat; Desai, Milind Y

    2011-09-01

    In patients with aortic stenosis (AS), precise assessment of severity is critical for treatment decisions. Estimation of aortic valve area (AVA) with transthoracic echocardiographic (TTE)-continuity equation (CE) assumes a circular left ventricular outflow tract (LVOT). We evaluated incremental utility of 3D multidetector computed tomography (MDCT) over TTE assessment of AS severity. We included 51 patients (age, 81±8 years; 61% men; mean gradient, 42 ± 12 mm Hg) with calcific AS who underwent evaluation for treatment options. TTE parameters included systolic LVOT diameter (D) and continuous and pulsed wave (CW and PW) velocity-time integrals (VTI) through the LVOT and mean transaortic gradient. MDCT parameters included systolic LVOT area, ratio of maximal to minimal LVOT diameter (eccentricity index), and aortic planimetry (AVA(p)). TTE-CE AVA [(D(2)×0.786×VTIpw)/VTIcw] and dimensionless index (DI) [VTIpw/VTIcw] were calculated. Corrected AVA was calculated by substituting MDCT LVOT area into CE. The majority (96%) of patients had eccentric LVOT. LVOT area, measured on MDCT, was higher than on TTE (3.84 ± 0.8 cm(2) versus 3.03 ± 0.5 cm(2), P<0.01). TTE-AVA was smaller than AVA(p) and corrected AVA (0.67 ± 0.1cm(2), 0.82 ± 0.3 cm(2), and 0.86 ± 0.3 cm(2), P<0.01). Using TTE measurements alone, 73% of patients had congruence for severe AS (DI ≤0.25 and CE AVA <0.8 cm(2)), which increased to 92% using corrected CE. In patients with suspected severe AS, incorporation of MDCT-LVOT area into CE improves congruence for AS severity.

  19. Exploration and classification of chromatographic fingerprints as additional tool for identification and quality control of several Artemisia species.

    Science.gov (United States)

    Alaerts, Goedele; Pieters, Sigrid; Logie, Hans; Van Erps, Jürgen; Merino-Arévalo, Maria; Dejaegher, Bieke; Smeyers-Verbeke, Johanna; Vander Heyden, Yvan

    2014-07-01

    -analysis technique. Samples of different quality could be indicated on the score plots. No multi-component analysis was required to reach the goal. Furthermore, differences related to the origin of some of the not-certified samples were shown. The importance of the specific herbal part used for its identification was also presented. In addition, no differences were observed among fingerprints of lyophilised or conditioned-air dried samples. Finally, a classification technique, Soft Independent Modelling by Class Analogy (SIMCA), was successfully evaluated as identification technique for unknown samples. Six additional Artemisia species (29 herbal samples) were identified as not belonging to any of the four modelled classes. The developed chromatographic fingerprints and the evaluation of the entire profiles provide an added value to the distinction, identification and quality control of the simultaneously investigated Artemisia species. Copyright © 2014 Elsevier B.V. All rights reserved.

  20. Does weight loss improve semen quality and reproductive hormones? results from a cohort of severely obese men

    Directory of Open Access Journals (Sweden)

    Ernst Emil

    2011-08-01

    Full Text Available Abstract Background A high body mass index (BMI has been associated with reduced semen quality and male subfecundity, but no studies following obese men losing weight have yet been published. We examined semen quality and reproductive hormones among morbidly obese men and studied if weight loss improved the reproductive indicators. Methods In this pilot cohort study, 43 men with BMI > 33 kg/m2 were followed through a 14 week residential weight loss program. The participants provided semen samples and had blood samples drawn, filled in questionnaires, and had clinical examinations before and after the intervention. Conventional semen characteristics as well as sperm DNA integrity, analysed by the sperm chromatin structure assay (SCSA were obtained. Serum levels of testosterone, estradiol, sex hormone-binding globulin (SHBG, luteinizing hormone (LH, follicle-stimulating hormone (FSH, anti-Müllerian hormone (AMH and inhibin B (Inh-B were measured. Results Participants were from 20 to 59 years of age (median = 32 with BMI ranging from 33 to 61 kg/m2. At baseline, after adjustment for potential confounders, BMI was inversely associated with sperm concentration (p = 0.02, total sperm count (p = 0.02, sperm morphology (p = 0.04, and motile sperm (p = 0.005 as well as testosterone (p = 0.04 and Inh-B (p = 0.04 and positively associated to estradiol (p Conclusion This study found obesity to be associated with poor semen quality and altered reproductive hormonal profile. Weight loss may potentially lead to improvement in semen quality. Whether the improvement is a result of the reduction in body weight per se or improved lifestyles remains unknown.

  1. Psychometric properties of the Spanish version of the Body Weight, Image and Self-Esteem Evaluation Questionnaire in patients with severe mental disorders.

    Science.gov (United States)

    Al-Halabi, Susana; Garcia-Portilla, Maria Paz; Saiz, Pilar Alejandra; Fonseca, Eduardo; Bobes-Bascaran, Maria Teresa; Galván, Gonzalo; Iglesias, Celso; Arrojo, Manuel; Benabarre, Antoni; Goikolea, José Manuel; Sanchez, Emilio; Sarramea, Fernando; Bobes, Julio

    2012-11-01

    Clinicians need brief and valid instruments to monitor the psychosocial impact of weight gain in persons with psychiatric disorders. We examined the psychometric properties of the Spanish version of the Body Weight, Image and Self-Esteem Evaluation (B-WISE) questionnaire in patients with severe mental disorders. The data come from a naturalistic, cross-sectional, validation study conducted at 6 centres in Spain. A total of 211 outpatients with severe mental disorders, 118 with schizophrenia and 93 with bipolar disorder, were evaluated using the B-WISE, the Visual Analogue Scale for Weight and Body Image, and the Clinical Global Impression-Severity (CGI-S). The body mass index was also obtained. The principal component analysis confirms 3 components explaining 50.93% of the variance. The Cronbach α values for B-WISE scales ranged between .55 and .73. Significant Pearson correlations were found between B-WISE total score and CGI-S (r = -0.25; P Body Image (r = 0.47; P Body mass index categorization significantly influenced total B-WISE scores (F = 3.586, P < .050). The B-WISE score corresponding to the 5th and 10th percentiles was 22. We were able to demonstrate that the Spanish version of the B-WISE is a valid instrument for assessing psychosocial impact of weight gain in patients with severe mental disorders in daily clinical practice. Copyright © 2012 Elsevier Inc. All rights reserved.

  2. Classification of activity engagement in individuals with severe physical disabilities using signals of the peripheral nervous system.

    Directory of Open Access Journals (Sweden)

    Azadeh Kushki

    Full Text Available Communication barriers often result in exclusion of children and youth with disabilities from activities and social settings that are essential to their psychosocial development. In particular, difficulties in describing their experiences of activities and social settings hinder our understanding of the factors that promote inclusion and participation of this group of individuals. To address this specific communication challenge, we examined the feasibility of developing a language-free measure of experience in youth with severe physical disabilities. To do this, we used the activity of the peripheral nervous system to detect patterns of psychological arousal associated with activities requiring different patterns of cognitive/affective and interpersonal involvement (activity engagement. We demonstrated that these signals can differentiate among patterns of arousal associated with these activities with high accuracy (two levels: 81%, three levels: 74%. These results demonstrate the potential for development of a real-time, motor- and language-free measure for describing the experiences of children and youth with disabilities.

  3. Factors associated with long-term weight-loss maintenance following bariatric surgery in adolescents with severe obesity.

    Science.gov (United States)

    Ryder, J R; Gross, A C; Fox, C K; Kaizer, A M; Rudser, K D; Jenkins, T M; Ratcliff, M B; Kelly, A S; Kirk, S; Siegel, R M; Inge, T H

    2018-01-01

    Bariatric surgery produces robust weight loss, however, factors associated with long-term weight-loss maintenance among adolescents undergoing Roux-en-Y gastric bypass surgery are unknown. Fifty adolescents (mean±s.d. age and body mass index (BMI)=17.1±1.7 years and 59±11 kg m -2 ) underwent Roux-en-Y gastric bypass surgery, had follow-up visits at 1 year and at a visit between 5 and 12 years following surgery (Follow-up of Adolescent Bariatric Surgery at 5 Plus years (FABS-5+) visit; mean±s.d. 8.1±1.6 years). A non-surgical comparison group (n=30; mean±s.d. age and BMI=15.3±1.7 years and BMI=52±8 kg m -2 ) was recruited to compare weight trajectories over time. Questionnaires (health-related and eating behaviors, health responsibility, impact of weight on quality of life (QOL), international physical activity questionnaire and dietary habits via surgery guidelines) were administered at the FABS-5+ visit. Post hoc, participants were split into two groups: long-term weight-loss maintainers (n=23; baseline BMI=58.2 kg m -2 ; 1-year BMI=35.8 kg m -2 ; FABS-5+ BMI=34.9 kg m -2 ) and re-gainers (n=27; baseline BMI=59.8 kg m -2 ; 1-year BMI=36.8 kg m -2 ; FABS-5+ BMI=48.0 kg m -2 ) to compare factors which might contribute to differences. Data were analyzed using generalized estimating equations adjusted for age, sex, baseline BMI, baseline diabetes status and length of follow-up. The BMI of the surgical group declined from baseline to 1 year (-38.5±6.9%), which, despite some regain, was largely maintained until FABS-5+ (-29.6±13.9% change). The BMI of the comparison group increased from baseline to the FABS-5+ visit (+10.3±20.6%). When the surgical group was split into maintainers and re-gainers, no differences in weight-related and eating behaviors, health responsibility, physical activity/inactivity, or dietary habits were observed between groups. However, at FABS-5+, maintainers had greater overall QOL scores than re

  4. Determinants of Integrated Management of Childhood Illness (IMCI) non-severe pneumonia classification and care in Malawi health facilities: Analysis of a national facility census.

    Science.gov (United States)

    Johansson, Emily White; Nsona, Humphreys; Carvajal-Aguirre, Liliana; Amouzou, Agbessi; Hildenwall, Helena

    2017-12-01

    Research shows inadequate Integrated Management of Childhood Illness (IMCI)-pneumonia care in various low-income settings but evidence is largely from small-scale studies with limited evidence of patient-, provider- and facility-levels determinants of IMCI non-severe pneumonia classification and its management. The Malawi Service Provision Assessment 2013-2014 included 3149 outpatients aged 2-59 months with completed observations, interviews and re-examinations. Mixed-effects logistic regression models quantified the influence of patient-, provider and facility-level determinants on having IMCI non-severe pneumonia and its management in observed consultations. Among 3149 eligible outpatients, 590 (18.7%) had IMCI non-severe pneumonia classification in re-examination. 228 (38.7%) classified cases received first-line antibiotics and 159 (26.9%) received no antibiotics. 18.6% with cough or difficult breathing had 60-second respiratory rates counted during consultations, and conducting this assessment was significantly associated with IMCI training ever received (odds ratio (OR) = 2.37, 95% confidence interval (CI): 1.29-4.31) and negative rapid diagnostic test results (OR = 3.21, 95% CI: 1.45-7.13). Older children had lower odds of assessments than infants (OR = 48-59 months: 0.35, 95% CI: 0.16-0.75). Children presenting with any of the following complaints also had reduced odds of assessment: fever, diarrhea, skin problem or any danger sign. First-line antibiotic treatment for classified cases was significantly associated with high temperatures (OR = 3.26, 95% CI: 1.24-8.55) while older children had reduced odds of first-line treatment compared to infants (OR = 48-59 months: 0.29, 95% CI: 0.10-0.83). RDT-confirmed malaria was a significant predictor of no antibiotic receipt for IMCI non-severe pneumonia (OR = 10.65, 95% CI: 2.39-47.36). IMCI non-severe pneumonia care was sub-optimal in Malawi health facilities in 2013-2014 with inadequate

  5. Severity Classification of a Seismic Event based on the Magnitude-Distance Ratio Using Only One Seismological Station

    Directory of Open Access Journals (Sweden)

    Luis Hernán Ochoa Gutiérrez

    2014-07-01

    Full Text Available Seismic event characterization is often accomplished using algorithms based only on information received at seismological stations located closest to the particular event, while ignoring historical data received at those stations. These historical data are stored and unseen at this stage. This characterization process can delay the emergency response, costing valuable time in the mitigation of the adverse effects on the affected population. Seismological stations have recorded data during many events that have been characterized by classical methods, and these data can be used as previous "knowledge" to train such stations to recognize patterns. This knowledge can be used to make faster characterizations using only one three-component broadband station by applying bio-inspired algorithms or recently developed stochastic methods, such as kernel methods. We trained a Support Vector Machine (SVM algorithm with seismograph data recorded by INGEOMINAS's National Seismological Network at a three-component station located near Bogota, Colombia. As input model descriptors, we used the following: (1 the integral of the Fourier transform/power spectrum for each component, divided into 7 windows of 2 seconds and beginning at the P onset time, and (2 the ratio between the calculated logarithm of magnitude (Mb and epicentral distance. We used 986 events with magnitudes greater than 3 recorded from late 2003 to 2008. The algorithm classifies events with magnitude-distance ratios (a measure of the severity of possible damage caused by an earthquake greater than a background value. This value can be used to estimate the magnitude based on a known epicentral distance, which is calculated from the difference between P and S onset times. This rapid (< 20 seconds magnitude estimate can be used for rapid response strategies. The results obtained in this work confirm that many hypocentral parameters and a rapid location of a seismic event can be obtained using a few

  6. Detection and classification of focal liver lesions in patients with colorectal cancer: Retrospective comparison of diffusion-weighted MR imaging and multi-slice CT

    International Nuclear Information System (INIS)

    Eiber, Matthias; Fingerle, Alexander A.; Brügel, Melanie; Gaa, Jochen; Rummeny, Ernst J.; Holzapfel, Konstantin

    2012-01-01

    Objectives: To compare the diagnostic performance of diffusion-weighted MR imaging (DWI) with multi-slice CT (MS-CT) in the detection and classification of focal liver lesions in patients with colorectal cancer. Methods: In a retrospective study 68 patients who underwent DWI at 1.5 T (b-values of 50, 300 and 600 s/mm 2 ) and contrast-enhanced MS-CT were analysed by two radiologists blinded to the clinical results. Imaging results were correlated with intraoperative surgical and ultrasound findings (n = 24), imaging follow-up or PET (n = 44). Sensitivity of DWI and MS-CT in detection of focal liver lesions was compared on a per-lesion and a per-segment basis. Receiver operator-characteristic (ROC) curves to determine the diagnostic performance and the sensitivities of correctly identifying liver metastases on a segmental base were calculated. Results: For lesion detection, DWI was significantly superior to MS-CT both on a per-lesion (difference in sensitivities for reader 1 and 2 22.65% and 19.06%, p < 0.0001) and a per-segment basis (16.86% and 11.76%, p < 0.0001). Especially lesions smaller than 10 mm were better detected with DWI compared to MS-CT (difference 41.10% and 29.45%, p < 0.0001). ROC-analysis showed superiority for lesions classification (p < 0.0001) of DWI (AUC: 0.949 and 0.951) as compared to MS-CT (AUC: 0.879 and 0.892, p < 0.0001 and p = 0.005). DWI was able to filter out metastatic segments with a higher sensitivity (88.2 and 86.5%) compared to MS-CT (68.0 and 67.4%, p < 0.0001 and p = 0.005, respectively). Conclusion: Compared to MS-CT DWI is both more sensitive in the detection of liver lesions and more accurate in determining the extent of metastatic disease in patients with colorectal cancer and therefore might help to optimize therapeutic management in those patients.

  7. [Effect of Low Molecular Weight Heparin Calcium Combined Compound Danshen Injection on Perinatal Outcomes of Nephrotic Syndrome Patients with Early Onset Severe Pre-eclampsia].

    Science.gov (United States)

    Tong, Chong-xin; Xing, Xiao-fen; Qiao, Shu-hua; Liu, Lin; Shan, Ling

    2015-08-01

    To observe the effect of low molecular weight heparin calcium (LMWHC) combined Compound Danshen Injection (DI) on nephrotic syndrome patients with early onset severe preeclampsia. Totally 80 nephrotic syndrome patients with early onset severe pre-eclampsia were randomly assigned to four groups voluntarily, i.e., Group A (22 cases, treated by magnesium sulfate), B (19 cases, treated by magnesium sulfate plus LMWHC), C (21 cases, magnesium sulfate plus DI), D (18 cases, magnesium sulfate plus LMWHC and DI). Umbilical arterial S/D ratios, amniotic fluid index (AFI), prolonged gestational age, placenta weight, neonatal weight, and Apgar score were compared among the four groups. Compared with before treatment in the same group, umbilical arterial S/D ratios decreased in the four groups (P <0. 05). AFI decreased in Group A, while it increased in Group B, C, and D (P<0. 05). Compared with Group A at the same time point, umbilical arterial S/D ratios decreased, and AFI increased in Group B, C, and D (P <0. 01 , P <0. 05). Prolonged gestational age and neonatal weight were increased in Group B, C, and D (P <0. 01, P <0. 05). Placenta weight were increased in Group B and D (P <0. 05). Apgar scores at 1 and 5 min were improved in Group D (P <0. 05). Compared with Group B and C at the same time point, umbilical arterial S/D ratios decreased, and AFI increased in Group D (P<0. 05). Compared with Group B, prolonged gestational age and placenta weight were decreased in Group C, but prolonged gestational age and placenta weight were increased in Group D (P <0.05). Compared with Group C, prolonged gestational age, placenta weight, and neonatal weight were increased in Group D (P <0. 05). Treatment of nephrotic syndrome patients with early onset severe pre-eclampsia by LMWHC combined DI could prolong gestational ages, obviously improve prenatal outcomes, with better effect obtained than using any of them alone.

  8. Association of previous severe low birth weight with adverse perinatal outcomes in a subsequent pregnancy among HIV-prevalent urban African women.

    Science.gov (United States)

    Smid, Marcela C; Ahmed, Yusuf; Stoner, Marie C D; Vwalika, Bellington; Stringer, Elizabeth M; Stringer, Jeffrey S A

    2017-02-01

    To evaluate the association between severity of prior low birth weight (LBW) delivery and adverse perinatal outcomes in the subsequent delivery among an HIV-prevalent urban African population. A retrospective cohort study was conducted among 41 109 women who had undergone two deliveries in Lusaka, Zambia, between February 1, 2006, and May 31, 2013. The relationship between prior LBW delivery (<2500 g) and a composite measure of adverse perinatal outcome in the second pregnancy was assessed using multivariate logistic regression. Women with prior LBW delivery (n=4259) had an increased risk of LBW in the second delivery versus those without prior LBW delivery (n=37 642). Such risk correlated with the severity of first delivery LBW. The adjusted odds ratio (AOR) was 2.89 (95% confidence interval [CI] 2.05-4.09) for a birth weight of 1000-1499 g, 3.05 (95% CI 2.42-3.86) for a birth weight of 1500-1999 g, and 2.02 (95% CI 1.81-2.27) for a birth weight of 2000-2499 g. Previous LBW delivery also increased the risk of adverse perinatal outcome, with an AOR of 1.4 (95% CI 1.2-1.7). Severe prior LBW delivery conferred substantial risk for adverse perinatal outcomes in a subsequent pregnancy. © 2016 International Federation of Gynecology and Obstetrics.

  9. Quantitative evaluation of hyperintensity on T1-weighted MRI in liver cirrhosis : correlation with child-pugh classification and hepatic encephalopathy

    International Nuclear Information System (INIS)

    Eun, Hyo Won; Choi, Hye Young; Lee, Sun Wha; Yi, Sun Young

    1999-01-01

    To investigate the differences in signal changes in the globus pallidus and white matter, as seen on T1-weighted MR brain images, and to determine whether these differences can be used as an indicator of subclinical hepatic encephalopathy. A total of 25 cases of liver cirrhosis were evaluated and as a control group, 20 subjects were also studied. Using a 1.5T MRI scannet, brain MR images were obtained, and the differences in signal intensity in both the globus pallidus and thalamus and in both white and gray matter were then quantified using the contrast to noise ratio(CNR). On the basis of the Child-Pugh classification, 25patients with liver cirrhosis were divided into three groups, with eight in group A, eight in B, and nine in C. Using clinical criteria, hepatic encephalopathy was diagnosed in seven of the 25 patients. There after, CNRs(CNR1 and CNR2) were conpared between the control and cirrhotic groups and between cirrhotic groups with or without hepatic encephalopathy. In the control group, mean values were 3.2±5.9 for CNR1 and 8.4±8.0 for CNR2. In the cirrhotic group, these values were 10.6±9.0 for CNR1 and 9.8±6.4 for CNR2. A statistically significant difference was noted between normal and cirrhotic groups only for CNR1(p<0.05). CNR values in patients with liver cirrhosis were 8.5±11.5 for CNR1 and 11.7±8.7 for CNR2 in the Child A group, 10.4±5.1 for CNR1 and 9.3±3.2 for CNR2 in the B group, and 12.8±9.7 for CNR1 and 8.7±6.5 for CNR2 in the C group. There was no significant difference in mean CNRI values between patients with or without hepatic encephalopathy. Differences in signal intensities in the globus pallidus and white matter, as seen on T1-weighted MR brain images, cannot be used as an indicator of hepatic encephalopathy in patients with liver cirrhosis

  10. Quantitative evaluation of hyperintensity on T1-weighted MRI in liver cirrhosis : correlation with child-pugh classification and hepatic encephalopathy

    Energy Technology Data Exchange (ETDEWEB)

    Eun, Hyo Won; Choi, Hye Young; Lee, Sun Wha; Yi, Sun Young [Ewha Womans Univ. College of Medicine, Seoul (Korea, Republic of)

    1999-11-01

    To investigate the differences in signal changes in the globus pallidus and white matter, as seen on T1-weighted MR brain images, and to determine whether these differences can be used as an indicator of subclinical hepatic encephalopathy. A total of 25 cases of liver cirrhosis were evaluated and as a control group, 20 subjects were also studied. Using a 1.5T MRI scannet, brain MR images were obtained, and the differences in signal intensity in both the globus pallidus and thalamus and in both white and gray matter were then quantified using the contrast to noise ratio(CNR). On the basis of the Child-Pugh classification, 25patients with liver cirrhosis were divided into three groups, with eight in group A, eight in B, and nine in C. Using clinical criteria, hepatic encephalopathy was diagnosed in seven of the 25 patients. There after, CNRs(CNR1 and CNR2) were conpared between the control and cirrhotic groups and between cirrhotic groups with or without hepatic encephalopathy. In the control group, mean values were 3.2{+-}5.9 for CNR1 and 8.4{+-}8.0 for CNR2. In the cirrhotic group, these values were 10.6{+-}9.0 for CNR1 and 9.8{+-}6.4 for CNR2. A statistically significant difference was noted between normal and cirrhotic groups only for CNR1(p<0.05). CNR values in patients with liver cirrhosis were 8.5{+-}11.5 for CNR1 and 11.7{+-}8.7 for CNR2 in the Child A group, 10.4{+-}5.1 for CNR1 and 9.3{+-}3.2 for CNR2 in the B group, and 12.8{+-}9.7 for CNR1 and 8.7{+-}6.5 for CNR2 in the C group. There was no significant difference in mean CNRI values between patients with or without hepatic encephalopathy. Differences in signal intensities in the globus pallidus and white matter, as seen on T1-weighted MR brain images, cannot be used as an indicator of hepatic encephalopathy in patients with liver cirrhosis.

  11. Psychological aspects of eating behavior as predictors of 10-y weight changes after surgical and conventional treatment of severe obesity: results from the Swedish Obese Subjects intervention study.

    Science.gov (United States)

    Konttinen, Hanna; Peltonen, Markku; Sjöström, Lars; Carlsson, Lena; Karlsson, Jan

    2015-01-01

    There is a need for a better understanding of the factors that influence long-term weight outcomes after bariatric surgery. We examined whether pretreatment and posttreatment levels of cognitive restraint, disinhibition, and hunger and 1-y changes in these eating behaviors predict short- and long-term weight changes after surgical and conventional treatments of severe obesity. Participants were from an ongoing, matched (nonrandomized) prospective intervention trial of the Swedish Obese Subjects (SOS) study. The current analyses included 2010 obese subjects who underwent bariatric surgery and 1916 contemporaneously matched obese controls who received conventional treatment. Physical measurements (e.g., weight and height) and questionnaires (e.g., Three-Factor Eating Questionnaire) were completed before the intervention and 0.5, 1, 2, 3, 4, 6, 8, and 10 y after the start of the treatment. Structural equation modeling was used as the main analytic strategy. The surgery group lost more weight and reported greater decreases in disinhibition and hunger at 1- and 10-y follow-ups (all P women) and experienced larger 1-y decreases in these behaviors (β = 0.31-0.48, P women) lost more weight 2, 6, and 10 y after surgery. In control patients, larger 1-y increases in cognitive restraint predicted a greater 2-y weight loss in both sexes. A higher tendency to eat in response to various internal and external cues shortly after surgery predicted less-successful short- and long-term weight outcomes, making postoperative susceptibility for uncontrolled eating an important indicator of targeted interventions. © 2015 American Society for Nutrition.

  12. The long-term outcome after severe trauma of children in Flanders (Belgium): A population-based cohort study using the International Classification of Functioning-related outcome score

    NARCIS (Netherlands)

    P. van de Voorde (Patrick); M. Sabbe (Marc); R. Tsonaka (Roula); D. Rizopoulos (Dimitris); P. Calle (Paul); A. de De Jaeger (Annick); E.M.E.H. Lesaffre (Emmanuel); D. Matthys (Dirk)

    2011-01-01

    textabstractImportant long-term health problems have been described after severe paediatric trauma. The International Classification of Functioning (ICF) was developed as a universal framework to describe that health. We evaluated outcome in children after 'severe' trauma (defined as: hospitalised

  13. An herbal medicine, Go-sha-jinki-gan (GJG, increases muscle weight in severe muscle dystrophy model mice

    Directory of Open Access Journals (Sweden)

    Yusei Takemoto

    2017-12-01

    Full Text Available Go-sha-jinki-gan (GJG, a traditional Japanese herbal medicine has a clinical implication to alleviate age-related symptoms, especially in some motor disorders. However, the scientific evidence is limited, and there is a possibility to expand the medical application range of GJG. Using senescence-accelerated mice, our group showed that GJG exerted an effect to prevent sarcopenia, the aged-related loss of skeletal muscle. Because muscular dystrophy is characterized by a progressive loss of skeletal muscle, we examined the effects of GJG on a mouse model of muscular dystrophy. Using a newly established mouse model for Duchenne muscular dystrophy (DMD, DBA/2-mdx, we showed that GJG significantly increased the body and skeletal muscle weights in comparison to the control DBA/2-mdx mice, regardless of gender. The increased skeletal muscle mass resulted from an increment in the myofiber size, but not from the myofiber number. Both the skeletal muscle regenerative ability and the accumulation of fibrosis (the dystrophic pathology in GJG-fed DBA/2-mdx mice were comparable to those in control DBA/2-mdx mice, suggesting that the cellular target of GJG is myofibers, with no contribution from the muscle satellite cells neither in an direct nor in an indirect manner. Taken together, GJG increased the skeletal muscle mass in a mouse model of muscular dystrophy, in addition to our previously tested sarcopenia mouse model.

  14. Neurobehavioral conditions and effects of gender, weight and severity in preterm infants according to the Neonatal Behavioral Assessment Scale

    Directory of Open Access Journals (Sweden)

    Alicia Álvarez-García

    2015-10-01

    Full Text Available The increasing number of preterm babies in recent years has raised interest in studying the consequences of prematurity as a risk factor. In the present paper, 30 preterm babies (at 40 weeks of gestational age were assessed using the Neonatal Behavioral Assessment Scale and the results were compared with those of a control group of 28 full term babies. Moreover, the influence of weight, sex and gestational age was analyzed considering the Brazelton results in the preterm group. The preterm group showed significantly lower scores than the control group for 9 of the 28 behavioral items in the Scale and for 2 of the 5 clusters. However, preterm babies performed better in habituation to disturbing stimuli (light and noise during sleep. In relation to the influence of sex, premature girls performed better in the Social-Interactive cluster. The preterm group has lower neurobehavioral conditions than the full term group, probably due to the abrupt interruption of their intrauterine maturation. In contrast, they showed a better ability of habituation, maybe as a consequence of a learning effect due to earlier additional extrauterine exposition.

  15. Measurements of double differential cross sections (DDX) for several medium-weight and heavy nuclei at 15 MeV

    International Nuclear Information System (INIS)

    Iwasaki, Shin

    1984-01-01

    Measurements of double differential cross sections (DDX) for several intermediate and heavy nuclei have been performed at 15 MeV in the Dynamitron Laboratory at Tohoku University. Comparison of the experimental data with the evaluated nuclear data file, ENDF/B-IV revealed that the data file could not reproduce the experimental ones, particularly in the angular distributions. Nuclear model calculation showed that the preequilibrium process was important in the present incident energy region. Measurements have been performed for titanium, niobium, molybdenum, lead, and thorium (in progress), including the light elements, carbon and aluminum. (author)

  16. Polymorphism of the FTO Gene Influences Body Weight in Children with Type 1 Diabetes without Severe Obesity

    OpenAIRE

    Łuczyński, Włodzimierz; Fendler, Wojciech; Ramatowska, Anna; Szypowska, Agnieszka; Szadkowska, Agnieszka; Młynarski, Wojciech; Chumiecki, Miron; Jarosz-Chobot, Przemysława; Chrzanowska, Joanna; Noczyńska, Anna; Brandt, Agnieszka; Myśliwiec, Małgorzata; Głowińska-Olszewska, Barbara; Bernatowicz, Paweł; Kowalczuk, Oksana

    2014-01-01

    The objective was to compare the impact of clinical and genetic factors on body mass index (BMI) in children with type 1 diabetes (T1DM) without severe obesity. A total of 1,119 children with T1DM (aged 4–18 years) were qualified to take part in the study. All children were genotyped for variants of FTO, MC4R, INSIG2, FASN, NPC1, PTER, SIRT1, MAF, IRT1, and CD36. Results. Variants of FTO showed significant association with BMI-SDS in the T1DM group. The main factors influencing BMI-SDS in chi...

  17. Risk Factors for the Failure of Spinal Burst Fractures Treated Conservatively According to the Thoracolumbar Injury Classification and Severity Score (TLICS: A Retrospective Cohort Trial.

    Directory of Open Access Journals (Sweden)

    Jieliang Shen

    Full Text Available The management of thoracolumbar (TL burst fractures is still controversial. The thoracolumbar injury classification and severity score (TLICS algorithm is now widely used to guide clinical decision making, however, in clinical practice, we come to realize that TLICS also has its limitations for treating patients with total scores less than 4, for which conservative treatment may not be optimal in all cases.The aim of this study is to identify several risk factors for the failure of conservative treatment of TL burst fractures according to TLICS algorithm.From June 2008 to December 2013, a cohort of 129 patients with T10-l2 TL burst fractures with a TLISC score ≤3 treated non-operatively were identified and included into this retrospective study. Age, sex, pain intensity, interpedicular distance (IPD, canal compromise, loss of vertebral body height and kyphotic angle (KA were selected as potential risk factors and compared between the non-operative success group and the non-operative failure group.One hundred and four patients successfully completed non-operative treatment, the other 25 patients were converted to surgical treatment because of persistent local back pain or progressive neurological deficits during follow-up. Our results showed that age, visual analogue scale (VAS score and IPD, KA were significantly different between the two groups. Furthermore, regression analysis indicated that VAS score and IPD could be considered as significant predictors for the failure of conservative treatment.The recommendation of non-operative treatment for TLICS score ≤3 has limitations in some patients, and VAS score and IPD could be considered as risk factors for the failure of conservative treatment. Thus, conservative treatment should be decided with caution in patients with greater VAS scores or IPD. If non-operative management is decided, a close follow-up is necessary.

  18. Changes in body weight, body composition and cardiovascular risk factors after long-term nutritional intervention in patients with severe mental illness: an observational study

    Directory of Open Access Journals (Sweden)

    Vlahavas George

    2011-02-01

    Full Text Available Abstract Background Compared with the general population, individuals with severe mental illness (SMI have increased prevalence rates of obesity and greater risk for cardiovascular disease. This study aimed to investigate the effects of a long term nutritional intervention on body weight, body fat and cardiovascular risk factors in a large number of patients with SMI. Methods Nine hundred and eighty-nine patients with a mean ± S.D age of 40 ± 11.7 yrs participated in a 9 mo nutritional intervention which provided personalised dietetic treatment and lifestyle counselling every two weeks. Patients had an average body mass index (BMI of 34.3 ± 7.1 kg.m-2 and body weight (BW of 94.9 ± 21.7 kg. Fasted blood samples were collected for the measurement of glucose, total cholesterol, triglycerides and HDL- cholesterol. All measurements were undertaken at baseline and at 3 mo, 6 mo and 9 mo of the nutritional intervention. Results Four hundred and twenty-three patients of 989 total patients' cases (42.8% dropped out within the first 3 months. Two hundred eighty-five completed 6 months of the program and 145 completed the entire 9 month nutritional intervention. There were progressive statistically significant reductions in mean weight, fat mass, waist and BMI throughout the duration of monitoring (p -2 (p Conclusion The nutritional intervention produced significant reductions in body weight, body fat and improved the cardiometabolic profile in patients with SMI. These findings indicate the importance of weight-reducing nutritional intervention in decreasing the cardiovascular risk in patients with SMI.

  19. Inflammatory status is different in relationship to insulin resistance in severely obese people and changes after bariatric surgery or diet-induced weight loss.

    Science.gov (United States)

    Ballesteros-Pomar, M D; Calleja, S; Díez-Rodríguez, R; Calleja-Fernández, A; Vidal-Casariego, A; Nuñez-Alonso, A; Cano-Rodríguez, I; Olcoz-Goñi, J L

    2014-11-01

    To assess if insulin resistance is related to a different inflammatory status (especially lymphocyte subpopulations) in severely obese people and to evaluate changes after weight loss either following a very-low calorie diet (VLCD) or bariatric surgery. Severely obese patients were consecutively recruited in our Obesity Unit. Blood lymphocyte subpopulations and inflammatory parameters were measured baseline, after a VLCD during 6 weeks and one year after biliopancreatic diversion. Insulin resistance was evaluated by Homeostasis Model Assessment (HOMA) index. After excluding diabetic patients, 58 patients were studied. HOMA index classified 63.8% of them as insulin resistant (IR). Serum baseline levels of inflammatory cytokines were not significantly different between IR and insulinsensitive (IS) patients but, regarding lymphocyte subpopulations, Natural Killer (NK) cells were higher in IR patients [(305.0 (136.7) vs. 235.0 (80.7) cells/µL, p=0.047]. NK cells showed a significant positive correlation with HOMA index (r=0.484, p=0.000) and with the carbohydrate content of the diet (r=0.420, p=0.001). After VLCD, NK cells significantly decreased, but only in IR patients and in those losing more than 10% of their initial weight. After biliopancreatic diversion, total and CD8 T Lymphocytes, B lymphocytes and NK cells also decreased but only in IR individuals. NK cells are significantly increased in IR severely obese people in respect to IS, suggesting a slightly different immune status in these patients with a probable dietary relationship. Weight loss could reverse this increase either after VLCD or after bariatric surgery. © J. A. Barth Verlag in Georg Thieme Verlag KG Stuttgart · New York.

  20. Neurodevelopmental outcomes of infants with very low birth weights are associated with the severity of their extra-uterine growth retardation

    Directory of Open Access Journals (Sweden)

    Han-Chun Chien

    2018-04-01

    Full Text Available Background: For infants with very low birth weights (VLBW, their neurodevelopmental outcomes are thought to be associated with extra-uterine growth retardation (EUGR. In this study, based on a single institute, we analyzed the association between different levels or severity of EUGR of VLBW infants and their neurodevelopmental outcomes later at a corrected age of 24 months. Methods: This is a hospital-based retrospective cohort study. The severity of EUGR was classified into three categories according to the z-score of discharge weight: z < −2.0, <−2.5, and <−3.0. The outcomes were assessed using the Bayley Scales of Infant Development-II (BSID-II at a corrected age of 24 months. We then estimated the association of EUGR with low mental developmental index (MDI or low psychomotor developmental index (PDI. Multiple logistic regression and stratified analyses were used to adjust for the possible confounding factors. Results: In total, 224 VLBW infants were enrolled in this study from 1997 to 2006. In the univariate analysis, EUGR for weight at discharge from hospital was associated with MDI <85 at the corrected age of 24 months, and this association was related to the severity of EUGR (z < −2.5, OR: 1.92 (1.04–3.53; z < −3.0, OR: 2.83 (1.26–6.36. In addition, the relationship was not confounded by gender nor small for gestational age. The stratified analysis against hemodynamic significant patent ductus arteriosus also revealed that EUGR was an independent predictor for neurodevelopmental outcomes. Conclusion: In VLBW preterm infants, EUGR was significantly associated with low MDI scores assessed at a corrected age of 24 months. Early evaluation and recognition of EUGR should be emphasized when caring for preterm infants. Key Words: EUGR, VLBW, neurodevelopment

  1. NICE-Accredited Commissioning Guidance for Weight Assessment and Management Clinics: a Model for a Specialist Multidisciplinary Team Approach for People with Severe Obesity.

    Science.gov (United States)

    Welbourn, Richard; Dixon, John; Barth, Julian H; Finer, Nicholas; Hughes, Carly A; le Roux, Carel W; Wass, John

    2016-03-01

    Despite increasing prevalence of obesity, no country has successfully implemented comprehensive pathways to provide advice to all the severely obese patients that seek treatment. We aimed to formulate pathways for referral into and out of weight assessment and management clinics (WAMCs) that include internal medicine/primary care physicians as part of a multidisciplinary team that could provide specialist advice and interventions, including referral for bariatric surgery. Using a National Institute of Health and Care Excellence (NICE)-accredited process, a Guidance Development Group conducted a literature search identifying existing WAMCs. As very few examples of effective structures and clinical pathways existed, the current evidence base for optimal assessment and management of bariatric surgery patients was used to reach a consensus. The model we describe could be adopted internationally by health services to manage severely obese patients.

  2. Discriminative clustering on manifold for adaptive transductive classification.

    Science.gov (United States)

    Zhang, Zhao; Jia, Lei; Zhang, Min; Li, Bing; Zhang, Li; Li, Fanzhang

    2017-10-01

    In this paper, we mainly propose a novel adaptive transductive label propagation approach by joint discriminative clustering on manifolds for representing and classifying high-dimensional data. Our framework seamlessly combines the unsupervised manifold learning, discriminative clustering and adaptive classification into a unified model. Also, our method incorporates the adaptive graph weight construction with label propagation. Specifically, our method is capable of propagating label information using adaptive weights over low-dimensional manifold features, which is different from most existing studies that usually predict the labels and construct the weights in the original Euclidean space. For transductive classification by our formulation, we first perform the joint discriminative K-means clustering and manifold learning to capture the low-dimensional nonlinear manifolds. Then, we construct the adaptive weights over the learnt manifold features, where the adaptive weights are calculated through performing the joint minimization of the reconstruction errors over features and soft labels so that the graph weights can be joint-optimal for data representation and classification. Using the adaptive weights, we can easily estimate the unknown labels of samples. After that, our method returns the updated weights for further updating the manifold features. Extensive simulations on image classification and segmentation show that our proposed algorithm can deliver the state-of-the-art performance on several public datasets. Copyright © 2017 Elsevier Ltd. All rights reserved.

  3. MR relaxometry in chronic liver diseases: Comparison of T1 mapping, T2 mapping, and diffusion-weighted imaging for assessing cirrhosis diagnosis and severity

    Energy Technology Data Exchange (ETDEWEB)

    Cassinotto, Christophe, E-mail: christophe.cassinotto@chu-bordeaux.fr [Department of Diagnostic and Interventional Imaging, Hôpital Haut-Lévêque, Centre Hospitalier Universitaire et Université de Bordeaux, 1 Avenue de Magellan, 33604 Pessac (France); INSERM U1053, Université Bordeaux, Bordeaux (France); Feldis, Matthieu, E-mail: matthieu.feldis@chu-bordeaux.fr [Department of Diagnostic and Interventional Imaging, Hôpital Haut-Lévêque, Centre Hospitalier Universitaire et Université de Bordeaux, 1 Avenue de Magellan, 33604 Pessac (France); Vergniol, Julien, E-mail: julien.vergniol@chu-bordeaux.fr [Centre D’investigation de la Fibrose Hépatique, Hôpital Haut-Lévêque, Centre Hospitalier Universitaire de Bordeaux, 1 Avenue de Magellan, 33604 Pessac (France); Mouries, Amaury, E-mail: amaury.mouries@chu-bordeaux.fr [Department of Diagnostic and Interventional Imaging, Hôpital Haut-Lévêque, Centre Hospitalier Universitaire et Université de Bordeaux, 1 Avenue de Magellan, 33604 Pessac (France); Cochet, Hubert, E-mail: hubert.cochet@chu-bordeaux.fr [Department of Diagnostic and Interventional Imaging, Hôpital Haut-Lévêque, Centre Hospitalier Universitaire et Université de Bordeaux, 1 Avenue de Magellan, 33604 Pessac (France); and others

    2015-08-15

    Highlights: • The use of MR to classify cirrhosis in different stages is a new interesting field. • We compared liver and spleen T1 mapping, T2 mapping and diffusion-weighted imaging. • MR relaxometry using liver T1 mapping is accurate for the diagnosis of cirrhosis. • Liver T1 mapping shows that values increase with the severity of cirrhosis. • Diffusion-weighted imaging is less accurate than T1 mapping while T2 mapping is not reliable. - Abstract: Background: MR relaxometry has been extensively studied in the field of cardiac diseases, but its contribution to liver imaging is unclear. We aimed to compare liver and spleen T1 mapping, T2 mapping, and diffusion-weighted MR imaging (DWI) for assessing the diagnosis and severity of cirrhosis. Methods: We prospectively included 129 patients with normal (n = 40) and cirrhotic livers (n = 89) from May to September 2014. Non-enhanced liver T1 mapping, splenic T2 mapping, and liver and splenic DWI were measured and compared for assessing cirrhosis severity using Child-Pugh score, MELD score, and presence or not of large esophageal varices (EVs) and liver stiffness measurements using Fibroscan{sup ®} as reference. Results: Liver T1 mapping was the only variable demonstrating significant differences between normal patients (500 ± 79 ms), Child-Pugh A patients (574 ± 84 ms) and Child-Pugh B/C patients (690 ± 147 ms; all p-values <0.00001). Liver T1 mapping had a significant correlation with Child-Pugh score (Pearson's correlation coefficient of 0.46), MEDL score (0.30), and liver stiffness measurement (0.52). Areas under the receiver operating characteristic curves of liver T1 mapping for the diagnosis of cirrhosis (O.85; 95% confidence intervals (CI), 0.77–0.91), Child-Pugh B/C cirrhosis (0.87; 95%CI, 0.76–0.93), and large EVs (0.75; 95%CI, 0.63–0.83) were greater than that of spleen T2 mapping, liver and spleen DWI (all p-values < 0.01). Conclusion: Liver T1 mapping is a promising new diagnostic

  4. MR relaxometry in chronic liver diseases: Comparison of T1 mapping, T2 mapping, and diffusion-weighted imaging for assessing cirrhosis diagnosis and severity

    International Nuclear Information System (INIS)

    Cassinotto, Christophe; Feldis, Matthieu; Vergniol, Julien; Mouries, Amaury; Cochet, Hubert

    2015-01-01

    Highlights: • The use of MR to classify cirrhosis in different stages is a new interesting field. • We compared liver and spleen T1 mapping, T2 mapping and diffusion-weighted imaging. • MR relaxometry using liver T1 mapping is accurate for the diagnosis of cirrhosis. • Liver T1 mapping shows that values increase with the severity of cirrhosis. • Diffusion-weighted imaging is less accurate than T1 mapping while T2 mapping is not reliable. - Abstract: Background: MR relaxometry has been extensively studied in the field of cardiac diseases, but its contribution to liver imaging is unclear. We aimed to compare liver and spleen T1 mapping, T2 mapping, and diffusion-weighted MR imaging (DWI) for assessing the diagnosis and severity of cirrhosis. Methods: We prospectively included 129 patients with normal (n = 40) and cirrhotic livers (n = 89) from May to September 2014. Non-enhanced liver T1 mapping, splenic T2 mapping, and liver and splenic DWI were measured and compared for assessing cirrhosis severity using Child-Pugh score, MELD score, and presence or not of large esophageal varices (EVs) and liver stiffness measurements using Fibroscan ® as reference. Results: Liver T1 mapping was the only variable demonstrating significant differences between normal patients (500 ± 79 ms), Child-Pugh A patients (574 ± 84 ms) and Child-Pugh B/C patients (690 ± 147 ms; all p-values <0.00001). Liver T1 mapping had a significant correlation with Child-Pugh score (Pearson's correlation coefficient of 0.46), MEDL score (0.30), and liver stiffness measurement (0.52). Areas under the receiver operating characteristic curves of liver T1 mapping for the diagnosis of cirrhosis (O.85; 95% confidence intervals (CI), 0.77–0.91), Child-Pugh B/C cirrhosis (0.87; 95%CI, 0.76–0.93), and large EVs (0.75; 95%CI, 0.63–0.83) were greater than that of spleen T2 mapping, liver and spleen DWI (all p-values < 0.01). Conclusion: Liver T1 mapping is a promising new diagnostic tool for

  5. Spectroscopic classification of transients

    DEFF Research Database (Denmark)

    Stritzinger, M. D.; Fraser, M.; Hummelmose, N. N.

    2017-01-01

    We report the spectroscopic classification of several transients based on observations taken with the Nordic Optical Telescope (NOT) equipped with ALFOSC, over the nights 23-25 August 2017.......We report the spectroscopic classification of several transients based on observations taken with the Nordic Optical Telescope (NOT) equipped with ALFOSC, over the nights 23-25 August 2017....

  6. Deep neural network with weight sparsity control and pre-training extracts hierarchical features and enhances classification performance: Evidence from whole-brain resting-state functional connectivity patterns of schizophrenia.

    Science.gov (United States)

    Kim, Junghoe; Calhoun, Vince D; Shim, Eunsoo; Lee, Jong-Hwan

    2016-01-01

    Functional connectivity (FC) patterns obtained from resting-state functional magnetic resonance imaging data are commonly employed to study neuropsychiatric conditions by using pattern classifiers such as the support vector machine (SVM). Meanwhile, a deep neural network (DNN) with multiple hidden layers has shown its ability to systematically extract lower-to-higher level information of image and speech data from lower-to-higher hidden layers, markedly enhancing classification accuracy. The objective of this study was to adopt the DNN for whole-brain resting-state FC pattern classification of schizophrenia (SZ) patients vs. healthy controls (HCs) and identification of aberrant FC patterns associated with SZ. We hypothesized that the lower-to-higher level features learned via the DNN would significantly enhance the classification accuracy, and proposed an adaptive learning algorithm to explicitly control the weight sparsity in each hidden layer via L1-norm regularization. Furthermore, the weights were initialized via stacked autoencoder based pre-training to further improve the classification performance. Classification accuracy was systematically evaluated as a function of (1) the number of hidden layers/nodes, (2) the use of L1-norm regularization, (3) the use of the pre-training, (4) the use of framewise displacement (FD) removal, and (5) the use of anatomical/functional parcellation. Using FC patterns from anatomically parcellated regions without FD removal, an error rate of 14.2% was achieved by employing three hidden layers and 50 hidden nodes with both L1-norm regularization and pre-training, which was substantially lower than the error rate from the SVM (22.3%). Moreover, the trained DNN weights (i.e., the learned features) were found to represent the hierarchical organization of aberrant FC patterns in SZ compared with HC. Specifically, pairs of nodes extracted from the lower hidden layer represented sparse FC patterns implicated in SZ, which was

  7. A relative weights comparison of trauma-related shame and guilt as predictors of DSM-5 posttraumatic stress disorder symptom severity among US veterans and military members.

    Science.gov (United States)

    Cunningham, Katherine C; Davis, Joanne L; Wilson, Sarah M; Resick, Patricia A

    2018-06-01

    Veterans and military service members have increased risk for post-traumatic stress disorder (PTSD) and consequent problems with health, psychosocial functioning, and quality of life. In this population and others, shame and guilt have emerged as contributors to PTSD, but there is a considerable need for research that precisely demonstrates how shame and guilt are associated with PTSD. This study examined whether a) trauma-related shame predicts PTSD severity beyond the effects of trauma-related guilt and b) shame accounts for a greater proportion of variance in PTSD symptoms than guilt. We collected cross-sectional self-report data on measures of PTSD symptom severity based on Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) criteria, trauma-related shame, and trauma-related guilt via online survey. Participants included 61 US veterans and active duty service members. Hierarchical multiple regression and relative weights analysis were used to test hypotheses. In step 1 of regression analysis, guilt was significantly associated with PTSD. However, when shame was added to the model, the effect of guilt became non-significant, and only shame significant predicted PTSD. Results from relative weights analysis indicated that both shame and guilt predicted PTSD, jointly accounting for 46% of the variance in PTSD. Compared to guilt, trauma-related shame accounted for significantly more explained variance in PTSD. This study provided evidence that among US veterans and service members, trauma-related shame and guilt differ in their association with PTSD and that trauma-related shame, in particular, is associated with the severity of PTSD. Trauma-related shame and guilt explained almost half of the observed variance in PTSD symptom severity among this sample of US military veterans and service members. Trauma-related shame and guilt each made a unique contribution to PTSD severity after accounting for the similarity between these two emotions

  8. Handling Imbalanced Data Sets in Multistage Classification

    Science.gov (United States)

    López, M.

    Multistage classification is a logical approach, based on a divide-and-conquer solution, for dealing with problems with a high number of classes. The classification problem is divided into several sequential steps, each one associated to a single classifier that works with subgroups of the original classes. In each level, the current set of classes is split into smaller subgroups of classes until they (the subgroups) are composed of only one class. The resulting chain of classifiers can be represented as a tree, which (1) simplifies the classification process by using fewer categories in each classifier and (2) makes it possible to combine several algorithms or use different attributes in each stage. Most of the classification algorithms can be biased in the sense of selecting the most populated class in overlapping areas of the input space. This can degrade a multistage classifier performance if the training set sample frequencies do not reflect the real prevalence in the population. Several techniques such as applying prior probabilities, assigning weights to the classes, or replicating instances have been developed to overcome this handicap. Most of them are designed for two-class (accept-reject) problems. In this article, we evaluate several of these techniques as applied to multistage classification and analyze how they can be useful for astronomy. We compare the results obtained by classifying a data set based on Hipparcos with and without these methods.

  9. Classifying Classifications

    DEFF Research Database (Denmark)

    Debus, Michael S.

    2017-01-01

    This paper critically analyzes seventeen game classifications. The classifications were chosen on the basis of diversity, ranging from pre-digital classification (e.g. Murray 1952), over game studies classifications (e.g. Elverdam & Aarseth 2007) to classifications of drinking games (e.g. LaBrie et...... al. 2013). The analysis aims at three goals: The classifications’ internal consistency, the abstraction of classification criteria and the identification of differences in classification across fields and/or time. Especially the abstraction of classification criteria can be used in future endeavors...... into the topic of game classifications....

  10. Self-reported pain severity, quality of life, disability, anxiety and depression in patients classified with 'nociceptive', 'peripheral neuropathic' and 'central sensitisation' pain. The discriminant validity of mechanisms-based classifications of low back (±leg) pain.

    LENUS (Irish Health Repository)

    Smart, Keith M

    2012-04-01

    Evidence of validity is required to support the use of mechanisms-based classifications of pain clinically. The purpose of this study was to evaluate the discriminant validity of \\'nociceptive\\' (NP), \\'peripheral neuropathic\\' (PNP) and \\'central sensitisation\\' (CSP) as mechanisms-based classifications of pain in patients with low back (±leg) pain by evaluating the extent to which patients classified in this way differ from one another according to health measures associated with various dimensions of pain. This study employed a cross-sectional, between-subjects design. Four hundred and sixty-four patients with low back (±leg) pain were assessed using a standardised assessment protocol. Clinicians classified each patient\\'s pain using a mechanisms-based classification approach. Patients completed a number of self-report measures associated with pain severity, health-related quality of life, functional disability, anxiety and depression. Discriminant validity was evaluated using a multivariate analysis of variance. There was a statistically significant difference between pain classifications on the combined self-report measures, (p = .001; Pillai\\'s Trace = .33; partial eta squared = .16). Patients classified with CSP (n = 106) reported significantly more severe pain, poorer general health-related quality of life, and greater levels of back pain-related disability, depression and anxiety compared to those classified with PNP (n = 102) and NP (n = 256). A similar pattern was found in patients with PNP compared to NP. Mechanisms-based pain classifications may reflect meaningful differences in attributes underlying the multidimensionality of pain. Further studies are required to evaluate the construct and criterion validity of mechanisms-based classifications of musculoskeletal pain.

  11. Diffusion-weighted magnetic resonance imaging of thymoma: ability of the Apparent Diffusion Coefficient in predicting the World Health Organization (WHO) classification and the Masaoka-Koga staging system and its prognostic significance on disease-free survival

    International Nuclear Information System (INIS)

    Priola, Adriano Massimiliano; Priola, Sandro Massimo; Gned, Dario; Ducco, Lorena; Veltri, Andrea; Giraudo, Maria Teresa; Fornari, Alessandro; Ferrero, Bruno

    2016-01-01

    To evaluate the usefulness of diffusion-weighted magnetic resonance for distinguishing thymomas according to WHO and Masaoka-Koga classifications and in predicting disease-free survival (DFS) by using the apparent diffusion coefficient (ADC). Forty-one patients were grouped based on WHO (low-risk vs. high-risk) and Masaoka-Koga (early vs. advanced) classifications. For prognosis, seven patients with recurrence at follow-up were grouped separately from healthy subjects. Differences on ADC levels between groups were tested using Student-t testing. Logistic regression models and areas under the ROC curve (AUROC) were estimated. Mean ADC values were different between groups of WHO (low-risk = 1.58 ± 0.20 x 10 -3 mm 2 /sec; high-risk = 1.21 ± 0.23 x 10 -3 mm 2 /sec; p < 0.0001) and Masaoka-Koga (early = 1.43 ± 0.26 x 10 -3 mm 2 /sec; advanced = 1.31 ± 0.31 x 10 -3 mm 2 /sec; p = 0.016) classifications. Mean ADC of type-B3 (1.05 ± 0.17 x 10 -3 mm 2 /sec) was lower than type-B2 (1.32 ± 0.20 x 10 -3 mm 2 /sec; p = 0.023). AUROC in discriminating groups was 0.864 for WHO classification (cut-point = 1.309 x 10 -3 mm 2 /sec; accuracy = 78.1 %) and 0.730 for Masaoka-Koga classification (cut-point = 1.243 x 10 -3 mm 2 /sec; accuracy = 73.2 %). Logistic regression models and two-way ANOVA were significant for WHO classification (odds ratio[OR] = 0.93, p = 0.007; p < 0.001), but not for Masaoka-Koga classification (OR = 0.98, p = 0.31; p = 0.38). ADC levels were significantly associated with DFS recurrence rate being higher for patients with ADC ≤ 1.299 x 10 -3 mm 2 /sec (p = 0.001; AUROC, 0.834; accuracy = 78.0 %). ADC helps to differentiate high-risk from low-risk thymomas and discriminates the more aggressive type-B3. Primary tumour ADC is a prognostic indicator of recurrence. (orig.)

  12. Preoperative 3D FSE T1-Weighted MR Plaque Imaging for Severely Stenotic Cervical ICA: Accuracy of Predicting Emboli during Carotid Endarterectomy

    Directory of Open Access Journals (Sweden)

    Yasushi Ogasawara

    2016-10-01

    Full Text Available The aim of the present study was to determine whether preoperative three-dimensional (3D fast spin-echo (FSE T1-weighted magnetic resonance (MR plaque imaging for severely stenotic cervical carotid arteries could accurately predict the development of artery-to-artery emboli during exposure of the carotid arteries in carotid endarterectomy (CEA. Seventy-five patients underwent preoperative MR plaque imaging and CEA under transcranial Doppler ultrasonography of the ipsilateral middle cerebral artery. On reformatted axial MR image slices showing the maximum plaque occupation rate (POR and maximum plaque intensity for each patient, the contrast ratio (CR was calculated by dividing the internal carotid artery plaque signal intensity by the sternocleidomastoid muscle signal intensity. For all patients, the area under the receiver operating characteristic curve (AUC—used to discriminate between the presence and absence of microembolic signals—was significantly greater for the CR on the axial image with maximum plaque intensity (CRmax intensity (0.941 than for that with the maximum POR (0.885 (p < 0.05. For 32 patients in whom both the maximum POR and the maximum plaque density were identified, the AUCs for the CR were 1.000. Preoperative 3D FSE T1-weighted MR plaque imaging accurately predicts the development of artery-to-artery emboli during exposure of the carotid arteries in CEA.

  13. Knowledge discovery from patients' behavior via clustering-classification algorithms based on weighted eRFM and CLV model: An empirical study in public health care services.

    Science.gov (United States)

    Zare Hosseini, Zeinab; Mohammadzadeh, Mahdi

    2016-01-01

    The rapid growing of information technology (IT) motivates and makes competitive advantages in health care industry. Nowadays, many hospitals try to build a successful customer relationship management (CRM) to recognize target and potential patients, increase patient loyalty and satisfaction and finally maximize their profitability. Many hospitals have large data warehouses containing customer demographic and transactions information. Data mining techniques can be used to analyze this data and discover hidden knowledge of customers. This research develops an extended RFM model, namely RFML (added parameter: Length) based on health care services for a public sector hospital in Iran with the idea that there is contrast between patient and customer loyalty, to estimate customer life time value (CLV) for each patient. We used Two-step and K-means algorithms as clustering methods and Decision tree (CHAID) as classification technique to segment the patients to find out target, potential and loyal customers in order to implement strengthen CRM. Two approaches are used for classification: first, the result of clustering is considered as Decision attribute in classification process and second, the result of segmentation based on CLV value of patients (estimated by RFML) is considered as Decision attribute. Finally the results of CHAID algorithm show the significant hidden rules and identify existing patterns of hospital consumers.

  14. Knowledge discovery from patients’ behavior via clustering-classification algorithms based on weighted eRFM and CLV model: An empirical study in public health care services

    Science.gov (United States)

    Zare Hosseini, Zeinab; Mohammadzadeh, Mahdi

    2016-01-01

    The rapid growing of information technology (IT) motivates and makes competitive advantages in health care industry. Nowadays, many hospitals try to build a successful customer relationship management (CRM) to recognize target and potential patients, increase patient loyalty and satisfaction and finally maximize their profitability. Many hospitals have large data warehouses containing customer demographic and transactions information. Data mining techniques can be used to analyze this data and discover hidden knowledge of customers. This research develops an extended RFM model, namely RFML (added parameter: Length) based on health care services for a public sector hospital in Iran with the idea that there is contrast between patient and customer loyalty, to estimate customer life time value (CLV) for each patient. We used Two-step and K-means algorithms as clustering methods and Decision tree (CHAID) as classification technique to segment the patients to find out target, potential and loyal customers in order to implement strengthen CRM. Two approaches are used for classification: first, the result of clustering is considered as Decision attribute in classification process and second, the result of segmentation based on CLV value of patients (estimated by RFML) is considered as Decision attribute. Finally the results of CHAID algorithm show the significant hidden rules and identify existing patterns of hospital consumers. PMID:27610177

  15. Detection of hepatocellular carcinoma in gadoxetic acid-enhanced MRI and diffusion-weighted MRI with respect to the severity of liver cirrhosis

    International Nuclear Information System (INIS)

    Kim, Ah Yeong; Kim, Young Kon; Lee, Min Woo; Park, Min Jung; Hwang, Jiyoung; Lee, Mi Hee; Lee, Jae Won

    2012-01-01

    Background As gadoxetic acid-enhanced magnetic resonance imaging (MRI) and diffusion-weighted imaging (DWI) have been widely used for the evaluation of hepatocellular carcinoma (HCC), it is clinically relevant to determine the diagnostic efficacy of gadoxetic acid-enhanced MRI and DWI for detection of HCCs with respect to the severity of liver cirrhosis. Purpose To compare the diagnostic accuracy and sensitivity of gadoxetic acid-enhanced MRI and DWI for detection of HCCs with respect to the severity of liver cirrhosis. Material and Methods A total of 189 patients with 240 HCCs (≤3.0 cm) (Child-Pugh A, 81 patients with 90 HCCs; Child-Pugh B, 65 patients with 85 HCCs; Child-Pugh C, 43 patients with 65 HCCs) underwent DWI and gadoxetic acid-enhanced MRI at 3.0 T. A gadoxetic acid set (dynamic and hepatobiliary phase plus T2-weighted image) and DWI set (DWI plus unenhanced MRIs) for each Child-Pugh class were analyzed independently by two observers for detecting HCCs using receiver-operating characteristic analysis. The diagnostic accuracy and sensitivity were calculated. Results There was a trend toward decreased diagnostic accuracy for gadoxetic acid and DWI set with respect to the severity of cirrhosis (Child-Pugh A [mean 0.974, 0.961], B [mean 0.904, 0.863], C [mean 0.779, 0.760]). For both observers, the sensitivities of both image sets were highest in Child-Pugh class A (mean 95.6%, 93.9%), followed by class B (mean 83.0%, 77.1%), and class C (mean 60.6%, 60.0%) (P < 0.05). Conclusion In HCC detection, the diagnostic accuracy and sensitivity for gadoxetic acid-enhanced MRI and DWI were highest in Child-Pugh class A, followed by Child-Pugh class B, and Child-Pugh class C, indicating a tendency toward decreased diagnostic capability with the severity of cirrhosis

  16. Exercise training with weight loss and either a high- or low-glycemic index diet reduces metabolic syndrome severity in older adults.

    Science.gov (United States)

    Malin, Steven K; Niemi, Nicole; Solomon, Thomas P J; Haus, Jacob M; Kelly, Karen R; Filion, Julianne; Rocco, Michael; Kashyap, Sangeeta R; Barkoukis, Hope; Kirwan, John P

    2012-01-01

    The efficacy of combining carbohydrate quality with exercise on metabolic syndrome risk is unclear. Thus, we determined the effects of exercise training with a low (LoGIx)- or high (HiGIx)-glycemic index diet on the severity of the metabolic syndrome (Z-score). Twenty-one adults (66.2±1.1 years; BMI=35.3±0.9 kg/m2) with the metabolic syndrome were randomized to 12 weeks of exercise (60 min/day for 5 days/week at about 85% HRmax) and provided a LoGIx (n=11) or HiGIx (n=10) diet. Z-scores were determined from: blood pressure, triglycerides (TGs), high-density lipoproteins (HDLs), fasting plasma glucose (FPG), and waist circumference (WC) before and after the intervention. Body composition, aerobic fitness, insulin resistance, and nonesterfied fatty acid (NEFA) suppression were also assessed. LoGIx and HiGIx diets decreased body mass and insulin resistance and increased aerobic fitness comparably (pdiets decreased the Z-score similarly as each intervention decreased blood pressure, TGs, FPG and WC (pdiet tended to suppress NEFA during insulin stimulation compared with the LoGIx diet (p=0.06). Our findings highlight that exercise with weight loss reduces the severity of the metabolic syndrome whether individuals were randomized to a HiGIx or a LoGIx diet.

  17. Dairy cow disability weights.

    Science.gov (United States)

    McConnel, Craig S; McNeil, Ashleigh A; Hadrich, Joleen C; Lombard, Jason E; Garry, Franklyn B; Heller, Jane

    2017-08-01

    Over the past 175 years, data related to human disease and death have progressed to a summary measure of population health, the Disability-Adjusted Life Year (DALY). As dairies have intensified there has been no equivalent measure of the impact of disease on the productive life and well-being of animals. The development of a disease-adjusted metric requires a consistent set of disability weights that reflect the relative severity of important diseases. The objective of this study was to use an international survey of dairy authorities to derive disability weights for primary disease categories recorded on dairies. National and international dairy health and management authorities were contacted through professional organizations, dairy industry publications and conferences, and industry contacts. Estimates of minimum, most likely, and maximum disability weights were derived for 12 common dairy cow diseases. Survey participants were asked to estimate the impact of each disease on overall health and milk production. Diseases were classified from 1 (minimal adverse effects) to 10 (death). The data was modelled using BetaPERT distributions to demonstrate the variation in these dynamic disease processes, and to identify the most likely aggregated disability weights for each disease classification. A single disability weight was assigned to each disease using the average of the combined medians for the minimum, most likely, and maximum severity scores. A total of 96 respondents provided estimates of disability weights. The final disability weight values resulted in the following order from least to most severe: retained placenta, diarrhea, ketosis, metritis, mastitis, milk fever, lame (hoof only), calving trauma, left displaced abomasum, pneumonia, musculoskeletal injury (leg, hip, back), and right displaced abomasum. The peaks of the probability density functions indicated that for certain disease states such as retained placenta there was a relatively narrow range of

  18. Ethnic variation in validity of classification of overweight and obesity using self-reported weight and height in American women and men: the Third National Health and Nutrition Examination Survey

    Directory of Open Access Journals (Sweden)

    Sempos Christopher T

    2005-10-01

    Full Text Available Abstract Background Few data have been published on the validity of classification of overweight and obesity based on self-reported weight in representative samples of Hispanic as compared to other American populations despite the wide use of such data. Objective To test the null hypothesis that ethnicity is unrelated to bias of mean body mass index (BMI and to sensitivity of overweight or obesity (BMI >= 25 kg/m2 derived from self-reported (SR versus measured weight and height using measured BMI as the gold standard. Design Cross-sectional survey of a large national sample, the Third National Health and Nutrition Examination Survey (NHANES III conducted in 1988–1994. Participants American men and women aged 20 years and over (n = 15,025. Measurements SR height, weight, cigarette smoking, health status, and socio-demographic variables from home interview and measured weight and height. Results In women and Mexican American (MA men SR BMI underestimated true prevalence rates of overweight or obesity. For other men, no consistent difference was seen. Sensitivity of SR was similar in non-Hispanic European Americans (EA and non-Hispanic African Americans (AA but much lower in MA. Prevalence of obesity (BMI >= 30 kg/m2 is consistently underestimated by self-report, the gap being greater for MA than for other women, but similar for MA and other men. The mean difference between self-reported and measured BMI was greater in MA (men -0.37, women -0.76 kg/m2 than in non-Hispanic EA (men -0.22, women -0.62 kg/m2. In a regression model with the difference between self-reported and measured BMI as the dependent variable, MA ethnicity was a significant (p Conclusion Under-estimation of the prevalence of overweight or obesity based on height and weight self-reported at interview varied significantly among ethnic groups independent of other variables.

  19. Feasibility of using self-reported ethnicity in pregnancy according to the gestation-related optimal weight classification: a cross-sectional study.

    Science.gov (United States)

    Lockie, E; McCarthy, E A; Hui, L; Churilov, L; Walker, S P

    2018-05-01

    To evaluate the feasibility of self-reported ethnicity using the gestation-related optimal growth (GROW) classification in a contemporary multicultural antenatal population. Cross-sectional study. Tertiary obstetric hospital in Melbourne, Australia. Pregnant women attending the antenatal clinic. We surveyed pregnant women during April-June 2016 regarding their understanding of the term 'ethnicity', and how they would classify the ethnicity of themselves, their partner, and family members according to the Australian GROW classification. Two hundred and thirty-five women completed the survey. When describing 'ethnicity', most women (103, 44%) chose multiple descriptors, most frequently country of birth (54%) and region of ancestry (47%). Interpretation of 'ethnicity' varied significantly between ethnic groups: those choosing 'country of birth' were more likely to identify as Indian (odds ratio, OR 3.5, P = 0.03), whereas those choosing 'physical appearance' were more likely to identify as Chinese (OR 3.0, P = 0.047). Thirty participants (13%) were unable to describe their ethnicity from the available GROW options. Sixty-one (26%) respondents' ethnicity was inconsistent with that of their parents' heritage. A further 35% had a partner of different ethnicity. The agreement between country of birth and self-reported ethnicity was only fair (kappa 0.73, 95% confidence interval, 95% CI 0.64-0.82). This study confirms the complexity of defining ethnicity in contemporary multicultural settings. Self-reported ethnicity is often inaccurate, concepts of ethnicity vary by ethnic group, and country of birth is a poor descriptive surrogate. Adjustment for maternal ethnicity should be undertaken with caution in the customised assessment of fetal growth. Is self-reported maternal ethnicity reliable? We think not. © 2017 Royal College of Obstetricians and Gynaecologists.

  20. Localization of Coronary High-Intensity Signals on T1-Weighted MR Imaging: Relation to Plaque Morphology and Clinical Severity of Angina Pectoris.

    Science.gov (United States)

    Matsumoto, Kenji; Ehara, Shoichi; Hasegawa, Takao; Sakaguchi, Mikumo; Otsuka, Kenichiro; Yoshikawa, Junichi; Shimada, Kenei

    2015-10-01

    This study sought to investigate the relationship between localization of high-intensity signals (HISs) on T1-weighted imaging (T1WI) with the noncontrast magnetic resonance technique and plaque morphology detected on optical coherence tomography, and the clinical severity of angina pectoris. Since the introduction of the T1WI noncontrast magnetic resonance technique for plaque imaging, some groups have reported that HISs in the coronary artery on T1WI are associated with a vulnerable morphology and future cardiac events. However, the association between the localization of HISs, such as coronary intrawall or intraluminal, and plaque morphology has not been investigated. One hundred lesions with either stable or unstable angina were included and divided into 3 groups according to the following criteria using T1WI. First, the plaques with the ratio between the signal intensities of coronary plaque and cardiac muscle ≤1.0 were classified as non-HISs (n = 39). Then, HISs with the ratio between the signal intensities of coronary plaque and cardiac muscle >1.0 were classified into 2 types by using cross-sectional T1WI. Those localized within the coronary wall when the lumen was identified were defined as intrawall HISs (n = 37), whereas those occupying the lumen when the lumen was not, or even if only partly, identified, were defined as intraluminal HISs (n = 24). Multivariate analysis revealed that intrawall HISs were associated with macrophage accumulation and the absence of calcification assessed by using optical coherence tomography. In contrast, thrombus and intimal vasculature were independent factors associated with intraluminal HISs. Furthermore, 50% of patients with intraluminal HISs experienced rest angina, such as Braunwald class II or III. This study shows that intrawall and intraluminal HISs on T1WI in patients with angina are related to the different types of vulnerable plaque morphology and the clinical severity. Copyright © 2015 American College of

  1. Revised PROPELLER for T2-weighted imaging of the prostate at 3 Tesla: impact on lesion detection and PI-RADS classification

    Energy Technology Data Exchange (ETDEWEB)

    Meier-Schroers, Michael; Marx, Christian; Schmeel, Frederic Carsten; Wolter, Karsten; Block, Wolfgang; Sprinkart, Alois Martin; Traeber, Frank; Schild, Hans Heinz; Kukuk, Guido Matthias [University Hospital Bonn, Department of Radiology, Bonn (Germany); Gieseke, Juergen [Philips Healthcare Germany, Hamburg (Germany); Willinek, Winfried [Hospital of Barmherzige Brueder, Department of Radiology, Neuroradiology, Sonography and Nuclear Medicine, Trier (Germany)

    2018-01-15

    To evaluate revised PROPELLER (RevPROP) for T2-weighted imaging (T2WI) of the prostate as a substitute for turbo spin echo (TSE). Three-Tesla MR images of 50 patients with 55 cancer-suspicious lesions were prospectively evaluated. Findings were correlated with histopathology after MRI-guided biopsy. T2 RevPROP, T2 TSE, diffusion-weighted imaging, dynamic contrast enhancement, and MR-spectroscopy were acquired. RevPROP was compared to TSE concerning PI-RADS scores, lesion size, lesion signal-intensity, lesion contrast, artefacts, and image quality. There were 41 carcinomas in 55 cancer-suspicious lesions. RevPROP detected 41 of 41 carcinomas (100%) and 54 of 55 lesions (98.2%). TSE detected 39 of 41 carcinomas (95.1%) and 51 of 55 lesions (92.7%). RevPROP showed fewer artefacts and higher image quality (each p < 0.001). No differences were observed between single and overall PI-RADS scores based on RevPROP or TSE (p = 0.106 and p = 0.107). Lesion size was not different (p = 0.105). T2-signal intensity of lesions was higher and T2-contrast of lesions was lower on RevPROP (each p < 0.001). For prostate cancer detection RevPROP is superior to TSE with respect to motion robustness, image quality and detection rates of lesions. Therefore, RevPROP might be used as a substitute for T2WI. (orig.)

  2. Revised PROPELLER for T2-weighted imaging of the prostate at 3 Tesla: impact on lesion detection and PI-RADS classification

    International Nuclear Information System (INIS)

    Meier-Schroers, Michael; Marx, Christian; Schmeel, Frederic Carsten; Wolter, Karsten; Block, Wolfgang; Sprinkart, Alois Martin; Traeber, Frank; Schild, Hans Heinz; Kukuk, Guido Matthias; Gieseke, Juergen; Willinek, Winfried

    2018-01-01

    To evaluate revised PROPELLER (RevPROP) for T2-weighted imaging (T2WI) of the prostate as a substitute for turbo spin echo (TSE). Three-Tesla MR images of 50 patients with 55 cancer-suspicious lesions were prospectively evaluated. Findings were correlated with histopathology after MRI-guided biopsy. T2 RevPROP, T2 TSE, diffusion-weighted imaging, dynamic contrast enhancement, and MR-spectroscopy were acquired. RevPROP was compared to TSE concerning PI-RADS scores, lesion size, lesion signal-intensity, lesion contrast, artefacts, and image quality. There were 41 carcinomas in 55 cancer-suspicious lesions. RevPROP detected 41 of 41 carcinomas (100%) and 54 of 55 lesions (98.2%). TSE detected 39 of 41 carcinomas (95.1%) and 51 of 55 lesions (92.7%). RevPROP showed fewer artefacts and higher image quality (each p < 0.001). No differences were observed between single and overall PI-RADS scores based on RevPROP or TSE (p = 0.106 and p = 0.107). Lesion size was not different (p = 0.105). T2-signal intensity of lesions was higher and T2-contrast of lesions was lower on RevPROP (each p < 0.001). For prostate cancer detection RevPROP is superior to TSE with respect to motion robustness, image quality and detection rates of lesions. Therefore, RevPROP might be used as a substitute for T2WI. (orig.)

  3. Weight loss is effective for symptomatic relief in obese subjects with knee osteoarthritis independently of joint damage severity assessed by high-field MRI and radiography

    DEFF Research Database (Denmark)

    Gudbergsen, H.; Boesen, M.; Lohmander, L. S.

    2012-01-01

    With an increasing prevalence of older and obese citizens, the problems of knee osteoarthritis (KOA) will escalate. Weight loss is recommended for obese KOA patients and in a majority of cases this leads to symptomatic relief. We hypothesized that pre-treatment structural status of the knee joint......, assessed by radiographs, 1.5 T magnetic resonance imaging (MRI) and knee-joint alignment, may influence the symptomatic changes following a significant weight reduction....

  4. Angiogenic Factor Profiles in Pregnant Women With a History of Early-Onset Severe Preeclampsia Receiving Low-Molecular-Weight Heparin Prophylaxis.

    Science.gov (United States)

    Lecarpentier, Edouard; Gris, Jean Christophe; Cochery-Nouvellon, Eva; Mercier, Erick; Touboul, Cyril; Thadhani, Ravi; Karumanchi, S Ananth; Haddad, Bassam

    2018-01-01

    To evaluate whether daily low-molecular-weight (LMW) heparin prophylaxis during pregnancy alters profile of circulating angiogenic factors that have been linked with the pathogenesis of preeclampsia and fetal growth restriction. This is a planned ancillary study of the Heparin-Preeclampsia trial, a randomized trial in pregnant women with a history of severe early-onset preeclampsia (less than 34 weeks of gestation). In the parent study, all women were treated with aspirin and then randomized to receive LMW heparin or aspirin alone. In this study, we measured serum levels of circulating angiogenic factors (soluble fms-like tyrosine kinase-1, placental growth factor, and soluble endoglin by immunoassay) at the following gestational windows: 10-13 6/7 weeks, 14-17 6/7 weeks, 18-21 6/7 weeks, 22-25 6/7 weeks, 26-29 6/7 weeks, 30-33 6/7 weeks, and 34-37 6/7 weeks. Samples were available from 185 patients: LMW heparin+aspirin (n=92) and aspirin alone (n=93). The two groups had comparable baseline characteristics and had similar adverse composite outcomes (35/92 [38.0%] compared with 36/93 [38.7%]; P=.92). There were no significant differences in serum levels of soluble fms-like tyrosine kinase-1, placental growth factor, and soluble endoglin in the participants who received LMW heparin and aspirin compared with those who received aspirin alone regardless of gestational age period. Finally, women who developed an adverse composite outcome at less than 34 weeks of gestation demonstrated significant alterations in serum angiogenic profile as early as 10-13 6/7 weeks that was most dramatic 6-8 weeks preceding delivery. Prophylactic LMW heparin therapy when beginning from before 14 weeks of gestation with aspirin during pregnancy is not associated with an improved angiogenic profile. This may provide a molecular explanation for the lack of clinical benefit noted in recent trials. ClinicalTrials.gov, NCT00986765.

  5. Role of body mass index in school-aged children with lower urinary tract dysfunction: Does weight classification predict treatment outcome?

    Science.gov (United States)

    Arlen, Angela M; Cooper, Christopher S; Leong, Traci

    2017-10-01

    Lower urinary tract (LUT) dysfunction comprises a large percentage of pediatric urology referrals. Childhood obesity is a major health concern, and has been associated with voiding symptoms. We assessed the impact of body mass index (BMI) on treatment outcomes of children presenting with LUT or bladder-bowel dysfunction (BBD). Children aged 5-17 years diagnosed with non-neurogenic LUT dysfunction and no prior urologic diagnoses were identified. Patient demographics including BMI, lower urinary tract symptoms, constipation, medical and psychologic comorbidities, imaging, and treatment outcomes were evaluated. BMI was normalized by age and gender according to percentiles: underweight  95th percentile. Uni- and multivariate analyses were performed to identify predictors of treatment response. During an 18-month period, 100 children (54 girls, 46 boys) met the inclusion criteria. The mean age at diagnosis was 7.7 ± 2.4 years, and mean length of follow-up 15.3 ± 13.1 months. Sixty-nine patients were a normal weight, 22 were overweight, and nine were obese. Fifteen percent of the children had complete treatment response, 63% partial response, and 22% non-response. On univariate analysis, children with elevated BMI (p = 0.04) or history of urinary tract infection (p = 0.01) were statistically more likely to not respond to treatment. Controlling for all other variables, children with BMI > 85th percentile had 3.1 times (95% CI 1.11-8.64; p = 0.03) increased odds of treatment failure (Table). BBD management includes implementation of a bowel program and timed voiding regimen, with additional treatment modalities tailored on the basis of the prevailing symptoms. We observed that school-aged children with a BMI ≥ 85th percentile were over three times more likely to experience treatment failure when controlling for all other patient characteristics including constipation and a history of urinary tract infection. Limitations of the study include the

  6. Comparative study of 99Tcm-ciprofloxacin scintigraphy, 18F-FDG PET and diffusion weighted imaging for detecting secondary infection associated with severe acute pancreatitis

    International Nuclear Information System (INIS)

    Wang Jianhua; Sun Gaofeng; Zhang Jian; Shao Chengwei; Pan Guixia; Peng Ye; Mao Juanli; Zheng Jianming; Zuo Changjing

    2013-01-01

    Objective: To compare the diagnostic values of 99 Tc m -ciprofloxacin SPECT, 18 F-FDG PET and MR diffusion weighted imaging (DWI) for detecting secondary infection associated with severe acute pancreatitis (SAP) in swine. Methods: Swine models were constructed and grouped, including control group (normal swine, n=6), non-infected SAP group (inoculated with inactivation Escherichia coli, n=6)and infected SAP group (inoculated with Escherichia coli, n=16). At 7 d after inoculation,a series of 99 Tc m ciprofloxacin SPECT, 18 F-FDG PET and MR DWI scans were performed. The imaging findings were visually evaluated and semi-quantitative analyzed. Lesion-background radioactive counts ratio (L/B), SUV max and the apparent diffusion coefficient (ADC) were calculated. The image results were compared with histopathological and bacteriological results, and the sensitivity, specificity, accuracy, positive predictive value and negative predictive value were calculated. Bonferroni test, the least significant difference t test and χ 2 test were used for statistical data analysis. Results: (1) The sensitivity, specificity, accuracy, positive predictive value and negative predictive value of 99 Tc m -ciprofloxacin SPECT via visual analysis were 93.8% (15/16), 5/6, 90.9% (20/22), 93.8%(15/16) and 5/6, whereas 81.2% (13/16), 2/6, 68.2% (15/22), 76.5%(13/17) and 2/5 for 18 F-FDG PET, and 15.4% (2/13), 5/6, 36.8%(7/19), 2/3 and 31.3% (5/16) for MRI DWI respectively. Both 99 Tc m -ciprofloxacin SPECT and 18 F-FDG PET had higher sensitivities (both P>0.05), but the specificity of 18 F-FDG PET was lower. (2) 99 Tc m -ciprofloxacin imaging showed the changes of L/B for the infected SAP swine were significantly different from those of the non-infected and normal swine (F=95.66, P<0.001). 18 F-FDG PET early-phase images showed SUV max was not significantly different between infected SAP (2.61±1.07) and non-infected SAP (1.87±0.76) groups (P>0.05), but the SUV max of infected SAP group was

  7. Self-regulatory skills usage strengthens the relations of self-efficacy for improved eating, exercise, and weight in the severely obese: toward an explanatory model.

    Science.gov (United States)

    Annesi, James J

    2011-07-01

    Lack of success with behavioral weight-management treatments indicates a need for a better understanding of modifiable psychological correlates. Adults with class 2 and 3 obesity (N = 183; Mean(BMI) = 42.0 kg/m(2)) volunteered for a 26-week nutrition and exercise treatment, based on social cognitive theory, that focused on self-efficacy and self-regulation applied to increasing cardiovascular exercise and fruit and vegetable consumption. Improved self-efficacy for controlled eating significantly predicted increased fruit and vegetable consumption (R(2) = .15). Improved self-efficacy for exercise significantly predicted increased exercise (R(2) = .46). When changes in self-regulatory skill usage were stepped into the 2 previous equations, the variances accounted for significantly increased. Increases in fruit and vegetable consumption and exercise significantly predicted weight loss (R(2) = .38). Findings suggest that behavioral theory should guide research on weight-loss treatment, and a focus on self-efficacy and self-regulatory skills applied to specific nutrition and exercise behaviors is warranted.

  8. Sustained High Levels of Both Total and High Molecular Weight Adiponectin in Plasma during the Convalescent Phase of Haemorrhagic Fever with Renal Syndrome Are Associated with Disease Severity

    Directory of Open Access Journals (Sweden)

    Kang Tang

    2017-01-01

    Full Text Available Haemorrhagic fever with renal syndrome (HFRS is characterised by an uncontrolled immune response that causes vascular leakage. Adiponectin (APN is an adipocytokine involved in prorevascularisation and immunomodulation. To investigate the possible effects of APN in the pathogenesis of HFRS, total and high molecular weight (HMW APN levels in the plasma of patients with HFRS were quantified using enzyme-linked immunosorbent assay (ELISA. Compared with those in healthy controls, the plasma total and HMW APN levels in patients were elevated to different degrees from the fever onset and remained high at the convalescent phase. Consistent with these results, western blot analysis additionally showed that low molecular weight (LMW, middle molecular weight (MMW, and HMW APN levels were all elevated and contributed to the elevation of the total APN level. Importantly, sustained high levels of total and HMW APN at the convalescent phase were significantly higher in patients with critical disease than those in patients with mild or moderate disease. Moreover, total and HMW APN levels negatively correlated with white blood cell count and positively correlated with platelet count and serum albumin level. These results may provide insights into understanding the roles of total and HMW APN in the pathogenesis of HFRS.

  9. Bosniak Classification system

    DEFF Research Database (Denmark)

    Graumann, Ole; Osther, Susanne Sloth; Karstoft, Jens

    2014-01-01

    Background: The Bosniak classification is a diagnostic tool for the differentiation of cystic changes in the kidney. The process of categorizing renal cysts may be challenging, involving a series of decisions that may affect the final diagnosis and clinical outcome such as surgical management....... Purpose: To investigate the inter- and intra-observer agreement among experienced uroradiologists when categorizing complex renal cysts according to the Bosniak classification. Material and Methods: The original categories of 100 cystic renal masses were chosen as “Gold Standard” (GS), established...... to the calculated weighted κ all readers performed “very good” for both inter-observer and intra-observer variation. Most variation was seen in cysts catagorized as Bosniak II, IIF, and III. These results show that radiologists who evaluate complex renal cysts routinely may apply the Bosniak classification...

  10. Cerebral ischemic lesions detected with diffusion-weighted magnetic resonance imaging after carotid artery stenting. Comparison of several anti-embolic protection devices

    International Nuclear Information System (INIS)

    Taha, M.M.; Maeda, Masayuki; Sakaida, Hiroshi

    2009-01-01

    Distal embolism is an important periprocedural technical complication with carotid angioplasty and carotid artery stenting (CAS). We evaluated the safety and efficacy of protection devices used during CAS by detecting new cerebral ischemic lesions using diffusion-weighted magnetic resonance imaging in 95 patients who underwent 98 CAS procedures: 34 using single PercuSurge GuardWire, 31 using double balloon protection, 15 using proximal flow reverse protection devices, 14 using Naviballoon, and 4 using filter anti-embolic devices. Diffusion-weighted imaging was performed preoperatively and postoperatively to evaluate the presence of any new embolic cerebral lesions. Postoperative diffusion-weighted imaging revealed 117 new ischemic lesions. Three patients had new ischemic stroke, two minor and one major, all ipsilateral to the treated carotid artery. The remaining patients had clinically silent ischemia. The incidence of new embolic lesions was lower using the proximal flow reverse protection device than with the double balloon protection (33% vs. 48.4%), but the volume of ipsilateral new ischemic lesions per patient was 136.6 mm 3 vs. 86.9 mm 3 , respectively. Neuroprotection with Naviballoon yielded ipsilateral lesions of large volume (86.6 mm 3 ) and higher number (5.7 lesions per patient) than using the filter anti-embolic device (34.8 mm 3 and 1 lesion per patient). New cerebral ischemic lesions after neuroprotected CAS are usually silent. The lower incidence of distal ischemia using proximal flow reverse and double balloon protection devices is limited by the larger volume and higher number of ischemic lesions. (author)

  11. Cerebral ischemic lesions detected with diffusion-weighted magnetic resonance imaging after carotid artery stenting: Comparison of several anti-embolic protection devices.

    Science.gov (United States)

    Taha, Mahmoud M; Maeda, Masayuki; Sakaida, Hiroshi; Kawaguchi, Kenji; Toma, Naoki; Yamamoto, Akitaka; Hirose, Tomofumi; Miura, Youichi; Fujimoto, Masashi; Matsushima, Satoshi; Taki, Waro

    2009-09-01

    Distal embolism is an important periprocedural technical complication with carotid angioplasty and carotid artery stenting (CAS). We evaluated the safety and efficacy of protection devices used during CAS by detecting new cerebral ischemic lesions using diffusion-weighted magnetic resonance imaging in 95 patients who underwent 98 CAS procedures: 34 using single PercuSurge GuardWire, 31 using double balloon protection, 15 using proximal flow reverse protection devices, 14 using Naviballoon, and 4 using filter anti-embolic devices. Diffusion-weighted imaging was performed preoperatively and postoperatively to evaluate the presence of any new embolic cerebral lesions. Postoperative diffusion-weighted imaging revealed 117 new ischemic lesions. Three patients had new ischemic stroke, two minor and one major, all ipsilateral to the treated carotid artery. The remaining patients had clinically silent ischemia. The incidence of new embolic lesions was lower using the proximal flow reverse protection device than with the double balloon protection (33% vs. 48.4%), but the volume of ipsilateral new ischemic lesions per patient was 136.6 mm(3) vs. 86.9 mm(3), respectively. Neuroprotection with Naviballoon yielded ipsilateral lesions of large volume (86.6 mm(3)) and higher number (5.7 lesions per patient) than using the filter anti-embolic device (34.8 mm(3) and 1 lesion per patient). New cerebral ischemic lesions after neuroprotected CAS are usually silent. The lower incidence of distal ischemia using proximal flow reverse and double balloon protection devices is limited by the larger volume and higher number of ischemic lesions.

  12. Exploratory double-blind, parallel-group, placebo-controlled study of edaravone (MCI-186) in amyotrophic lateral sclerosis (Japan ALS severity classification: Grade 3, requiring assistance for eating, excretion or ambulation).

    Science.gov (United States)

    2017-10-01

    Our objective was to explore the efficacy and safety of edaravone in amyotrophic lateral sclerosis (ALS) patients with a Japan ALS severity classification of Grade 3. In a 24-week, double-blind, randomized study, 25 patients who met all of the following criteria were enrolled: Japan ALS severity classification Grade 3; definite, probable, or probable-laboratory supported ALS (El Escorial/revised Airlie House); forced vital capacity (%FVC) ≥60%; duration of disease ≤3 years at consent; and change in the revised ALS functional rating scale (ALSFRS-R) score of -1 to -4 points during the 12-week pre-observation period. Patients received edaravone (n = 13) or placebo (n = 12) for six cycles. The efficacy outcome was change in the ALSFRS-R score. The least-squares mean change in the ALSFRS-R score ± standard error during the 24-week treatment was -6.52 ± 1.78 in the edaravone group and -6.00 ± 1.83 in the placebo group; the difference of -0.52 ± 2.46 was not statistically significant (p = 0.835). Incidence of adverse events was 92.3% (12/13) in the edaravone group and 100.0% (12/12) in the placebo group. There was no intergroup difference in the changes in the ALSFRS-R score. The incidences of adverse events were similar in the two groups.

  13. Weighted approximation with varying weight

    CERN Document Server

    Totik, Vilmos

    1994-01-01

    A new construction is given for approximating a logarithmic potential by a discrete one. This yields a new approach to approximation with weighted polynomials of the form w"n"(" "= uppercase)P"n"(" "= uppercase). The new technique settles several open problems, and it leads to a simple proof for the strong asymptotics on some L p(uppercase) extremal problems on the real line with exponential weights, which, for the case p=2, are equivalent to power- type asymptotics for the leading coefficients of the corresponding orthogonal polynomials. The method is also modified toyield (in a sense) uniformly good approximation on the whole support. This allows one to deduce strong asymptotics in some L p(uppercase) extremal problems with varying weights. Applications are given, relating to fast decreasing polynomials, asymptotic behavior of orthogonal polynomials and multipoint Pade approximation. The approach is potential-theoretic, but the text is self-contained.

  14. Granular loess classification based

    International Nuclear Information System (INIS)

    Browzin, B.S.

    1985-01-01

    This paper discusses how loess might be identified by two index properties: the granulometric composition and the dry unit weight. These two indices are necessary but not always sufficient for identification of loess. On the basis of analyses of samples from three continents, it was concluded that the 0.01-0.5-mm fraction deserves the name loessial fraction. Based on the loessial fraction concept, a granulometric classification of loess is proposed. A triangular chart is used to classify loess

  15. Unsupervised Classification Using Immune Algorithm

    OpenAIRE

    Al-Muallim, M. T.; El-Kouatly, R.

    2012-01-01

    Unsupervised classification algorithm based on clonal selection principle named Unsupervised Clonal Selection Classification (UCSC) is proposed in this paper. The new proposed algorithm is data driven and self-adaptive, it adjusts its parameters to the data to make the classification operation as fast as possible. The performance of UCSC is evaluated by comparing it with the well known K-means algorithm using several artificial and real-life data sets. The experiments show that the proposed U...

  16. Exercise training with weight loss and either a high- or low-glycemic index diet reduces metabolic syndrome severity in older adults

    DEFF Research Database (Denmark)

    Malin, Steven K; Niemi, Nicole; Solomon, Thomas

    2012-01-01

    The efficacy of combining carbohydrate quality with exercise on metabolic syndrome risk is unclear. Thus, we determined the effects of exercise training with a low (LoGIx)- or high (HiGIx)-glycemic index diet on the severity of the metabolic syndrome (Z-score).......The efficacy of combining carbohydrate quality with exercise on metabolic syndrome risk is unclear. Thus, we determined the effects of exercise training with a low (LoGIx)- or high (HiGIx)-glycemic index diet on the severity of the metabolic syndrome (Z-score)....

  17. Investigating the safety and efficacy of naltrexone for anti-psychotic induced weight gain in severe mental illness: study protocol of a double-blind, randomized, placebo-controlled trial.

    Science.gov (United States)

    Tek, Cenk; Guloksuz, Sinan; Srihari, Vinod H; Reutenauer, Erin L

    2013-06-27

    Obesity is a growing health problem leading to high rates of mortality and morbidity in patients with severe mental illness (SMI). The increased rate of obesity is largely attributed to antipsychotic use. The effect of antipsychotic medications on H1 and 5HT2 receptors has been associated with weight gain, but there is also a substantial amount of evidence showing that D2 receptor blockade may be responsible for weight gain by interacting with the dopamine-opioid system. Unfortunately, current available medications for weight loss have limited efficacy in this population. Naltrexone, an opioid receptor antagonist, may be a promising agent to reduce antipsychotic induced weight gain by decreasing food cravings. We aim to investigate the safety and efficacy of two doses of naltrexone (25 mg & 50 mg) versus placebo for weight and health risk reduction in overweight and obese individuals (BMI ≥ 28) with SMI, who gained weight while being treated with antipsychotics. One hundred and forty four patients will be recruited throughout the greater New Haven area. The participants will be randomized to naltrexone 25 mg/day, naltrexone 50 mg/day, or placebo in a 1:1:1 ratio. Participants will be on the study medication for 52 weeks, and assessed weekly for the first 4 weeks and bi-weekly thereafter. The primary outcome measurements are weight reduction and percentage achieving clinically significant weight loss (5% of total body weight). Waist circumference, body mass index, serum lipid profile, fasting glucose, and glycosylated hemoglobin are the secondary outcome measures. The effect of naltrexone on other outcome measurements such as schizophrenia symptoms, depression, dietary consumption, quality of life, cognitive functioning, physical activity, metabolism/inflammation markers, serum leptin, ghrelin, peptide YY, adinopectin, high sensitivity CRP, interleukin 6, interleukin-1B, interleukin-18, and tumor necrosis factor alpha (TNF-α) will be evaluated. The data will be

  18. Intra- and interrater reliability of three different MRI grading and classification systems after acute hamstring injuries.

    Science.gov (United States)

    Wangensteen, Arnlaug; Tol, Johannes L; Roemer, Frank W; Bahr, Roald; Dijkstra, H Paul; Crema, Michel D; Farooq, Abdulaziz; Guermazi, Ali

    2017-04-01

    To assess and compare the intra- and interrater reliability of three different MRI grading and classification systems after acute hamstring injury. Male athletes (n=40) with clinical diagnosis of acute hamstring injury and MRI ≤5days were selected from a prospective cohort. Two radiologists independently evaluated the MRIs using standardised scoring form including the modified Peetrons grading system, the Chan acute muscle strain injury classification and the British Athletics Muscle Injury Classification. Intra-and interrater reliability was assessed with linear weighted kappa (κ) or unweighted Cohen's κ and percentage agreement was calculated. We observed 'substantial' to 'almost perfect' intra- (κ range 0.65-1.00) and interrater reliability (κ range 0.77-1.00) with percentage agreement 83-100% and 88-100%, respectively, for severity gradings, overall anatomical sites and overall classifications for the three MRI systems. We observed substantial variability (κ range -0.05 to 1.00) for subcategories within the Chan classification and the British Athletics Muscle Injury Classification, however, the prevalence of positive scorings was low for some subcategories. The modified Peetrons grading system, overall Chan classification and overall British Athletics Muscle Injury Classification demonstrated 'substantial' to 'almost perfect' intra- and interrater reliability when scored by experienced radiologists. The intra- and interrater reliability for the anatomical subcategories within the classifications remains unclear. Copyright © 2017 Elsevier B.V. All rights reserved.

  19. Latent class models for classification

    NARCIS (Netherlands)

    Vermunt, J.K.; Magidson, J.

    2003-01-01

    An overview is provided of recent developments in the use of latent class (LC) and other types of finite mixture models for classification purposes. Several extensions of existing models are presented. Two basic types of LC models for classification are defined: supervised and unsupervised

  20. A supervised learning rule for classification of spatiotemporal spike patterns.

    Science.gov (United States)

    Lilin Guo; Zhenzhong Wang; Adjouadi, Malek

    2016-08-01

    This study introduces a novel supervised algorithm for spiking neurons that take into consideration synapse delays and axonal delays associated with weights. It can be utilized for both classification and association and uses several biologically influenced properties, such as axonal and synaptic delays. This algorithm also takes into consideration spike-timing-dependent plasticity as in Remote Supervised Method (ReSuMe). This paper focuses on the classification aspect alone. Spiked neurons trained according to this proposed learning rule are capable of classifying different categories by the associated sequences of precisely timed spikes. Simulation results have shown that the proposed learning method greatly improves classification accuracy when compared to the Spike Pattern Association Neuron (SPAN) and the Tempotron learning rule.

  1. High-molecular-weight adiponectin is selectively reduced in women with polycystic ovary syndrome independent of body mass index and severity of insulin resistance.

    LENUS (Irish Health Repository)

    O'Connor, A

    2010-03-01

    Context: High-molecular-weight (HMW) adiponectin contributes to insulin resistance (IR), which is closely associated with the pathophysiology of polycystic ovary syndrome (PCOS). Abnormalities in adipocyte function have been identified in PCOS and potentially contribute to lower adiponectin concentrations. Objective: Our objective was to determine which variables in plasma and adipose tissue influence HMW adiponectin in a well characterized cohort of women with PCOS. Design: This was a cross-sectional study. Settings and Participants: A teaching hospital. Women with PCOS (n = 98) and body mass index (BMI)-matched controls (n = 103) (including 68 age-, BMI-, and IR-matched pairs). Interventions: A standard 75-g oral glucose tolerance test was performed for each participant. Subcutaneous adipose tissue samples were taken by needle biopsy for a subset of PCOS women (n = 9) and controls (n = 8). Main Outcome Measures: Serum levels of HMW adiponectin and their relation to indices of insulin sensitivity, body composition, and circulating androgens as well as adipose tissue expression levels of ADIPOQ, TNFalpha, PPARgamma, and AR were assessed. Results: HMW adiponectin was significantly lower in women with PCOS compared with both BMI- and BMI- and IR-matched controls (P = 0.009 and P = 0.027, respectively). Although BMI and IR were the main predictors of HMW adiponectin, an interaction between waist to hip ratio and plasma testosterone contributed to its variance (P = 0.026). Adipose tissue gene expression analysis demonstrated that AR and TNFalpha (P = 0.008 and P = 0.035, respectively) but not ADIPOQ mRNA levels were increased in PCOS compared with controls. Conclusions: HMW adiponectin is selectively reduced in women with PCOS, independent of BMI and IR. Gene expression analysis suggests that posttranscriptional\\/translational modification contributes to reduced HMW adiponectin in PCOS.

  2. Gait pattern of severely disabled hemiparetic subjects on a new controlled gait trainer as compared to assisted treadmill walking with partial body weight support.

    Science.gov (United States)

    Hesse, S; Uhlenbrock, D; Sarkodie-Gyan, T

    1999-10-01

    To investigate to what extent and with how much therapeutic effort nonambulatory stroke patients could train a gait-like movement on a newly developed, machine-supported gait trainer. Open study comparing the movement on the gait trainer with assisted walking on the treadmill. Motion analysis laboratory of a rehabilitation centre. Fourteen chronic, nonambulatory hemiparetic patients. Complex gait analysis while training on the gait trainer and while walking on the treadmill. Gait kinematics, kinesiological EMG of several lower limb muscles and the required assistance. Patients could train a gait-like movement on the gait trainer, characterized kinematically by a perfect symmetry, larger hip extension during stance, less knee flexion and less ankle plantar flexion during swing as compared to treadmill walking (p gait trainer (p gait trainer offered severely disabled hemiparetic subjects the possibility of training a gait-like, highly symmetrical movement with a favourable facilitation of relevant anti-gravity muscles. At the same time, the effort required of the therapists was reduced.

  3. Acoustic classification of dwellings

    DEFF Research Database (Denmark)

    Berardi, Umberto; Rasmussen, Birgit

    2014-01-01

    insulation performance, national schemes for sound classification of dwellings have been developed in several European countries. These schemes define acoustic classes according to different levels of sound insulation. Due to the lack of coordination among countries, a significant diversity in terms...... exchanging experiences about constructions fulfilling different classes, reducing trade barriers, and finally increasing the sound insulation of dwellings.......Schemes for the classification of dwellings according to different building performances have been proposed in the last years worldwide. The general idea behind these schemes relates to the positive impact a higher label, and thus a better performance, should have. In particular, focusing on sound...

  4. Tissue Classification

    DEFF Research Database (Denmark)

    Van Leemput, Koen; Puonti, Oula

    2015-01-01

    Computational methods for automatically segmenting magnetic resonance images of the brain have seen tremendous advances in recent years. So-called tissue classification techniques, aimed at extracting the three main brain tissue classes (white matter, gray matter, and cerebrospinal fluid), are now...... well established. In their simplest form, these methods classify voxels independently based on their intensity alone, although much more sophisticated models are typically used in practice. This article aims to give an overview of often-used computational techniques for brain tissue classification...

  5. Transporter Classification Database (TCDB)

    Data.gov (United States)

    U.S. Department of Health & Human Services — The Transporter Classification Database details a comprehensive classification system for membrane transport proteins known as the Transporter Classification (TC)...

  6. MRI interrReader and intra-reader reliabilities for assessing injury morphology and posterior ligamentous complex integrity of the spine according to the thoracolumbar injury classification system and severity score

    International Nuclear Information System (INIS)

    Lee, Guen Young; Lee, Joon Woo; Choi, Seung Woo; Lim, Hyun Jin; Sun, Hye Young; Kang, Yu Suhn; Kang, Heung Sik; Chai, Jee Won; Kim, Su Jin

    2015-01-01

    To evaluate spine magnetic resonance imaging (MRI) inter-reader and intra-reader reliabilities using the thoracolumbar injury classification system and severity score (TLICS) and to analyze the effects of reader experience on reliability and the possible reasons for discordant interpretations. Six radiologists (two senior, two junior radiologists, and two residents) independently scored 100 MRI examinations of thoracolumbar spine injuries to assess injury morphology and posterior ligamentous complex (PLC) integrity according to the TLICS. Inter-reader and intra-reader agreements were determined and analyzed according to the number of years of radiologist experience. Inter-reader agreement between the six readers was moderate (k = 0.538 for the first and 0.537 for the second review) for injury morphology and fair to moderate (k = 0.440 for the first and 0.389 for the second review) for PLC integrity. No significant difference in inter-reader agreement was observed according to the number of years of radiologist experience. Intra-reader agreements showed a wide range (k = 0.538-0.822 for injury morphology and 0.423-0.616 for PLC integrity). Agreement was achieved in 44 for the first and 45 for the second review about injury morphology, as well as in 41 for the first and 38 for the second review of PLC integrity. A positive correlation was detected between injury morphology score and PLC integrity. The reliability of MRI for assessing thoracolumbar spinal injuries according to the TLICS was moderate for injury morphology and fair to moderate for PLC integrity, which may not be influenced by radiologist' experience

  7. Intra- and interrater reliability of three different MRI grading and classification systems after acute hamstring injuries

    International Nuclear Information System (INIS)

    Wangensteen, Arnlaug; Tol, Johannes L.; Roemer, Frank W.; Bahr, Roald; Dijkstra, H. Paul; Crema, Michel D.; Farooq, Abdulaziz; Guermazi, Ali

    2017-01-01

    Highlights: • Three different MRI grading and classification systems for acute hamstring injuries are overall reliable. • Reliability for the subcategories within these MRI grading and classification systems remains, however, unclear. - Abstract: Objective: To assess and compare the intra- and interrater reliability of three different MRI grading and classification systems after acute hamstring injury. Methods: Male athletes (n = 40) with clinical diagnosis of acute hamstring injury and MRI ≤5 days were selected from a prospective cohort. Two radiologists independently evaluated the MRIs using standardised scoring form including the modified Peetrons grading system, the Chan acute muscle strain injury classification and the British Athletics Muscle Injury Classification. Intra-and interrater reliability was assessed with linear weighted kappa (κ) or unweighted Cohen's κ and percentage agreement was calculated. Results: We observed ‘substantial’ to ‘almost perfect’ intra- (κ range 0.65–1.00) and interrater reliability (κ range 0.77–1.00) with percentage agreement 83–100% and 88–100%, respectively, for severity gradings, overall anatomical sites and overall classifications for the three MRI systems. We observed substantial variability (κ range −0.05 to 1.00) for subcategories within the Chan classification and the British Athletics Muscle Injury Classification, however, the prevalence of positive scorings was low for some subcategories. Conclusions: The modified Peetrons grading system, overall Chan classification and overall British Athletics Muscle Injury Classification demonstrated ‘substantial' to ‘almost perfect' intra- and interrater reliability when scored by experienced radiologists. The intra- and interrater reliability for the anatomical subcategories within the classifications remains unclear.

  8. Intra- and interrater reliability of three different MRI grading and classification systems after acute hamstring injuries

    Energy Technology Data Exchange (ETDEWEB)

    Wangensteen, Arnlaug, E-mail: arnlaug.wangensteen@nih.no [Aspetar, Orthopaedic and Sports Medicine Hospital, Doha (Qatar); Oslo Sports Trauma Research Center, Department of Sports Medicine, Norwegian School of Sport Sciences, Oslo (Norway); Tol, Johannes L., E-mail: johannes.tol@aspetar.com [Aspetar, Orthopaedic and Sports Medicine Hospital, Doha (Qatar); Amsterdam Center for Evidence Sports Medicine, Academic Medical Center (Netherlands); The Sports Physician Group, OLVG, Amsterdam (Netherlands); Roemer, Frank W. [Quantitative Imaging Center, Department of Radiology, Boston University School of Medicine, Boston, MA (United States); Department of Radiology, University of Erlangen-Nuremberg, Erlangen (Germany); Bahr, Roald [Aspetar, Orthopaedic and Sports Medicine Hospital, Doha (Qatar); Oslo Sports Trauma Research Center, Department of Sports Medicine, Norwegian School of Sport Sciences, Oslo (Norway); Dijkstra, H. Paul [Aspetar, Orthopaedic and Sports Medicine Hospital, Doha (Qatar); Crema, Michel D. [Quantitative Imaging Center, Department of Radiology, Boston University School of Medicine, Boston, MA (United States); Department of Radiology, Saint-Antoine Hospital, University Paris VI, Paris (France); Farooq, Abdulaziz [Aspetar, Orthopaedic and Sports Medicine Hospital, Doha (Qatar); Guermazi, Ali [Quantitative Imaging Center, Department of Radiology, Boston University School of Medicine, Boston, MA (United States)

    2017-04-15

    Highlights: • Three different MRI grading and classification systems for acute hamstring injuries are overall reliable. • Reliability for the subcategories within these MRI grading and classification systems remains, however, unclear. - Abstract: Objective: To assess and compare the intra- and interrater reliability of three different MRI grading and classification systems after acute hamstring injury. Methods: Male athletes (n = 40) with clinical diagnosis of acute hamstring injury and MRI ≤5 days were selected from a prospective cohort. Two radiologists independently evaluated the MRIs using standardised scoring form including the modified Peetrons grading system, the Chan acute muscle strain injury classification and the British Athletics Muscle Injury Classification. Intra-and interrater reliability was assessed with linear weighted kappa (κ) or unweighted Cohen's κ and percentage agreement was calculated. Results: We observed ‘substantial’ to ‘almost perfect’ intra- (κ range 0.65–1.00) and interrater reliability (κ range 0.77–1.00) with percentage agreement 83–100% and 88–100%, respectively, for severity gradings, overall anatomical sites and overall classifications for the three MRI systems. We observed substantial variability (κ range −0.05 to 1.00) for subcategories within the Chan classification and the British Athletics Muscle Injury Classification, however, the prevalence of positive scorings was low for some subcategories. Conclusions: The modified Peetrons grading system, overall Chan classification and overall British Athletics Muscle Injury Classification demonstrated ‘substantial' to ‘almost perfect' intra- and interrater reliability when scored by experienced radiologists. The intra- and interrater reliability for the anatomical subcategories within the classifications remains unclear.

  9. Vietnamese Document Representation and Classification

    Science.gov (United States)

    Nguyen, Giang-Son; Gao, Xiaoying; Andreae, Peter

    Vietnamese is very different from English and little research has been done on Vietnamese document classification, or indeed, on any kind of Vietnamese language processing, and only a few small corpora are available for research. We created a large Vietnamese text corpus with about 18000 documents, and manually classified them based on different criteria such as topics and styles, giving several classification tasks of different difficulty levels. This paper introduces a new syllable-based document representation at the morphological level of the language for efficient classification. We tested the representation on our corpus with different classification tasks using six classification algorithms and two feature selection techniques. Our experiments show that the new representation is effective for Vietnamese categorization, and suggest that best performance can be achieved using syllable-pair document representation, an SVM with a polynomial kernel as the learning algorithm, and using Information gain and an external dictionary for feature selection.

  10. Micronutrient Supplementation, Dietary Intervention and Resulting Body Weight Gain of Severe Acute Malnourished Children – A Pilot Project Study of OJUS Medical Institute with Existing ICDS Project in Nasik District, Maharashtra

    Directory of Open Access Journals (Sweden)

    Subhasree Ray

    2014-12-01

    Full Text Available Introduction: OJUS Medical Institute in collaboration with Women & Child development department of Nashik District, Maharashtra conducted a target oriented pilot project study to see the improvement in body weight gain of SAM children, supplemented with nutritionally enriched diet and micronutrients. The Egg-DOT project is a target vertical intervention study that involved both Anganwadi workers and Community health workers to bring a fruitful result by working hand-in-hand. Rationale: ICDS is one of the best supplementary nutrition programs to address and eliminate malnutrition from the country. To make it more comprehensive and result oriented the pilot project study is formulated and executed to see if the addition in existing system could eradicate malnutrition in an effective manner and strengthen the Govt. health machinery. Objective: The study aimed at working along with the Govt. to reduce severity of malnutrition. It shouted for a healthy public-private relationship to bring optimum result from the existing Govt. project in reducing burden of malnutrition, spreading health education and behavioural modification in the community members by adopting a systematic micronutrient-diet-health education  intervention strategy. Materials & methods: Along with existing nutritional intervention, a small modification in diet is introduced to fulfill the deficit of 300 Kcal approximately. Good quality fat and protein are added to the Anganwadi meal with daily micronutrient supplementation. The supplementation is continued for 30 days in 25 SAM children of 3 to 5 years. The baseline and end line body weight measurements are taken and compared to see the improvement. Result: After 30 days of intervention the supplemented SAM children showed statistically significant increased body weight (P<0.01 with an overall healthy nutritional status. Conclusion: The study showed that public-private collaborative systematic strategy with proper

  11. Weighted Clustering

    DEFF Research Database (Denmark)

    Ackerman, Margareta; Ben-David, Shai; Branzei, Simina

    2012-01-01

    We investigate a natural generalization of the classical clustering problem, considering clustering tasks in which different instances may have different weights.We conduct the first extensive theoretical analysis on the influence of weighted data on standard clustering algorithms in both...... the partitional and hierarchical settings, characterizing the conditions under which algorithms react to weights. Extending a recent framework for clustering algorithm selection, we propose intuitive properties that would allow users to choose between clustering algorithms in the weighted setting and classify...

  12. Chinese parents' perceptions of their children's weights and their relationship to parenting behaviours.

    Science.gov (United States)

    Wen, X; Hui, S S C

    2011-05-01

    The purpose of this study is to examine Chinese parents' perceptions of their children's weights and explore the parenting behaviours associated with these perceptions. A total of 2143 adolescents and 1869 parents were recruited from secondary schools in Ganzhou and Shantou in China. The adolescents' actual weights and heights were measured by trained testers. The self-reported parents' weights and heights, parental perception of the adolescents' weights, adolescents' perception of their own weights, parenting behaviours and demographic information were collected through the questionnaires distributed to the respondents. The results based on Kappa statistics show only a slight agreement between parental perception of their children's weights and the adolescents' actual weights (Kappa = 0.221). The results from the logistic regression show that the parents' gender [odds ratio (OR) = 0.80, 95% confidence interval (CI): 0.64-1.00], adolescents' gender (OR = 1.61, 95% CI: 1.29-2.01) and perception of their own weights (OR = 0.30, 95% CI: 0.24-0.38) are associated with the parents' perception of their children's weights. Statistically significant difference in several parenting behaviours was found between the parents with correct and incorrect perceptions of their children's weight. Misconceptions about their children's weights are prevalent among Chinese parents. The association between parents' perception of their children's weight and parenting behaviours suggests that the accurate classification of children's weights could help prevent childhood obesity. © 2010 Blackwell Publishing Ltd.

  13. Classification in context

    DEFF Research Database (Denmark)

    Mai, Jens Erik

    2004-01-01

    This paper surveys classification research literature, discusses various classification theories, and shows that the focus has traditionally been on establishing a scientific foundation for classification research. This paper argues that a shift has taken place, and suggests that contemporary...... classification research focus on contextual information as the guide for the design and construction of classification schemes....

  14. Classification of the web

    DEFF Research Database (Denmark)

    Mai, Jens Erik

    2004-01-01

    This paper discusses the challenges faced by investigations into the classification of the Web and outlines inquiries that are needed to use principles for bibliographic classification to construct classifications of the Web. This paper suggests that the classification of the Web meets challenges...... that call for inquiries into the theoretical foundation of bibliographic classification theory....

  15. Fuzzy One-Class Classification Model Using Contamination Neighborhoods

    Directory of Open Access Journals (Sweden)

    Lev V. Utkin

    2012-01-01

    Full Text Available A fuzzy classification model is studied in the paper. It is based on the contaminated (robust model which produces fuzzy expected risk measures characterizing classification errors. Optimal classification parameters of the models are derived by minimizing the fuzzy expected risk. It is shown that an algorithm for computing the classification parameters is reduced to a set of standard support vector machine tasks with weighted data points. Experimental results with synthetic data illustrate the proposed fuzzy model.

  16. Comparison of liraglutide plus basal insulin and basal-bolus insulin therapy (BBIT) for glycemic control, body weight stability, and treatment satisfaction in patients treated using BBIT for type 2 diabetes without severe insulin deficiency: A randomized prospective pilot study.

    Science.gov (United States)

    Yamamoto, Saki; Hayashi, Toshiyuki; Ohara, Makoto; Goto, Satoshi; Sato, Jun; Nagaike, Hiroe; Fukase, Ayako; Sato, Nobuko; Hiromura, Munenori; Tomoyasu, Masako; Nakanishi, Noriko; Lee, Soushou; Osamura, Anna; Yamamoto, Takeshi; Fukui, Tomoyasu; Hirano, Tsutomu

    2018-03-26

    We examined whether 0.9 mg/day liraglutide plus basal insulin (Lira-basal) is superior to basal-bolus insulin therapy (BBIT) for type 2 diabetes (T2DM) without severe insulin deficiency as determined by glucagon stimulation. Fifty patients receiving BBIT were enrolled in this 24-week, prospective, randomized, open-labeled study. After excluding subjects with fasting C-peptide immunoreactivity (CPR) basal (n = 12) or continued BBIT (n = 13). Primary endpoint was change in HbA1c. Secondary endpoints were changes in body weight (BW), 7-point self-monitored blood glucose (SMBG), and Diabetes Treatment Satisfaction Questionnaire status (DTSQs) scores. The Lira-basal group demonstrated reduced HbA1c, whereas the BBIT group showed no change. BW was reduced in the Lira-basal group but increased in the BBIT group. The Lira-basal group also exhibited significantly reduced pre-breakfast and pre-lunch SMBG. DTSQs scores improved in the Lira-basal group but not the BBIT group. Plasma lipids, liver function, and kidney function were not significantly changed in either group. Lira-basal therapy is superior to BBIT for T2DM without severe insulin deficiency. This study was registered with UMIN Clinical Trials Registry (UMIN000028313). Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

  17. AN ADABOOST OPTIMIZED CCFIS BASED CLASSIFICATION MODEL FOR BREAST CANCER DETECTION

    Directory of Open Access Journals (Sweden)

    CHANDRASEKAR RAVI

    2017-06-01

    Full Text Available Classification is a Data Mining technique used for building a prototype of the data behaviour, using which an unseen data can be classified into one of the defined classes. Several researchers have proposed classification techniques but most of them did not emphasis much on the misclassified instances and storage space. In this paper, a classification model is proposed that takes into account the misclassified instances and storage space. The classification model is efficiently developed using a tree structure for reducing the storage complexity and uses single scan of the dataset. During the training phase, Class-based Closed Frequent ItemSets (CCFIS were mined from the training dataset in the form of a tree structure. The classification model has been developed using the CCFIS and a similarity measure based on Longest Common Subsequence (LCS. Further, the Particle Swarm Optimization algorithm is applied on the generated CCFIS, which assigns weights to the itemsets and their associated classes. Most of the classifiers are correctly classifying the common instances but they misclassify the rare instances. In view of that, AdaBoost algorithm has been used to boost the weights of the misclassified instances in the previous round so as to include them in the training phase to classify the rare instances. This improves the accuracy of the classification model. During the testing phase, the classification model is used to classify the instances of the test dataset. Breast Cancer dataset from UCI repository is used for experiment. Experimental analysis shows that the accuracy of the proposed classification model outperforms the PSOAdaBoost-Sequence classifier by 7% superior to other approaches like Naïve Bayes Classifier, Support Vector Machine Classifier, Instance Based Classifier, ID3 Classifier, J48 Classifier, etc.

  18. Fitness Tracker for Weight Lifting Style Workouts

    Energy Technology Data Exchange (ETDEWEB)

    Wihl, B. M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)

    2017-02-01

    This document proposes an early, high level design for a fitness tracking system which can automatically log weight lifting style workouts. The system will provide an easy to use interface both physically through the use of several wireless wristband style motion trackers worn on the limbs, and graphically through a smartphone application. Exercise classification will be accomplished by calibration of the user’s specific motions. The system will accurately track a user’s workout, miscounting no more than one repetition in every 20, have sufficient battery life to last several hours, work with existing smartphones and have a cost similar to those of current fitness tracking devices. This document presents the mission background, current state-of-theart, stakeholders and their expectations, the proposed system’s context and concepts, implementation concepts, system requirements, first sublevel function decomposition, possible risks for the system, and a reflection on the design process.

  19. Hazard classification methodology

    International Nuclear Information System (INIS)

    Brereton, S.J.

    1996-01-01

    This document outlines the hazard classification methodology used to determine the hazard classification of the NIF LTAB, OAB, and the support facilities on the basis of radionuclides and chemicals. The hazard classification determines the safety analysis requirements for a facility

  20. Concomitant preterm birth and severe small-for-gestational age birth weight among infants of immigrant mothers in Ontario originating from the Philippines and East Asia: a population-based study.

    Science.gov (United States)

    Bartsch, Emily; Park, Alison L; Jairam, Jennifer; Ray, Joel G

    2017-07-18

    Women from the Philippines form one of the largest immigrant groups to North America. Their newborns experience higher rates of preterm birth (PTB), and separately, small-for-gestational age (SGA) birth weight, compared with other East Asians. It is not known if Filipino women are at elevated risk of concomitant PTB and severe SGA (PTB-SGA), a pathological state likely reflective of placental dysfunction and neonatal morbidity. We conducted a population-based study of all singleton or twin live births in Ontario, from 2002 to 2011, among immigrant mothers from the Philippines (n=27 946), Vietnam (n=15 297), Hong Kong (n=5618), South Korea (n=5148) and China (n=42 517). We used modified Poisson regression to generate relative risks (RR) of PTB-SGA, defined as a birth gestation and a birth weight mothers from China (2.3 per 1000), the rate of PTB-SGA was significantly higher among infants of mothers from the Philippines (6.5 per 1000; RR 2.91, 95% CI 2.27 to 3.73), and those from Vietnam (3.7 per 1000; RR 1.68, 95% CI 1.21 to 2.34). The RR of PTB-SGA was not higher for infants of mothers from Hong Kong or South Korea. Among infants born to immigrant women from five East Asian birthplaces, the risk of PTB-SGA was highest among those from the Philippines. These women and their fetuses may require additional monitoring and interventions. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

  1. Neuromuscular disease classification system

    Science.gov (United States)

    Sáez, Aurora; Acha, Begoña; Montero-Sánchez, Adoración; Rivas, Eloy; Escudero, Luis M.; Serrano, Carmen

    2013-06-01

    Diagnosis of neuromuscular diseases is based on subjective visual assessment of biopsies from patients by the pathologist specialist. A system for objective analysis and classification of muscular dystrophies and neurogenic atrophies through muscle biopsy images of fluorescence microscopy is presented. The procedure starts with an accurate segmentation of the muscle fibers using mathematical morphology and a watershed transform. A feature extraction step is carried out in two parts: 24 features that pathologists take into account to diagnose the diseases and 58 structural features that the human eye cannot see, based on the assumption that the biopsy is considered as a graph, where the nodes are represented by each fiber, and two nodes are connected if two fibers are adjacent. A feature selection using sequential forward selection and sequential backward selection methods, a classification using a Fuzzy ARTMAP neural network, and a study of grading the severity are performed on these two sets of features. A database consisting of 91 images was used: 71 images for the training step and 20 as the test. A classification error of 0% was obtained. It is concluded that the addition of features undetectable by the human visual inspection improves the categorization of atrophic patterns.

  2. Attribute Weighting Based K-Nearest Neighbor Using Gain Ratio

    Science.gov (United States)

    Nababan, A. A.; Sitompul, O. S.; Tulus

    2018-04-01

    K- Nearest Neighbor (KNN) is a good classifier, but from several studies, the result performance accuracy of KNN still lower than other methods. One of the causes of the low accuracy produced, because each attribute has the same effect on the classification process, while some less relevant characteristics lead to miss-classification of the class assignment for new data. In this research, we proposed Attribute Weighting Based K-Nearest Neighbor Using Gain Ratio as a parameter to see the correlation between each attribute in the data and the Gain Ratio also will be used as the basis for weighting each attribute of the dataset. The accuracy of results is compared to the accuracy acquired from the original KNN method using 10-fold Cross-Validation with several datasets from the UCI Machine Learning repository and KEEL-Dataset Repository, such as abalone, glass identification, haberman, hayes-roth and water quality status. Based on the result of the test, the proposed method was able to increase the classification accuracy of KNN, where the highest difference of accuracy obtained hayes-roth dataset is worth 12.73%, and the lowest difference of accuracy obtained in the abalone dataset of 0.07%. The average result of the accuracy of all dataset increases the accuracy by 5.33%.

  3. Gender classification under extended operating conditions

    Science.gov (United States)

    Rude, Howard N.; Rizki, Mateen

    2014-06-01

    Gender classification is a critical component of a robust image security system. Many techniques exist to perform gender classification using facial features. In contrast, this paper explores gender classification using body features extracted from clothed subjects. Several of the most effective types of features for gender classification identified in literature were implemented and applied to the newly developed Seasonal Weather And Gender (SWAG) dataset. SWAG contains video clips of approximately 2000 samples of human subjects captured over a period of several months. The subjects are wearing casual business attire and outer garments appropriate for the specific weather conditions observed in the Midwest. The results from a series of experiments are presented that compare the classification accuracy of systems that incorporate various types and combinations of features applied to multiple looks at subjects at different image resolutions to determine a baseline performance for gender classification.

  4. Classification of IRAS asteroids

    International Nuclear Information System (INIS)

    Tedesco, E.F.; Matson, D.L.; Veeder, G.J.

    1989-01-01

    Albedos and spectral reflectances are essential for classifying asteroids. For example, classes E, M and P are indistinguishable without albedo data. Colorometric data are available for about 1000 asteroids but, prior to IRAS, albedo data was available for only about 200. IRAS broke this bottleneck by providing albedo data on nearly 2000 asteroids. Hence, excepting absolute magnitudes, the albedo and size are now the most common asteroid physical parameters known. In this chapter the authors present the results of analyses of IRAS-derived asteroid albedos, discuss their application to asteroid classification, and mention several studies which might be done to exploit further this data set

  5. Discussion on the safety classification of nuclear safety mechanical equipment

    International Nuclear Information System (INIS)

    Shen Wei

    2010-01-01

    The purpose and definition of the equipment safety classification in nuclear plant are introduced. The differences of several safety classification criterions are compared, and the object of safety classification is determined. According to the regulation, the definition and category of the safety functions are represented. The safety classification method, safety classification process, safety class interface, and the requirement for the safety class mechanical equipment are explored. At last, the relation of the safety classification between the mechanical and electrical equipment is presented, and the relation of the safety classification between mechanical equipment and system is also presented. (author)

  6. [The influence of previous pregnancy terminations, miscarriages and still-births on the incidence of babies with low birth weight and premature births as well as a somatic classification of newborns].

    Science.gov (United States)

    Voigt, M; Olbertz, D; Fusch, C; Krafczyk, D; Briese, V; Schneider, K T M

    2008-02-01

    The influence of previous interruptions, miscarriages and IUFD on the IUGR and preterm rate as well as on the somatic staging (gestational age and birth weight) of the new born is a subject of controversial discussion in the literature. The present paper attempts to quantify these risks of the medical history. 2 282 412 singleton pregnancies of the period 1995 to 2000 were evaluated from the German Perinatal Database. For the analysis 1 065 202 pregnancies (46.7 %) of those mothers without any live birth in the medical history were assessed. To exclude any influence from previous abortions patients with previous miscarriages and IUFDs were excluded. The control collective were new borns whose mothers had suffered neither from miscarriages nor from abortions or IUFD. Previous interruptions, miscarriages and IUFD influence the rate of new borns with low birth weight and increase the rate of prematurity. With increasing numbers of isolated or combined risks in the medical history, the rate of newborns with a low birth weight or with prematurity is increased. The lowest risk was found after one interruption, the highest rate with two or more IUFDs. Interruptions, miscarriages or IUFD are not risk factors for IUGR or SGA. Previous interruptions, miscarriages and IUFD are relevant risk factors for prematurity and are related with low birth weight of the new borns. Pregnant women with such risk factors have to been considered as risk pregnancies and need intensive surveillance.

  7. Interpreting weightings of the peer assessment rating index and the discrepancy index across contexts on Chinese patients.

    Science.gov (United States)

    Liu, Siqi; Oh, Heesoo; Chambers, David William; Xu, Tianmin; Baumrind, Sheldon

    2018-04-06

    Determine optimal weightings of Peer Assessment Rating (PAR) index and Discrepancy Index (DI) for malocclusion severity assessment in Chinese orthodontic patients. Sixty-nine Chinese orthodontists assessed a full set of pre-treatment records from a stratified random sample of 120 subjects gathered from six university orthodontic centres. Using professional judgment as the outcome variable, multiple regression analyses were performed to derive customized weighting systems for the PAR index and DI, for all subjects and each Angle classification subgroup. Professional judgment was consistent, with an Intraclass Correlation Coefficient (ICC) of 0.995. The PAR index or DI can be reliably measured, with ICC = 0.959 and 0.990, respectively. The predictive accuracy of PAR index was greatly improved by the Chinese weighting process (from r = 0.431 to r = 0.788) with almost equal distribution in each Angle classification subgroup. The Chinese-weighted DI showed a higher predictive accuracy, at P = 0.01, compared with the PAR index (r = 0.851 versus r = 0.788). A better performance was found in the Class II group (r = 0.890) when compared to Class I (r = 0.736) and III (r = 0.785) groups. The Chinese-weighted PAR index and DI were capable of predicting 62 per cent and 73 per cent of total variance in the professional judgment of malocclusion severity in Chinese patients. Differential prediction across Angle classifications merits attention since different weighting formulas were found.

  8. Mild, moderate, meaningful? Examining the psychological and functioning correlates of DSM-5 eating disorder severity specifiers.

    Science.gov (United States)

    Gianini, Loren; Roberto, Christina A; Attia, Evelyn; Walsh, B Timothy; Thomas, Jennifer J; Eddy, Kamryn T; Grilo, Carlos M; Weigel, Thomas; Sysko, Robyn

    2017-08-01

    This study evaluated the DSM-5 severity specifiers for treatment-seeking groups of participants with anorexia nervosa (AN), the purging form of bulimia nervosa (BN), and binge-eating disorder (BED). Hundred and sixty-two participants with AN, 93 participants with BN, and 343 participants with BED were diagnosed using semi-structured interviews, sub-categorized using DSM-5 severity specifiers and compared on demographic and cross-sectional clinical measures. In AN, the number of previous hospitalizations and the duration of illness increased with severity, but there was no difference across severity groups on measures of eating pathology, depression, or measures of self-reported physical or emotional functioning. In BN, the level of eating concerns increased across the severity groups, but the groups did not differ on measures of depression, self-esteem, and most eating pathology variables. In BN, support was also found for an alternative severity classification scheme based upon number of methods of purging. In BED, levels of several measures of eating pathology and self-reported physical and emotional functioning increased across the severity groups. For BED, however, support was also found for an alternative severity classification scheme based upon overvaluation of shape and weight. Preliminary evidence was also found for a transdiagnostic severity index based upon overvaluation of shape and weight. Overall, these data show limited support for the DSM-5 severity specifiers for BN and modest support for the DSM-5 severity specifiers for AN and BED. © 2017 Wiley Periodicals, Inc.

  9. Weighted statistical parameters for irregularly sampled time series

    Science.gov (United States)

    Rimoldini, Lorenzo

    2014-01-01

    Unevenly spaced time series are common in astronomy because of the day-night cycle, weather conditions, dependence on the source position in the sky, allocated telescope time and corrupt measurements, for example, or inherent to the scanning law of satellites like Hipparcos and the forthcoming Gaia. Irregular sampling often causes clumps of measurements and gaps with no data which can severely disrupt the values of estimators. This paper aims at improving the accuracy of common statistical parameters when linear interpolation (in time or phase) can be considered an acceptable approximation of a deterministic signal. A pragmatic solution is formulated in terms of a simple weighting scheme, adapting to the sampling density and noise level, applicable to large data volumes at minimal computational cost. Tests on time series from the Hipparcos periodic catalogue led to significant improvements in the overall accuracy and precision of the estimators with respect to the unweighted counterparts and those weighted by inverse-squared uncertainties. Automated classification procedures employing statistical parameters weighted by the suggested scheme confirmed the benefits of the improved input attributes. The classification of eclipsing binaries, Mira, RR Lyrae, Delta Cephei and Alpha2 Canum Venaticorum stars employing exclusively weighted descriptive statistics achieved an overall accuracy of 92 per cent, about 6 per cent higher than with unweighted estimators.

  10. The Brain and Spinal Injury Center score: a novel, simple, and reproducible method for assessing the severity of acute cervical spinal cord injury with axial T2-weighted MRI findings.

    Science.gov (United States)

    Talbott, Jason F; Whetstone, William D; Readdy, William J; Ferguson, Adam R; Bresnahan, Jacqueline C; Saigal, Rajiv; Hawryluk, Gregory W J; Beattie, Michael S; Mabray, Marc C; Pan, Jonathan Z; Manley, Geoffrey T; Dhall, Sanjay S

    2015-10-01

    Previous studies that have evaluated the prognostic value of abnormal changes in signals on T2-weighted MRI scans of an injured spinal cord have focused on the longitudinal extent of this signal abnormality in the sagittal plane. Although the transverse extent of injury and the degree of spared spinal cord white matter have been shown to be important for predicting outcomes in preclinical animal models of spinal cord injury (SCI), surprisingly little is known about the prognostic value of altered T2 relaxivity in humans in the axial plane. The authors undertook a retrospective chart review of 60 patients who met the inclusion criteria of this study and presented to the authors' Level I trauma center with an acute blunt traumatic cervical SCI. Within 48 hours of admission, all patients underwent MRI examination, which included axial and sagittal T2 images. Neurological symptoms, evaluated with the grades according to the American Spinal Injury Association (ASIA) Impairment Scale (AIS), at the time of admission and at hospital discharge were correlated with MRI findings. Five distinct patterns of intramedullary spinal cord T2 signal abnormality were defined in the axial plane at the injury epicenter. These patterns were assigned ordinal values ranging from 0 to 4, referred to as the Brain and Spinal Injury Center (BASIC) scores, which encompassed the spectrum of SCI severity. The BASIC score strongly correlated with neurological symptoms at the time of both hospital admission and discharge. It also distinguished patients initially presenting with complete injury who improved by at least one AIS grade by the time of discharge from those whose injury did not improve. The authors' proposed score was rapid to apply and showed excellent interrater reliability. The authors describe a novel 5-point ordinal MRI score for classifying acute SCIs on the basis of axial T2-weighted imaging. The proposed BASIC score stratifies the SCIs according to the extent of transverse T2

  11. Optimal ABC inventory classification using interval programming

    NARCIS (Netherlands)

    Rezaei, J.; Salimi, N.

    2015-01-01

    Inventory classification is one of the most important activities in inventory management, whereby inventories are classified into three or more classes. Several inventory classifications have been proposed in the literature, almost all of which have two main shortcomings in common. That is, the

  12. Data Augmentation for Plant Classification

    NARCIS (Netherlands)

    Pawara, Pornntiwa; Okafor, Emmanuel; Schomaker, Lambertus; Wiering, Marco

    2017-01-01

    Data augmentation plays a crucial role in increasing the number of training images, which often aids to improve classification performances of deep learning techniques for computer vision problems. In this paper, we employ the deep learning framework and determine the effects of several

  13. The classification of the Ricci tensor in the general theory of relativity

    International Nuclear Information System (INIS)

    Cormack, W.J.

    1979-10-01

    A comprehensive classification of the Ricci tensor in General Relativity using several techniques is given and their connection with existing classification studied under the headings; canonical forms for the Ricci tensor, invariant 2-spaces in the classification of the Ricci tensor, Riemannian curvature and the classification of the Riemann and Ricci tensors, and spinor classifications of the Ricci tensor. (U.K.)

  14. Weight discrimination and bullying.

    Science.gov (United States)

    Puhl, Rebecca M; King, Kelly M

    2013-04-01

    Despite significant attention to the medical impacts of obesity, often ignored are the negative outcomes that obese children and adults experience as a result of stigma, bias, and discrimination. Obese individuals are frequently stigmatized because of their weight in many domains of daily life. Research spanning several decades has documented consistent weight bias and stigmatization in employment, health care, schools, the media, and interpersonal relationships. For overweight and obese youth, weight stigmatization translates into pervasive victimization, teasing, and bullying. Multiple adverse outcomes are associated with exposure to weight stigmatization, including depression, anxiety, low self-esteem, body dissatisfaction, suicidal ideation, poor academic performance, lower physical activity, maladaptive eating behaviors, and avoidance of health care. This review summarizes the nature and extent of weight stigmatization against overweight and obese individuals, as well as the resulting consequences that these experiences create for social, psychological, and physical health for children and adults who are targeted. Copyright © 2013 Elsevier Ltd. All rights reserved.

  15. Memristive Perceptron for Combinational Logic Classification

    Directory of Open Access Journals (Sweden)

    Lidan Wang

    2013-01-01

    Full Text Available The resistance of the memristor depends upon the past history of the input current or voltage; so it can function as synapse in neural networks. In this paper, a novel perceptron combined with the memristor is proposed to implement the combinational logic classification. The relationship between the memristive conductance change and the synapse weight update is deduced, and the memristive perceptron model and its synaptic weight update rule are explored. The feasibility of the novel memristive perceptron for implementing the combinational logic classification (NAND, NOR, XOR, and NXOR is confirmed by MATLAB simulation.

  16. SAW Classification Algorithm for Chinese Text Classification

    OpenAIRE

    Xiaoli Guo; Huiyu Sun; Tiehua Zhou; Ling Wang; Zhaoyang Qu; Jiannan Zang

    2015-01-01

    Considering the explosive growth of data, the increased amount of text data’s effect on the performance of text categorization forward the need for higher requirements, such that the existing classification method cannot be satisfied. Based on the study of existing text classification technology and semantics, this paper puts forward a kind of Chinese text classification oriented SAW (Structural Auxiliary Word) algorithm. The algorithm uses the special space effect of Chinese text where words...

  17. Weight Loss

    Science.gov (United States)

    ... Rights Employment Discrimination Health Care Professionals Law Enforcement Driver's License For Lawyers Food & Fitness Home Food MyFoodAdvisor ... Fit Types of Activity Weight Loss Assess Your Lifestyle Getting Started Food Choices In My Community Home ...

  18. Shellfish Feeding Experiments, Filter Weight and Tissue Weight

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Particulate matter removal by shellfish was quantified in several geographic locations, across several years. Data include filter and shellfish tissue weights.

  19. Effects of an in-patient treatment program based on regular exercise and a balanced diet on high molecular weight adiponectin, resistin levels, and insulin resistance in adolescents with severe obesity.

    Science.gov (United States)

    Gueugnon, Carine; Mougin, Fabienne; Simon-Rigaud, Marie-Laure; Regnard, Jacques; Nègre, Véronique; Dumoulin, Gilles

    2012-08-01

    Adiponectin, the most abundant hormone produced by adipose tissue, circulates in 3 isoforms, including high molecular weight (HMW) adiponectin. The latter has been suggested to be a better predictor of metabolic disturbances and insulin resistance associated with obesity. This study investigated changes in total and HMW adiponectin, resistin, and homeostasis model assessment (HOMA) during a 9-month in-patient treatment program based on physical exercise and a balanced diet in 32 severely obese adolescents. Total and HMW adiponectin, resistin, and HOMA were measured at baseline (month 0) and during the program (months 3, 6, 9). In addition, a control group of 15 teenagers served as a reference for the baseline assessments. At baseline, HMW adiponectin was more markedly decreased in obese adolescents than total adiponectin, and both were lower than in controls. Conversely, resistin and HOMA were higher in obese adolescents. During the program, there was a significant change in body composition and improved insulin sensitivity among obese teenagers. In addition, HMW adiponectin and the ratio of HMW-to-total adiponectin increased throughout the study, whereas total adiponectin only increased up until the sixth month. On the contrary, resistin did not show any significant change. In obese adolescents, a long-term combination of aerobic exercise and a balanced diet, inducing change in body composition and improved insulin sensitivity, markedly increased HMW adiponectin compared with total adiponectin, without any change in resistin concentrations. Our results thus suggest that the determination of HMW adiponectin could be more useful than measurement of total adiponectin in clinical settings.

  20. Support for linguistic macrofamilies from weighted sequence alignment

    Science.gov (United States)

    Jäger, Gerhard

    2015-01-01

    Computational phylogenetics is in the process of revolutionizing historical linguistics. Recent applications have shed new light on controversial issues, such as the location and time depth of language families and the dynamics of their spread. So far, these approaches have been limited to single-language families because they rely on a large body of expert cognacy judgments or grammatical classifications, which is currently unavailable for most language families. The present study pursues a different approach. Starting from raw phonetic transcription of core vocabulary items from very diverse languages, it applies weighted string alignment to track both phonetic and lexical change. Applied to a collection of ∼1,000 Eurasian languages and dialects, this method, combined with phylogenetic inference, leads to a classification in excellent agreement with established findings of historical linguistics. Furthermore, it provides strong statistical support for several putative macrofamilies contested in current historical linguistics. In particular, there is a solid signal for the Nostratic/Eurasiatic macrofamily. PMID:26403857

  1. Deep learning for image classification

    Science.gov (United States)

    McCoppin, Ryan; Rizki, Mateen

    2014-06-01

    This paper provides an overview of deep learning and introduces the several subfields of deep learning including a specific tutorial of convolutional neural networks. Traditional methods for learning image features are compared to deep learning techniques. In addition, we present our preliminary classification results, our basic implementation of a convolutional restricted Boltzmann machine on the Mixed National Institute of Standards and Technology database (MNIST), and we explain how to use deep learning networks to assist in our development of a robust gender classification system.

  2. Facial aging: A clinical classification

    Directory of Open Access Journals (Sweden)

    Shiffman Melvin

    2007-01-01

    Full Text Available The purpose of this classification of facial aging is to have a simple clinical method to determine the severity of the aging process in the face. This allows a quick estimate as to the types of procedures that the patient would need to have the best results. Procedures that are presently used for facial rejuvenation include laser, chemical peels, suture lifts, fillers, modified facelift and full facelift. The physician is already using his best judgment to determine which procedure would be best for any particular patient. This classification may help to refine these decisions.

  3. Object-Based Classification of Grasslands from High Resolution Satellite Image Time Series Using Gaussian Mean Map Kernels

    Directory of Open Access Journals (Sweden)

    Mailys Lopes

    2017-07-01

    Full Text Available This paper deals with the classification of grasslands using high resolution satellite image time series. Grasslands considered in this work are semi-natural elements in fragmented landscapes, i.e., they are heterogeneous and small elements. The first contribution of this study is to account for grassland heterogeneity while working at the object level by modeling its pixels distributions by a Gaussian distribution. To measure the similarity between two grasslands, a new kernel is proposed as a second contribution: the α -Gaussian mean kernel. It allows one to weight the influence of the covariance matrix when comparing two Gaussian distributions. This kernel is introduced in support vector machines for the supervised classification of grasslands from southwest France. A dense intra-annual multispectral time series of the Formosat-2 satellite is used for the classification of grasslands’ management practices, while an inter-annual NDVI time series of Formosat-2 is used for old and young grasslands’ discrimination. Results are compared to other existing pixel- and object-based approaches in terms of classification accuracy and processing time. The proposed method is shown to be a good compromise between processing speed and classification accuracy. It can adapt to the classification constraints, and it encompasses several similarity measures known in the literature. It is appropriate for the classification of small and heterogeneous objects such as grasslands.

  4. Combining anatomical, diffusion, and resting state functional magnetic resonance imaging for individual classification of mild and moderate Alzheimer's disease

    Directory of Open Access Journals (Sweden)

    Tijn M. Schouten

    2016-01-01

    Full Text Available Magnetic resonance imaging (MRI is sensitive to structural and functional changes in the brain caused by Alzheimer's disease (AD, and can therefore be used to help in diagnosing the disease. Improving classification of AD patients based on MRI scans might help to identify AD earlier in the disease's progress, which may be key in developing treatments for AD. In this study we used an elastic net classifier based on several measures derived from the MRI scans of mild to moderate AD patients (N=77 from the prospective registry on dementia study and controls (N=173 from the Austrian Stroke Prevention Family Study. We based our classification on measures from anatomical MRI, diffusion weighted MRI and resting state functional MRI. Our unimodal classification performance ranged from an area under the curve (AUC of 0.760 (full correlations between functional networks to 0.909 (grey matter density. When combining measures from multiple modalities in a stepwise manner, the classification performance improved to an AUC of 0.952. This optimal combination consisted of grey matter density, white matter density, fractional anisotropy, mean diffusivity, and sparse partial correlations between functional networks. Classification performance for mild AD as well as moderate AD also improved when using this multimodal combination. We conclude that different MRI modalities provide complementary information for classifying AD. Moreover, combining multiple modalities can substantially improve classification performance over unimodal classification.

  5. HIV classification using coalescent theory

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Ming [Los Alamos National Laboratory; Letiner, Thomas K [Los Alamos National Laboratory; Korber, Bette T [Los Alamos National Laboratory

    2008-01-01

    Algorithms for subtype classification and breakpoint detection of HIV-I sequences are based on a classification system of HIV-l. Hence, their quality highly depend on this system. Due to the history of creation of the current HIV-I nomenclature, the current one contains inconsistencies like: The phylogenetic distance between the subtype B and D is remarkably small compared with other pairs of subtypes. In fact, it is more like the distance of a pair of subsubtypes Robertson et al. (2000); Subtypes E and I do not exist any more since they were discovered to be composed of recombinants Robertson et al. (2000); It is currently discussed whether -- instead of CRF02 being a recombinant of subtype A and G -- subtype G should be designated as a circulating recombination form (CRF) nd CRF02 as a subtype Abecasis et al. (2007); There are 8 complete and over 400 partial HIV genomes in the LANL-database which belong neither to a subtype nor to a CRF (denoted by U). Moreover, the current classification system is somehow arbitrary like all complex classification systems that were created manually. To this end, it is desirable to deduce the classification system of HIV systematically by an algorithm. Of course, this problem is not restricted to HIV, but applies to all fast mutating and recombining viruses. Our work addresses the simpler subproblem to score classifications of given input sequences of some virus species (classification denotes a partition of the input sequences in several subtypes and CRFs). To this end, we reconstruct ancestral recombination graphs (ARG) of the input sequences under restrictions determined by the given classification. These restritions are imposed in order to ensure that the reconstructed ARGs do not contradict the classification under consideration. Then, we find the ARG with maximal probability by means of Markov Chain Monte Carlo methods. The probability of the most probable ARG is interpreted as a score for the classification. To our

  6. Video genre classification using multimodal features

    Science.gov (United States)

    Jin, Sung Ho; Bae, Tae Meon; Choo, Jin Ho; Ro, Yong Man

    2003-12-01

    We propose a video genre classification method using multimodal features. The proposed method is applied for the preprocessing of automatic video summarization or the retrieval and classification of broadcasting video contents. Through a statistical analysis of low-level and middle-level audio-visual features in video, the proposed method can achieve good performance in classifying several broadcasting genres such as cartoon, drama, music video, news, and sports. In this paper, we adopt MPEG-7 audio-visual descriptors as multimodal features of video contents and evaluate the performance of the classification by feeding the features into a decision tree-based classifier which is trained by CART. The experimental results show that the proposed method can recognize several broadcasting video genres with a high accuracy and the classification performance with multimodal features is superior to the one with unimodal features in the genre classification.

  7. Seafloor backscatter signal simulation and classification

    Digital Repository Service at National Institute of Oceanography (India)

    Mahale, V.; El Dine, W.G.; Chakraborty, B.

    . In this model a smooth echo envelope is generated then mixed up with multiplicative and additive noise. Several such echo signals were simulated for three types of seafloor. An Artificial Neural Network based classification technique is conceived to classify...

  8. Combining multiple classifiers for age classification

    CSIR Research Space (South Africa)

    Van Heerden, C

    2009-11-01

    Full Text Available The authors compare several different classifier combination methods on a single task, namely speaker age classification. This task is well suited to combination strategies, since significantly different feature classes are employed. Support vector...

  9. A Semisupervised Cascade Classification Algorithm

    Directory of Open Access Journals (Sweden)

    Stamatis Karlos

    2016-01-01

    Full Text Available Classification is one of the most important tasks of data mining techniques, which have been adopted by several modern applications. The shortage of enough labeled data in the majority of these applications has shifted the interest towards using semisupervised methods. Under such schemes, the use of collected unlabeled data combined with a clearly smaller set of labeled examples leads to similar or even better classification accuracy against supervised algorithms, which use labeled examples exclusively during the training phase. A novel approach for increasing semisupervised classification using Cascade Classifier technique is presented in this paper. The main characteristic of Cascade Classifier strategy is the use of a base classifier for increasing the feature space by adding either the predicted class or the probability class distribution of the initial data. The classifier of the second level is supplied with the new dataset and extracts the decision for each instance. In this work, a self-trained NB∇C4.5 classifier algorithm is presented, which combines the characteristics of Naive Bayes as a base classifier and the speed of C4.5 for final classification. We performed an in-depth comparison with other well-known semisupervised classification methods on standard benchmark datasets and we finally reached to the point that the presented technique has better accuracy in most cases.

  10. Analysis of Influence of Different Relations Types on the Quality of Thesaurus Application to Text Classification Problems

    Directory of Open Access Journals (Sweden)

    Nadezhda S. Lagutina

    2017-01-01

    Full Text Available The main purpose of the article is to analyze how effectively different types of thesaurus relations can be used for solutions of text classification tasks. The basis of the study is an automatically generated thesaurus of a subject area, that contains three types of relations: synonymous, hierarchical and associative. To generate the thesaurus the authors use a hybrid method based on several linguistic and statistical algorithms for extraction of semantic relations. The method allows to create a thesaurus with a sufficiently large number of terms and relations among them. The authors consider two problems: topical text classification and sentiment classification of large newspaper articles. To solve them, the authors developed two approaches that complement standard algorithms with a procedure that take into account thesaurus relations to determine semantic features of texts. The approach to topical classification includes the standard unsupervised BM25 algorithm and the procedure, that take into account synonymous and hierarchical relations of the thesaurus of the subject area. The approach to sentiment classification consists of two steps. At the first step, a thesaurus is created, whose terms weight polarities are calculated depending on the term occurrences in the training set or on the weights of related thesaurus terms. At the second step, the thesaurus is used to compute the features of words from texts and to classify texts by the algorithm SVM or Naive Bayes. In experiments with text corpora BBCSport, Reuters, PubMed and the corpus of articles about American immigrants, the authors varied the types of thesaurus relations that are involved in the classification and the degree of their use. The results of the experiments make it possible to evaluate the efficiency of the application of thesaurus relations for classification of raw texts and to determine under what conditions certain relationships affect more or less. In particular, the

  11. Asteroid taxonomic classifications

    International Nuclear Information System (INIS)

    Tholen, D.J.

    1989-01-01

    This paper reports on three taxonomic classification schemes developed and applied to the body of available color and albedo data. Asteroid taxonomic classifications according to two of these schemes are reproduced

  12. Hand eczema classification

    DEFF Research Database (Denmark)

    Diepgen, T L; Andersen, Klaus Ejner; Brandao, F M

    2008-01-01

    of the disease is rarely evidence based, and a classification system for different subdiagnoses of hand eczema is not agreed upon. Randomized controlled trials investigating the treatment of hand eczema are called for. For this, as well as for clinical purposes, a generally accepted classification system...... A classification system for hand eczema is proposed. Conclusions It is suggested that this classification be used in clinical work and in clinical trials....

  13. Healthy Weight

    Science.gov (United States)

    ... such diets limit your nutritional intake, can be unhealthy, and tend to fail in the long run. The key to achieving and maintaining a healthy weight isn't about short-term dietary changes. It's about a lifestyle that includes healthy eating, regular physical activity, and ...

  14. Automatic diabetic retinopathy classification

    Science.gov (United States)

    Bravo, María. A.; Arbeláez, Pablo A.

    2017-11-01

    Diabetic retinopathy (DR) is a disease in which the retina is damaged due to augmentation in the blood pressure of small vessels. DR is the major cause of blindness for diabetics. It has been shown that early diagnosis can play a major role in prevention of visual loss and blindness. This work proposes a computer based approach for the detection of DR in back-of-the-eye images based on the use of convolutional neural networks (CNNs). Our CNN uses deep architectures to classify Back-of-the-eye Retinal Photographs (BRP) in 5 stages of DR. Our method combines several preprocessing images of BRP to obtain an ACA score of 50.5%. Furthermore, we explore subproblems by training a larger CNN of our main classification task.

  15. Effects of supervised Self Organising Maps parameters on classification performance.

    Science.gov (United States)

    Ballabio, Davide; Vasighi, Mahdi; Filzmoser, Peter

    2013-02-26

    Self Organising Maps (SOMs) are one of the most powerful learning strategies among neural networks algorithms. SOMs have several adaptable parameters and the selection of appropriate network architectures is required in order to make accurate predictions. The major disadvantage of SOMs is probably due to the network optimisation, since this procedure can be often time-expensive. Effects of network size, training epochs and learning rate on the classification performance of SOMs are known, whereas the effect of other parameters (type of SOMs, weights initialisation, training algorithm, topology and boundary conditions) are not so obvious. This study was addressed to analyse the effect of SOMs parameters on the network classification performance, as well as on their computational times, taking into consideration a significant number of real datasets, in order to achieve a comprehensive statistical comparison. Parameters were contemporaneously evaluated by means of an approach based on the design of experiments, which enabled the investigation of their interaction effects. Results highlighted the most important parameters which influence the classification performance and enabled the identification of the optimal settings, as well as the optimal architectures to reduce the computational time of SOMs. Copyright © 2012 Elsevier B.V. All rights reserved.

  16. Five-way Smoking Status Classification Using Text Hot-Spot Identification and Error-correcting Output Codes

    OpenAIRE

    Cohen, Aaron M.

    2008-01-01

    We participated in the i2b2 smoking status classification challenge task. The purpose of this task was to evaluate the ability of systems to automatically identify patient smoking status from discharge summaries. Our submission included several techniques that we compared and studied, including hot-spot identification, zero-vector filtering, inverse class frequency weighting, error-correcting output codes, and post-processing rules. We evaluated our approaches using the same methods as the i2...

  17. Classification with support hyperplanes

    NARCIS (Netherlands)

    G.I. Nalbantov (Georgi); J.C. Bioch (Cor); P.J.F. Groenen (Patrick)

    2006-01-01

    textabstractA new classification method is proposed, called Support Hy- perplanes (SHs). To solve the binary classification task, SHs consider the set of all hyperplanes that do not make classification mistakes, referred to as semi-consistent hyperplanes. A test object is classified using

  18. Standard classification: Physics

    International Nuclear Information System (INIS)

    1977-01-01

    This is a draft standard classification of physics. The conception is based on the physics part of the systematic catalogue of the Bayerische Staatsbibliothek and on the classification given in standard textbooks. The ICSU-AB classification now used worldwide by physics information services was not taken into account. (BJ) [de

  19. 42 CFR 412.513 - Patient classification system.

    Science.gov (United States)

    2010-10-01

    ... LTC-DRG classification system provides a LTC-DRG, and an appropriate weighting factor, for those cases... intermediary decides that a different LTC-DRG should be assigned, the case will be reviewed by the appropriate... 42 Public Health 2 2010-10-01 2010-10-01 false Patient classification system. 412.513 Section 412...

  20. Sever's Disease

    Science.gov (United States)

    ... boys 10 years to 12 years of age. Soccer players and gymnasts often get Sever’s disease, but ... Crisis Situations Pets and Animals myhealthfinder Food and Nutrition Healthy Food Choices Weight Loss and Diet Plans ...

  1. An Improved Rotation Forest for Multi-Feature Remote-Sensing Imagery Classification

    Directory of Open Access Journals (Sweden)

    Yingchang Xiu

    2017-11-01

    Full Text Available Multi-feature, especially multi-temporal, remote-sensing data have the potential to improve land cover classification accuracy. However, sometimes it is difficult to utilize all the features efficiently. To enhance classification performance based on multi-feature imagery, an improved rotation forest, combining Principal Component Analysis (PCA and a boosting naïve Bayesian tree (NBTree, is proposed. First, feature extraction was carried out with PCA. The feature set was randomly split into several disjoint subsets; then, PCA was applied to each subset, and new training data for linear extracted features based on original training data were obtained. These steps were repeated several times. Second, based on the new training data, a boosting naïve Bayesian tree was constructed as the base classifier, which aims to achieve lower prediction error than a decision tree in the original rotation forest. At the classification phase, the improved rotation forest has two-layer voting. It first obtains several predictions through weighted voting in a boosting naïve Bayesian tree; then, the first-layer vote predicts by majority to obtain the final result. To examine the classification performance, the improved rotation forest was applied to multi-feature remote-sensing images, including MODIS Enhanced Vegetation Index (EVI imagery time series, MODIS Surface Reflectance products and ancillary data in Shandong Province for 2013. The EVI imagery time series was preprocessed using harmonic analysis of time series (HANTS to reduce the noise effects. The overall accuracy of the final classification result was 89.17%, and the Kappa coefficient was 0.71, which outperforms the original rotation forest and other classifier ensemble results, as well as the NASA land cover product. However, this new algorithm requires more computational time, meaning the efficiency needs to be further improved. Generally, the improved rotation forest has a potential advantage in

  2. Classification of refrigerants; Classification des fluides frigorigenes

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2001-07-01

    This document was made from the US standard ANSI/ASHRAE 34 published in 2001 and entitled 'designation and safety classification of refrigerants'. This classification allows to clearly organize in an international way the overall refrigerants used in the world thanks to a codification of the refrigerants in correspondence with their chemical composition. This note explains this codification: prefix, suffixes (hydrocarbons and derived fluids, azeotropic and non-azeotropic mixtures, various organic compounds, non-organic compounds), safety classification (toxicity, flammability, case of mixtures). (J.S.)

  3. Compositorial 'Weight' & 'Luminance'

    NARCIS (Netherlands)

    Koenderink, Jan; van Doorn, Andrea J.; Gegenfurtner, Karl

    2017-01-01

    Compositorial weight might be understood as an operational definition of salience. It is not a psychophysical entity, but holds a key position between psychophysics and aesthetics. Several factors ranging over raw photometric/colorimetric parameters, various kinds of psychophysical contrast, image

  4. TFM classification and staging of oral submucous fibrosis: A new proposal.

    Science.gov (United States)

    Arakeri, Gururaj; Thomas, Deepak; Aljabab, Abdulsalam S; Hunasgi, Santosh; Rai, Kirthi Kumar; Hale, Beverley; Fonseca, Felipe Paiva; Gomez, Ricardo Santiago; Rahimi, Siavash; Merkx, Matthias A W; Brennan, Peter A

    2018-04-01

    We have evaluated the rationale of existing grading and staging schemes of oral submucous fibrosis (OSMF) based on how they are categorized. A novel classification and staging scheme is proposed. A total of 300 OSMF patients were evaluated for agreement between functional, clinical, and histopathological staging. Bilateral biopsies were assessed in 25 patients to evaluate for any differences in histopathological staging of OSMF in the same mouth. Extent of clinician agreement for categorized staging data was evaluated using Cohen's weighted kappa analysis. Cross-tabulation was performed on categorical grading data to understand the intercorrelation, and the unweighted kappa analysis was used to assess the bilateral grade agreement. Probabilities of less than 0.05 were considered significant. Data were analyzed using SPSS Statistics (version 25.0, IBM, USA). A low agreement was found between all the stages depicting the independent nature of trismus, clinical features, and histopathological components (K = 0.312, 0.167, 0.152) in OSMF. Following analysis, a three-component classification scheme (TFM classification) was developed that describes the severity of each independently, grouping them using a novel three-tier staging scheme as a guide to the treatment plan. The proposed classification and staging could be useful for effective communication, categorization, and for recording data and prognosis, and for guiding treatment plans. Furthermore, the classification considers OSMF malignant transformation in detail. © 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  5. Classification, disease, and diagnosis.

    Science.gov (United States)

    Jutel, Annemarie

    2011-01-01

    Classification shapes medicine and guides its practice. Understanding classification must be part of the quest to better understand the social context and implications of diagnosis. Classifications are part of the human work that provides a foundation for the recognition and study of illness: deciding how the vast expanse of nature can be partitioned into meaningful chunks, stabilizing and structuring what is otherwise disordered. This article explores the aims of classification, their embodiment in medical diagnosis, and the historical traditions of medical classification. It provides a brief overview of the aims and principles of classification and their relevance to contemporary medicine. It also demonstrates how classifications operate as social framing devices that enable and disable communication, assert and refute authority, and are important items for sociological study.

  6. Clustering and classification of email contents

    Directory of Open Access Journals (Sweden)

    Izzat Alsmadi

    2015-01-01

    Full Text Available Information users depend heavily on emails’ system as one of the major sources of communication. Its importance and usage are continuously growing despite the evolution of mobile applications, social networks, etc. Emails are used on both the personal and professional levels. They can be considered as official documents in communication among users. Emails’ data mining and analysis can be conducted for several purposes such as: Spam detection and classification, subject classification, etc. In this paper, a large set of personal emails is used for the purpose of folder and subject classifications. Algorithms are developed to perform clustering and classification for this large text collection. Classification based on NGram is shown to be the best for such large text collection especially as text is Bi-language (i.e. with English and Arabic content.

  7. Security classification of information

    Energy Technology Data Exchange (ETDEWEB)

    Quist, A.S.

    1993-04-01

    This document is the second of a planned four-volume work that comprehensively discusses the security classification of information. The main focus of Volume 2 is on the principles for classification of information. Included herein are descriptions of the two major types of information that governments classify for national security reasons (subjective and objective information), guidance to use when determining whether information under consideration for classification is controlled by the government (a necessary requirement for classification to be effective), information disclosure risks and benefits (the benefits and costs of classification), standards to use when balancing information disclosure risks and benefits, guidance for assigning classification levels (Top Secret, Secret, or Confidential) to classified information, guidance for determining how long information should be classified (classification duration), classification of associations of information, classification of compilations of information, and principles for declassifying and downgrading information. Rules or principles of certain areas of our legal system (e.g., trade secret law) are sometimes mentioned to .provide added support to some of those classification principles.

  8. Seizure classification in EEG signals utilizing Hilbert-Huang transform

    Directory of Open Access Journals (Sweden)

    Abdulhay Enas W

    2011-05-01

    Full Text Available Abstract Background Classification method capable of recognizing abnormal activities of the brain functionality are either brain imaging or brain signal analysis. The abnormal activity of interest in this study is characterized by a disturbance caused by changes in neuronal electrochemical activity that results in abnormal synchronous discharges. The method aims at helping physicians discriminate between healthy and seizure electroencephalographic (EEG signals. Method Discrimination in this work is achieved by analyzing EEG signals obtained from freely accessible databases. MATLAB has been used to implement and test the proposed classification algorithm. The analysis in question presents a classification of normal and ictal activities using a feature relied on Hilbert-Huang Transform. Through this method, information related to the intrinsic functions contained in the EEG signal has been extracted to track the local amplitude and the frequency of the signal. Based on this local information, weighted frequencies are calculated and a comparison between ictal and seizure-free determinant intrinsic functions is then performed. Methods of comparison used are the t-test and the Euclidean clustering. Results The t-test results in a P-value Conclusion An original tool for EEG signal processing giving physicians the possibility to diagnose brain functionality abnormalities is presented in this paper. The proposed system bears the potential of providing several credible benefits such as fast diagnosis, high accuracy, good sensitivity and specificity, time saving and user friendly. Furthermore, the classification of mode mixing can be achieved using the extracted instantaneous information of every IMF, but it would be most likely a hard task if only the average value is used. Extra benefits of this proposed system include low cost, and ease of interface. All of that indicate the usefulness of the tool and its use as an efficient diagnostic tool.

  9. Seizure classification in EEG signals utilizing Hilbert-Huang transform.

    Science.gov (United States)

    Oweis, Rami J; Abdulhay, Enas W

    2011-05-24

    Classification method capable of recognizing abnormal activities of the brain functionality are either brain imaging or brain signal analysis. The abnormal activity of interest in this study is characterized by a disturbance caused by changes in neuronal electrochemical activity that results in abnormal synchronous discharges. The method aims at helping physicians discriminate between healthy and seizure electroencephalographic (EEG) signals. Discrimination in this work is achieved by analyzing EEG signals obtained from freely accessible databases. MATLAB has been used to implement and test the proposed classification algorithm. The analysis in question presents a classification of normal and ictal activities using a feature relied on Hilbert-Huang Transform. Through this method, information related to the intrinsic functions contained in the EEG signal has been extracted to track the local amplitude and the frequency of the signal. Based on this local information, weighted frequencies are calculated and a comparison between ictal and seizure-free determinant intrinsic functions is then performed. Methods of comparison used are the t-test and the Euclidean clustering. The t-test results in a P-value with respect to its fast response and ease to use. An original tool for EEG signal processing giving physicians the possibility to diagnose brain functionality abnormalities is presented in this paper. The proposed system bears the potential of providing several credible benefits such as fast diagnosis, high accuracy, good sensitivity and specificity, time saving and user friendly. Furthermore, the classification of mode mixing can be achieved using the extracted instantaneous information of every IMF, but it would be most likely a hard task if only the average value is used. Extra benefits of this proposed system include low cost, and ease of interface. All of that indicate the usefulness of the tool and its use as an efficient diagnostic tool.

  10. Classification and clinical assessment

    Directory of Open Access Journals (Sweden)

    F. Cantini

    2012-06-01

    Full Text Available There are at least nine classification criteria for psoriatic arthritis (PsA that have been proposed and used in clinical studies. With the exception of the ESSG and Bennett rules, all of the other criteria sets have a good performance in identifying PsA patients. As the CASPAR criteria are based on a robust study methodology, they are considered the current reference standard. However, if there seems to be no doubt that they are very good to classify PsA patients (very high specificity, they might be not sensitive enough to diagnose patients with unknown early PsA. The vast clinical heterogeneity of PsA makes its assessment very challenging. Peripheral joint involvement is measured by 78/76 joint counts, spine involvement by the instruments used for ankylosing spondylitis (AS, dactylitis by involved digit count or by the Leeds dactylitis index, enthesitis by the number of affected entheses (several indices available and psoriasis by the Psoriasis Area and Severity Index (PASI. Peripheral joint damage can be assessed by a modified van der Heijde-Sharp scoring system and axial damage by the methods used for AS or by the Psoriatic Arthritis Spondylitis Radiology Index (PASRI. As in other arthritides, global evaluation of disease activity and severity by patient and physician and assessment of disability and quality of life are widely used. Finally, composite indices that capture several clinical manifestations of PsA have been proposed and a new instrument, the Psoriatic ARthritis Disease Activity Score (PASDAS, is currently being developed.

  11. (Dis-)solving the Weight Problem in Binge-Eating Disorder: Systemic Insights From Three Treatment Contexts With Weight Stability, Weight Loss, and Weight Acceptance.

    Science.gov (United States)

    Meyer, Lene Bomholt; Waaddegaard, Mette; Lau, Marianne Engelbrecht; Tjørnhøj-Thomsen, Tine

    2018-04-01

    Binge-eating disorder (BED) is a severe eating disorder strongly associated with obesity. Treatments struggle to provide safe and effective ways of addressing weight in a BED context. This study explored a two-phased treatment for BED developed at a major out-patient eating disorder service in Denmark. The study used interviews and participant observations to gain insight into experiences and processes related to weight and body issues in three treatment contexts that addressed weight stability, weight acceptance, and weight loss. Using systems theory, the study proposed a relational weight problem that embeds feelings of non-acceptance due to weight, a merge of weight and identity, and an internalized body- and weight-critical gaze of others. Contrary to critical claims that weight acceptance discourages people with obesity from engaging in weight loss efforts, this study suggests that acceptance and a disentanglement of weight and identity are prerequisites for weight loss for this group.

  12. LDA boost classification: boosting by topics

    Science.gov (United States)

    Lei, La; Qiao, Guo; Qimin, Cao; Qitao, Li

    2012-12-01

    AdaBoost is an efficacious classification algorithm especially in text categorization (TC) tasks. The methodology of setting up a classifier committee and voting on the documents for classification can achieve high categorization precision. However, traditional Vector Space Model can easily lead to the curse of dimensionality and feature sparsity problems; so it affects classification performance seriously. This article proposed a novel classification algorithm called LDABoost based on boosting ideology which uses Latent Dirichlet Allocation (LDA) to modeling the feature space. Instead of using words or phrase, LDABoost use latent topics as the features. In this way, the feature dimension is significantly reduced. Improved Naïve Bayes (NB) is designed as the weaker classifier which keeps the efficiency advantage of classic NB algorithm and has higher precision. Moreover, a two-stage iterative weighted method called Cute Integration in this article is proposed for improving the accuracy by integrating weak classifiers into strong classifier in a more rational way. Mutual Information is used as metrics of weights allocation. The voting information and the categorization decision made by basis classifiers are fully utilized for generating the strong classifier. Experimental results reveals LDABoost making categorization in a low-dimensional space, it has higher accuracy than traditional AdaBoost algorithms and many other classic classification algorithms. Moreover, its runtime consumption is lower than different versions of AdaBoost, TC algorithms based on support vector machine and Neural Networks.

  13. Definition and classification of epilepsy. Classification of epileptic seizures 2016

    Directory of Open Access Journals (Sweden)

    K. Yu. Mukhin

    2017-01-01

    Full Text Available Epilepsy is one of the most common neurological diseases, especially in childhood and adolescence. The incidence varies from 15 to 113 cases per 100 000 population with the maximum among children under 1 year old. The prevalence of epilepsy is high, ranging from 5 to 8 cases (in some regions – 10 cases per 1000 children under 15 years old. Classification of the disease has great importance for diagnosis, treatment and prognosis. The article presents a novel strategy for classification of epileptic seizures, developed in 2016. It contains a number of brand new concepts, including a very important one, saying that some seizures, previously considered as generalized or focal only, can be, in fact, both focal and generalized. They include tonic, atonic, myoclonic seizures and epileptic spasms. The term “secondarily generalized seizure” is replace by the term “bilateral tonic-clonic seizure” (as soon as it is not a separate type of epileptic seizures, and the term reflects the spread of discharge from any area of cerebral cortex and evolution of any types of focal seizures. International League Against Epilepsy recommends to abandon the term “pseudo-epileptic seizures” and replace it by the term “psychogenic non-epileptic seizures”. If a doctor is not sure that seizures have epileptic nature, the term “paroxysmal event” should be used without specifying the disease. The conception of childhood epileptic encephalopathies, developed within this novel classification project, is one of the most significant achievements, since in this case not only the seizures, but even epileptiform activity can induce severe disorders of higher mental functions. In addition to detailed description of the new strategy for classification of epileptic seizures, the article contains a comprehensive review of the existing principles of epilepsy and epileptic seizures classification.

  14. Web Page Classification Method Using Neural Networks

    Science.gov (United States)

    Selamat, Ali; Omatu, Sigeru; Yanagimoto, Hidekazu; Fujinaka, Toru; Yoshioka, Michifumi

    Automatic categorization is the only viable method to deal with the scaling problem of the World Wide Web (WWW). In this paper, we propose a news web page classification method (WPCM). The WPCM uses a neural network with inputs obtained by both the principal components and class profile-based features (CPBF). Each news web page is represented by the term-weighting scheme. As the number of unique words in the collection set is big, the principal component analysis (PCA) has been used to select the most relevant features for the classification. Then the final output of the PCA is combined with the feature vectors from the class-profile which contains the most regular words in each class before feeding them to the neural networks. We have manually selected the most regular words that exist in each class and weighted them using an entropy weighting scheme. The fixed number of regular words from each class will be used as a feature vectors together with the reduced principal components from the PCA. These feature vectors are then used as the input to the neural networks for classification. The experimental evaluation demonstrates that the WPCM method provides acceptable classification accuracy with the sports news datasets.

  15. Classification of Flotation Frothers

    Directory of Open Access Journals (Sweden)

    Jan Drzymala

    2018-02-01

    Full Text Available In this paper, a scheme of flotation frothers classification is presented. The scheme first indicates the physical system in which a frother is present and four of them i.e., pure state, aqueous solution, aqueous solution/gas system and aqueous solution/gas/solid system are distinguished. As a result, there are numerous classifications of flotation frothers. The classifications can be organized into a scheme described in detail in this paper. The frother can be present in one of four physical systems, that is pure state, aqueous solution, aqueous solution/gas and aqueous solution/gas/solid system. It results from the paper that a meaningful classification of frothers relies on choosing the physical system and next feature, trend, parameter or parameters according to which the classification is performed. The proposed classification can play a useful role in characterizing and evaluation of flotation frothers.

  16. Penalized feature selection and classification in bioinformatics

    OpenAIRE

    Ma, Shuangge; Huang, Jian

    2008-01-01

    In bioinformatics studies, supervised classification with high-dimensional input variables is frequently encountered. Examples routinely arise in genomic, epigenetic and proteomic studies. Feature selection can be employed along with classifier construction to avoid over-fitting, to generate more reliable classifier and to provide more insights into the underlying causal relationships. In this article, we provide a review of several recently developed penalized feature selection and classific...

  17. Ontologies vs. Classification Systems

    DEFF Research Database (Denmark)

    Madsen, Bodil Nistrup; Erdman Thomsen, Hanne

    2009-01-01

    What is an ontology compared to a classification system? Is a taxonomy a kind of classification system or a kind of ontology? These are questions that we meet when working with people from industry and public authorities, who need methods and tools for concept clarification, for developing meta...... data sets or for obtaining advanced search facilities. In this paper we will present an attempt at answering these questions. We will give a presentation of various types of ontologies and briefly introduce terminological ontologies. Furthermore we will argue that classification systems, e.g. product...... classification systems and meta data taxonomies, should be based on ontologies....

  18. Weight Management in Phenylketonuria

    DEFF Research Database (Denmark)

    Rocha, Julio César; van Rijn, Margreet; van Dam, Esther

    2016-01-01

    . It is becoming evident that in addition to acceptable blood phenylalanine control, metabolic dieticians should regard weight management as part of routine clinical practice. SUMMARY: It is important for practitioners to differentiate the 3 levels for overweight interpretation: anthropometry, body composition...... and frequency and severity of associated metabolic comorbidities. The main objectives of this review are to suggest proposals for the minimal standard and gold standard for the assessment of weight management in PKU. While the former aims to underline the importance of nutritional status evaluation in every...... specialized clinic, the second objective is important in establishing an understanding of the breadth of overweight and obesity in PKU in Europe. KEY MESSAGES: In PKU, the importance of adopting a European nutritional management strategy on weight management is highlighted in order to optimize long...

  19. Boosted classification trees result in minor to modest improvement in the accuracy in classifying cardiovascular outcomes compared to conventional classification trees

    Science.gov (United States)

    Austin, Peter C; Lee, Douglas S

    2011-01-01

    Purpose: Classification trees are increasingly being used to classifying patients according to the presence or absence of a disease or health outcome. A limitation of classification trees is their limited predictive accuracy. In the data-mining and machine learning literature, boosting has been developed to improve classification. Boosting with classification trees iteratively grows classification trees in a sequence of reweighted datasets. In a given iteration, subjects that were misclassified in the previous iteration are weighted more highly than subjects that were correctly classified. Classifications from each of the classification trees in the sequence are combined through a weighted majority vote to produce a final classification. The authors' objective was to examine whether boosting improved the accuracy of classification trees for predicting outcomes in cardiovascular patients. Methods: We examined the utility of boosting classification trees for classifying 30-day mortality outcomes in patients hospitalized with either acute myocardial infarction or congestive heart failure. Results: Improvements in the misclassification rate using boosted classification trees were at best minor compared to when conventional classification trees were used. Minor to modest improvements to sensitivity were observed, with only a negligible reduction in specificity. For predicting cardiovascular mortality, boosted classification trees had high specificity, but low sensitivity. Conclusions: Gains in predictive accuracy for predicting cardiovascular outcomes were less impressive than gains in performance observed in the data mining literature. PMID:22254181

  20. A new classification scheme of plastic wastes based upon recycling labels

    Energy Technology Data Exchange (ETDEWEB)

    Özkan, Kemal, E-mail: kozkan@ogu.edu.tr [Computer Engineering Dept., Eskişehir Osmangazi University, 26480 Eskişehir (Turkey); Ergin, Semih, E-mail: sergin@ogu.edu.tr [Electrical Electronics Engineering Dept., Eskişehir Osmangazi University, 26480 Eskişehir (Turkey); Işık, Şahin, E-mail: sahini@ogu.edu.tr [Computer Engineering Dept., Eskişehir Osmangazi University, 26480 Eskişehir (Turkey); Işıklı, İdil, E-mail: idil.isikli@bilecik.edu.tr [Electrical Electronics Engineering Dept., Bilecik University, 11210 Bilecik (Turkey)

    2015-01-15

    Highlights: • PET, HPDE or PP types of plastics are considered. • An automated classification of plastic bottles based on the feature extraction and classification methods is performed. • The decision mechanism consists of PCA, Kernel PCA, FLDA, SVD and Laplacian Eigenmaps methods. • SVM is selected to achieve the classification task and majority voting technique is used. - Abstract: Since recycling of materials is widely assumed to be environmentally and economically beneficial, reliable sorting and processing of waste packaging materials such as plastics is very important for recycling with high efficiency. An automated system that can quickly categorize these materials is certainly needed for obtaining maximum classification while maintaining high throughput. In this paper, first of all, the photographs of the plastic bottles have been taken and several preprocessing steps were carried out. The first preprocessing step is to extract the plastic area of a bottle from the background. Then, the morphological image operations are implemented. These operations are edge detection, noise removal, hole removing, image enhancement, and image segmentation. These morphological operations can be generally defined in terms of the combinations of erosion and dilation. The effect of bottle color as well as label are eliminated using these operations. Secondly, the pixel-wise intensity values of the plastic bottle images have been used together with the most popular subspace and statistical feature extraction methods to construct the feature vectors in this study. Only three types of plastics are considered due to higher existence ratio of them than the other plastic types in the world. The decision mechanism consists of five different feature extraction methods including as Principal Component Analysis (PCA), Kernel PCA (KPCA), Fisher’s Linear Discriminant Analysis (FLDA), Singular Value Decomposition (SVD) and Laplacian Eigenmaps (LEMAP) and uses a simple

  1. A new classification scheme of plastic wastes based upon recycling labels

    International Nuclear Information System (INIS)

    Özkan, Kemal; Ergin, Semih; Işık, Şahin; Işıklı, İdil

    2015-01-01

    Highlights: • PET, HPDE or PP types of plastics are considered. • An automated classification of plastic bottles based on the feature extraction and classification methods is performed. • The decision mechanism consists of PCA, Kernel PCA, FLDA, SVD and Laplacian Eigenmaps methods. • SVM is selected to achieve the classification task and majority voting technique is used. - Abstract: Since recycling of materials is widely assumed to be environmentally and economically beneficial, reliable sorting and processing of waste packaging materials such as plastics is very important for recycling with high efficiency. An automated system that can quickly categorize these materials is certainly needed for obtaining maximum classification while maintaining high throughput. In this paper, first of all, the photographs of the plastic bottles have been taken and several preprocessing steps were carried out. The first preprocessing step is to extract the plastic area of a bottle from the background. Then, the morphological image operations are implemented. These operations are edge detection, noise removal, hole removing, image enhancement, and image segmentation. These morphological operations can be generally defined in terms of the combinations of erosion and dilation. The effect of bottle color as well as label are eliminated using these operations. Secondly, the pixel-wise intensity values of the plastic bottle images have been used together with the most popular subspace and statistical feature extraction methods to construct the feature vectors in this study. Only three types of plastics are considered due to higher existence ratio of them than the other plastic types in the world. The decision mechanism consists of five different feature extraction methods including as Principal Component Analysis (PCA), Kernel PCA (KPCA), Fisher’s Linear Discriminant Analysis (FLDA), Singular Value Decomposition (SVD) and Laplacian Eigenmaps (LEMAP) and uses a simple

  2. Gynecomastia Classification for Surgical Management: A Systematic Review and Novel Classification System.

    Science.gov (United States)

    Waltho, Daniel; Hatchell, Alexandra; Thoma, Achilleas

    2017-03-01

    Gynecomastia is a common deformity of the male breast, where certain cases warrant surgical management. There are several surgical options, which vary depending on the breast characteristics. To guide surgical management, several classification systems for gynecomastia have been proposed. A systematic review was performed to (1) identify all classification systems for the surgical management of gynecomastia, and (2) determine the adequacy of these classification systems to appropriately categorize the condition for surgical decision-making. The search yielded 1012 articles, and 11 articles were included in the review. Eleven classification systems in total were ascertained, and a total of 10 unique features were identified: (1) breast size, (2) skin redundancy, (3) breast ptosis, (4) tissue predominance, (5) upper abdominal laxity, (6) breast tuberosity, (7) nipple malposition, (8) chest shape, (9) absence of sternal notch, and (10) breast skin elasticity. On average, classification systems included two or three of these features. Breast size and ptosis were the most commonly included features. Based on their review of the current classification systems, the authors believe the ideal classification system should be universal and cater to all causes of gynecomastia; be surgically useful and easy to use; and should include a comprehensive set of clinically appropriate patient-related features, such as breast size, breast ptosis, tissue predominance, and skin redundancy. None of the current classification systems appears to fulfill these criteria.

  3. Weight Loss Nutritional Supplements

    Science.gov (United States)

    Eckerson, Joan M.

    Obesity has reached what may be considered epidemic proportions in the United States, not only for adults but for children. Because of the medical implications and health care costs associated with obesity, as well as the negative social and psychological impacts, many individuals turn to nonprescription nutritional weight loss supplements hoping for a quick fix, and the weight loss industry has responded by offering a variety of products that generates billions of dollars each year in sales. Most nutritional weight loss supplements are purported to work by increasing energy expenditure, modulating carbohydrate or fat metabolism, increasing satiety, inducing diuresis, or blocking fat absorption. To review the literally hundreds of nutritional weight loss supplements available on the market today is well beyond the scope of this chapter. Therefore, several of the most commonly used supplements were selected for critical review, and practical recommendations are provided based on the findings of well controlled, randomized clinical trials that examined their efficacy. In most cases, the nutritional supplements reviewed either elicited no meaningful effect or resulted in changes in body weight and composition that are similar to what occurs through a restricted diet and exercise program. Although there is some evidence to suggest that herbal forms of ephedrine, such as ma huang, combined with caffeine or caffeine and aspirin (i.e., ECA stack) is effective for inducing moderate weight loss in overweight adults, because of the recent ban on ephedra manufacturers must now use ephedra-free ingredients, such as bitter orange, which do not appear to be as effective. The dietary fiber, glucomannan, also appears to hold some promise as a possible treatment for weight loss, but other related forms of dietary fiber, including guar gum and psyllium, are ineffective.

  4. Couinaud's classification v.s. Cho's classification. Their feasibility in the right hepatic lobe

    International Nuclear Information System (INIS)

    Shioyama, Yasukazu; Ikeda, Hiroaki; Sato, Motohito; Yoshimi, Fuyo; Kishi, Kazushi; Sato, Morio; Kimura, Masashi

    2008-01-01

    The objective of this study was to investigate if the new classification system proposed by Cho is feasible to clinical usage comparing with the classical Couinaud's one. One hundred consecutive cases of abdominal CT were studied using a 64 or an 8 slice multislice CT and created three dimensional portal vein images for analysis by the Workstation. We applied both Cho's classification and the classical Couinaud's one for each cases according to their definitions. Three diagnostic radiologists assessed their feasibility as category one (unable to classify) to five (clear to classify with total suit with the original classification criteria). And in each cases, we tried to judge whether Cho's or the classical Couinaud' classification could more easily transmit anatomical information. Analyzers could classified portal veins clearly (category 5) in 77 to 80% of cases and clearly (category 5) or almost clearly (category 4) in 86-93% along with both classifications. In the feasibility of classification, there was no statistically significant difference between two classifications. In 15 cases we felt that using Couinaud's classification is more convenient for us to transmit anatomical information to physicians than using Cho's one, because in these cases we noticed two large portal veins ramify from right main portal vein cranialy and caudaly and then we could not classify P5 as a branch of antero-ventral segment (AVS). Conversely in 17 cases we felt Cho's classification is more convenient because we could not divide right posterior branch as P6 and P7 and in these cases the right posterior portal vein ramified to several small branches. The anterior fissure vein was clearly noticed in only 60 cases. Comparing the classical Couinaud's classification and Cho's one in feasility of classification, there was no statistically significant difference. We propose we routinely report hepatic anatomy with the classical Couinauds classification and in the preoperative cases we

  5. 26 CFR 48.4071-2 - Determination of weight.

    Science.gov (United States)

    2010-04-01

    ... EXCISE TAXES MANUFACTURERS AND RETAILERS EXCISE TAXES Motor Vehicles, Tires, Tubes, Tread Rubber, and... each type, size, grade, and classification. The average weights must be established in accordance with...

  6. A statistical approach to root system classification.

    Directory of Open Access Journals (Sweden)

    Gernot eBodner

    2013-08-01

    Full Text Available Plant root systems have a key role in ecology and agronomy. In spite of fast increase in root studies, still there is no classification that allows distinguishing among distinctive characteristics within the diversity of rooting strategies. Our hypothesis is that a multivariate approach for plant functional type identification in ecology can be applied to the classification of root systems. We demonstrate that combining principal component and cluster analysis yields a meaningful classification of rooting types based on morphological traits. The classification method presented is based on a data-defined statistical procedure without a priori decision on the classifiers. Biplot inspection is used to determine key traits and to ensure stability in cluster based grouping. The classification method is exemplified with simulated root architectures and morphological field data. Simulated root architectures showed that morphological attributes with spatial distribution parameters capture most distinctive features within root system diversity. While developmental type (tap vs. shoot-borne systems is a strong, but coarse classifier, topological traits provide the most detailed differentiation among distinctive groups. Adequacy of commonly available morphologic traits for classification is supported by field data. Three rooting types emerged from measured data, distinguished by diameter/weight, density and spatial distribution respectively. Similarity of root systems within distinctive groups was the joint result of phylogenetic relation and environmental as well as human selection pressure. We concluded that the data-define classification is appropriate for integration of knowledge obtained with different root measurement methods and at various scales. Currently root morphology is the most promising basis for classification due to widely used common measurement protocols. To capture details of root diversity efforts in architectural measurement

  7. Applying inventory classification to a large inventory management system

    Directory of Open Access Journals (Sweden)

    Benjamin Isaac May

    2017-06-01

    Full Text Available Inventory classification aims to ensure that business-driving inventory items are efficiently managed in spite of constrained resources. There are numerous single- and multiple-criteria approaches to it. Our objective is to improve resource allocation to focus on items that can lead to high equipment availability. This concern is typical of many service industries such as military logistics, airlines, amusement parks and public works. Our study tests several inventory prioritization techniques and finds that a modified multi-criterion weighted non-linear optimization (WNO technique is a powerful approach for classifying inventory, outperforming traditional techniques of inventory prioritization such as ABC analysis in a variety of performance objectives.

  8. Epidemiology, classification, and modifiable risk factors of peripheral arterial disease

    Directory of Open Access Journals (Sweden)

    Nicolas W Shammas

    2007-05-01

    Full Text Available Nicolas W ShammasMidwest Cardiovascular Research Foundation, Cardiovascular Medicine, PC, Davenport, IA, USAAbstract: Peripheral arterial disease (PAD is part of a global vascular problem of diffuse atherosclerosis. PAD patients die mostly of cardiac and cerebrovascular-related events and much less frequently due to obstructive disease of the lower extremities. Aggressive risk factors modification is needed to reduce cardiac mortality in PAD patients. These include smoking cessation, reduction of blood pressure to current guidelines, aggressive low density lipoprotein lowering, losing weight, controlling diabetes and the use of oral antiplatelet drugs such as aspirin or clopidogrel. In addition to quitting smoking and exercise, cilostazol and statins have been shown to reduce claudication in patients with PAD. Patients with critical rest limb ischemia or severe progressive claudication need to be treated with revascularization to minimize the chance of limb loss, reduce symptoms, and improve quality of life.Keywords: peripheral arterial disease, epidemiology, risk factors, classification

  9. PATTERN CLASSIFICATION APPROACHES TO MATCHING BUILDING POLYGONS AT MULTIPLE SCALES

    Directory of Open Access Journals (Sweden)

    X. Zhang

    2012-07-01

    Full Text Available Matching of building polygons with different levels of detail is crucial in the maintenance and quality assessment of multi-representation databases. Two general problems need to be addressed in the matching process: (1 Which criteria are suitable? (2 How to effectively combine different criteria to make decisions? This paper mainly focuses on the second issue and views data matching as a supervised pattern classification. Several classifiers (i.e. decision trees, Naive Bayes and support vector machines are evaluated for the matching task. Four criteria (i.e. position, size, shape and orientation are used to extract information for these classifiers. Evidence shows that these classifiers outperformed the weighted average approach.

  10. Non-Hodgkin lymphoma response evaluation with MRI texture classification

    Directory of Open Access Journals (Sweden)

    Heinonen Tomi T

    2009-06-01

    Full Text Available Abstract Background To show magnetic resonance imaging (MRI texture appearance change in non-Hodgkin lymphoma (NHL during treatment with response controlled by quantitative volume analysis. Methods A total of 19 patients having NHL with an evaluable lymphoma lesion were scanned at three imaging timepoints with 1.5T device during clinical treatment evaluation. Texture characteristics of images were analyzed and classified with MaZda application and statistical tests. Results NHL tissue MRI texture imaged before treatment and under chemotherapy was classified within several subgroups, showing best discrimination with 96% correct classification in non-linear discriminant analysis of T2-weighted images. Texture parameters of MRI data were successfully tested with statistical tests to assess the impact of the separability of the parameters in evaluating chemotherapy response in lymphoma tissue. Conclusion Texture characteristics of MRI data were classified successfully; this proved texture analysis to be potential quantitative means of representing lymphoma tissue changes during chemotherapy response monitoring.

  11. Classification of radiological procedures

    International Nuclear Information System (INIS)

    1989-01-01

    A classification for departments in Danish hospitals which use radiological procedures. The classification codes consist of 4 digits, where the first 2 are the codes for the main groups. The first digit represents the procedure's topographical object and the second the techniques. The last 2 digits describe individual procedures. (CLS)

  12. Colombia: Territorial classification

    International Nuclear Information System (INIS)

    Mendoza Morales, Alberto

    1998-01-01

    The article is about the approaches of territorial classification, thematic axes, handling principles and territorial occupation, politician and administrative units and administration regions among other topics. Understanding as Territorial Classification the space distribution on the territory of the country, of the geographical configurations, the human communities, the political-administrative units and the uses of the soil, urban and rural, existent and proposed

  13. Munitions Classification Library

    Science.gov (United States)

    2016-04-04

    members of the community to make their own additions to any, or all, of the classification libraries . The next phase entailed data collection over less......Include area code) 04/04/2016 Final Report August 2014 - August 2015 MUNITIONS CLASSIFICATION LIBRARY Mr. Craig Murray, Parsons Dr. Thomas H. Bell, Leidos

  14. Recursive automatic classification algorithms

    Energy Technology Data Exchange (ETDEWEB)

    Bauman, E V; Dorofeyuk, A A

    1982-03-01

    A variational statement of the automatic classification problem is given. The dependence of the form of the optimal partition surface on the form of the classification objective functional is investigated. A recursive algorithm is proposed for maximising a functional of reasonably general form. The convergence problem is analysed in connection with the proposed algorithm. 8 references.

  15. Library Classification 2020

    Science.gov (United States)

    Harris, Christopher

    2013-01-01

    In this article the author explores how a new library classification system might be designed using some aspects of the Dewey Decimal Classification (DDC) and ideas from other systems to create something that works for school libraries in the year 2020. By examining what works well with the Dewey Decimal System, what features should be carried…

  16. Marijuana and Body Weight

    OpenAIRE

    Sansone, Randy A.; Sansone, Lori A.

    2014-01-01

    Acute marijuana use is classically associated with snacking behavior (colloquially referred to as “the munchies”). In support of these acute appetite-enhancing effects, several authorities report that marijuana may increase body mass index in patients suffering from human immunodeficiency virus and cancer. However, for these medical conditions, while appetite may be stimulated, some studies indicate that weight gain is not always clinically meaningful. In addition, in a study of cancer patien...

  17. DOE LLW classification rationale

    International Nuclear Information System (INIS)

    Flores, A.Y.

    1991-01-01

    This report was about the rationale which the US Department of Energy had with low-level radioactive waste (LLW) classification. It is based on the Nuclear Regulatory Commission's classification system. DOE site operators met to review the qualifications and characteristics of the classification systems. They evaluated performance objectives, developed waste classification tables, and compiled dose limits on the waste. A goal of the LLW classification system was to allow each disposal site the freedom to develop limits to radionuclide inventories and concentrations according to its own site-specific characteristics. This goal was achieved with the adoption of a performance objectives system based on a performance assessment, with site-specific environmental conditions and engineered disposal systems

  18. Constructing criticality by classification

    DEFF Research Database (Denmark)

    Machacek, Erika

    2017-01-01

    " in the bureaucratic practice of classification: Experts construct material criticality in assessments as they allot information on the materials to the parameters of the assessment framework. In so doing, they ascribe a new set of connotations to the materials, namely supply risk, and their importance to clean energy......, legitimizing a criticality discourse.Specifically, the paper introduces a typology delineating the inferences made by the experts from their produced recommendations in the classification of rare earth element criticality. The paper argues that the classification is a specific process of constructing risk....... It proposes that the expert bureaucratic practice of classification legitimizes (i) the valorisation that was made in the drafting of the assessment framework for the classification, and (ii) political operationalization when enacted that might have (non-)distributive implications for the allocation of public...

  19. Classification of new particles

    International Nuclear Information System (INIS)

    Karl, G.

    1976-01-01

    A classification of the new particles is proposed. Hadrons are constructed from quarks corresponding to several different representations of an SU 3 color group, with confined color. The new family of resonances, related to psi/J, is assigned to color-antisextet quarks Q. These new quarks Q do not form mixed mesons q-barQ with old antiquarks but can form mixed baryons Qqq. We speculate on the relation between color and mass. High-mass recurrences of the psi/J family are expected to have associated large changes in the cross section for electron-positron annihilation (ΔR > 4). A conjectured mass formula, which relates the masses of psi/J and ω, predicts the masses of possible recurrences of the psi/J particle. Other experimental implications at presently available energies are discussed, especially the necessity for an isovector partner for psi/J, and for pseudoscalar mesons at 1.8--2.2 GeV, some of which can decay into two photons

  20. Boundedness of positive operators on weighted amalgams

    Directory of Open Access Journals (Sweden)

    Aguilar Cañestro María Isabel

    2011-01-01

    Full Text Available Abstract In this article, we characterize the pairs (u, v of positive measurable functions such that T maps the weighted amalgam in (Lp (u, ℓ q for all , where T belongs to a class of positive operators which includes Hardy operators, maximal operators, and fractional integrals. 2000 Mathematics Subject Classification 26D10, 26D15 (42B35

  1. Disjoint hypercyclicity of weighted composition operators

    Indian Academy of Sciences (India)

    Hypercyclicity; supercyclicity; disjoint hypercyclicity; disjoint super- cyclicity; weighted composition operators; Hilbert space. 2010 Mathematics Subject Classification. 47A16, 47B33, 47B38. 1. Introduction. Let X be a topological vector space and T a bounded linear operator on X. The T-orbit of a vector x ∈ X is the set. O(x,T) ...

  2. Classification Using Markov Blanket for Feature Selection

    DEFF Research Database (Denmark)

    Zeng, Yifeng; Luo, Jian

    2009-01-01

    Selecting relevant features is in demand when a large data set is of interest in a classification task. It produces a tractable number of features that are sufficient and possibly improve the classification performance. This paper studies a statistical method of Markov blanket induction algorithm...... for filtering features and then applies a classifier using the Markov blanket predictors. The Markov blanket contains a minimal subset of relevant features that yields optimal classification performance. We experimentally demonstrate the improved performance of several classifiers using a Markov blanket...... induction as a feature selection method. In addition, we point out an important assumption behind the Markov blanket induction algorithm and show its effect on the classification performance....

  3. Overweight, Obesity, and Weight Loss

    Science.gov (United States)

    ... Back to section menu Healthy Weight Weight and obesity Underweight Weight, fertility, and pregnancy Weight loss and ... section Home Healthy Weight Healthy Weight Weight and obesity Underweight Weight, fertility, and pregnancy Weight loss and ...

  4. General regression and representation model for classification.

    Directory of Open Access Journals (Sweden)

    Jianjun Qian

    Full Text Available Recently, the regularized coding-based classification methods (e.g. SRC and CRC show a great potential for pattern classification. However, most existing coding methods assume that the representation residuals are uncorrelated. In real-world applications, this assumption does not hold. In this paper, we take account of the correlations of the representation residuals and develop a general regression and representation model (GRR for classification. GRR not only has advantages of CRC, but also takes full use of the prior information (e.g. the correlations between representation residuals and representation coefficients and the specific information (weight matrix of image pixels to enhance the classification performance. GRR uses the generalized Tikhonov regularization and K Nearest Neighbors to learn the prior information from the training data. Meanwhile, the specific information is obtained by using an iterative algorithm to update the feature (or image pixel weights of the test sample. With the proposed model as a platform, we design two classifiers: basic general regression and representation classifier (B-GRR and robust general regression and representation classifier (R-GRR. The experimental results demonstrate the performance advantages of proposed methods over state-of-the-art algorithms.

  5. Automatic detection and classification of breast tumors in ultrasonic images using texture and morphological features.

    Science.gov (United States)

    Su, Yanni; Wang, Yuanyuan; Jiao, Jing; Guo, Yi

    2011-01-01

    Due to severe presence of speckle noise, poor image contrast and irregular lesion shape, it is challenging to build a fully automatic detection and classification system for breast ultrasonic images. In this paper, a novel and effective computer-aided method including generation of a region of interest (ROI), segmentation and classification of breast tumor is proposed without any manual intervention. By incorporating local features of texture and position, a ROI is firstly detected using a self-organizing map neural network. Then a modified Normalized Cut approach considering the weighted neighborhood gray values is proposed to partition the ROI into clusters and get the initial boundary. In addition, a regional-fitting active contour model is used to adjust the few inaccurate initial boundaries for the final segmentation. Finally, three textures and five morphologic features are extracted from each breast tumor; whereby a highly efficient Affinity Propagation clustering is used to fulfill the malignancy and benign classification for an existing database without any training process. The proposed system is validated by 132 cases (67 benignancies and 65 malignancies) with its performance compared to traditional methods such as level set segmentation, artificial neural network classifiers, and so forth. Experiment results show that the proposed system, which needs no training procedure or manual interference, performs best in detection and classification of ultrasonic breast tumors, while having the lowest computation complexity.

  6. A Study on SVM Based on the Weighted Elitist Teaching-Learning-Based Optimization and Application in the Fault Diagnosis of Chemical Process

    Directory of Open Access Journals (Sweden)

    Cao Junxiang

    2015-01-01

    Full Text Available Teaching-Learning-Based Optimization (TLBO is a new swarm intelligence optimization algorithm that simulates the class learning process. According to such problems of the traditional TLBO as low optimizing efficiency and poor stability, this paper proposes an improved TLBO algorithm mainly by introducing the elite thought in TLBO and adopting different inertia weight decreasing strategies for elite and ordinary individuals of the teacher stage and the student stage. In this paper, the validity of the improved TLBO is verified by the optimizations of several typical test functions and the SVM optimized by the weighted elitist TLBO is used in the diagnosis and classification of common failure data of the TE chemical process. Compared with the SVM combining other traditional optimizing methods, the SVM optimized by the weighted elitist TLBO has a certain improvement in the accuracy of fault diagnosis and classification.

  7. Classification of movement disorders.

    Science.gov (United States)

    Fahn, Stanley

    2011-05-01

    The classification of movement disorders has evolved. Even the terminology has shifted, from an anatomical one of extrapyramidal disorders to a phenomenological one of movement disorders. The history of how this shift came about is described. The history of both the definitions and the classifications of the various neurologic conditions is then reviewed. First is a review of movement disorders as a group; then, the evolving classifications for 3 of them--parkinsonism, dystonia, and tremor--are covered in detail. Copyright © 2011 Movement Disorder Society.

  8. Word Embedding Perturbation for Sentence Classification

    OpenAIRE

    Zhang, Dongxu; Yang, Zhichao

    2018-01-01

    In this technique report, we aim to mitigate the overfitting problem of natural language by applying data augmentation methods. Specifically, we attempt several types of noise to perturb the input word embedding, such as Gaussian noise, Bernoulli noise, and adversarial noise, etc. We also apply several constraints on different types of noise. By implementing these proposed data augmentation methods, the baseline models can gain improvements on several sentence classification tasks.

  9. Handling Dynamic Weights in Weighted Frequent Pattern Mining

    Science.gov (United States)

    Ahmed, Chowdhury Farhan; Tanbeer, Syed Khairuzzaman; Jeong, Byeong-Soo; Lee, Young-Koo

    Even though weighted frequent pattern (WFP) mining is more effective than traditional frequent pattern mining because it can consider different semantic significances (weights) of items, existing WFP algorithms assume that each item has a fixed weight. But in real world scenarios, the weight (price or significance) of an item can vary with time. Reflecting these changes in item weight is necessary in several mining applications, such as retail market data analysis and web click stream analysis. In this paper, we introduce the concept of a dynamic weight for each item, and propose an algorithm, DWFPM (dynamic weighted frequent pattern mining), that makes use of this concept. Our algorithm can address situations where the weight (price or significance) of an item varies dynamically. It exploits a pattern growth mining technique to avoid the level-wise candidate set generation-and-test methodology. Furthermore, it requires only one database scan, so it is eligible for use in stream data mining. An extensive performance analysis shows that our algorithm is efficient and scalable for WFP mining using dynamic weights.

  10. Physical Activity and Sedentary Time Associations with Metabolic Health Across Weight Statuses in Children and Adolescents

    DEFF Research Database (Denmark)

    Kuzik, Nicholas; Carson, Valerie; Andersen, Lars Bo

    2017-01-01

    classification compared with metabolically healthy (MH) classification for the NW group. More MVPA was associated with lower odds of MU classification than MH classification for NW and overweight groups. For multinomial logistic regressions, more MVPA was associated with lower odds of MH-obesity classification......, as well as MU-NW, -overweight, and -obesity classifications, compared with the MH-NW group. Furthermore, more sedentary time was associated with higher odds of MU-NW classification compared with the MH-NW group. CONCLUSIONS: More MVPA was beneficial for metabolic health and weight status, whereas lower......OBJECTIVE: The aim of this study was to examine the prevalence of metabolic health across weight statuses and the associations of physical activity and sedentary time within and across metabolic health-weight status groups. METHODS: Six studies (n = 4,581) from the International Children...

  11. Update on diabetes classification.

    Science.gov (United States)

    Thomas, Celeste C; Philipson, Louis H

    2015-01-01

    This article highlights the difficulties in creating a definitive classification of diabetes mellitus in the absence of a complete understanding of the pathogenesis of the major forms. This brief review shows the evolving nature of the classification of diabetes mellitus. No classification scheme is ideal, and all have some overlap and inconsistencies. The only diabetes in which it is possible to accurately diagnose by DNA sequencing, monogenic diabetes, remains undiagnosed in more than 90% of the individuals who have diabetes caused by one of the known gene mutations. The point of classification, or taxonomy, of disease, should be to give insight into both pathogenesis and treatment. It remains a source of frustration that all schemes of diabetes mellitus continue to fall short of this goal. Copyright © 2015 Elsevier Inc. All rights reserved.

  12. Learning Apache Mahout classification

    CERN Document Server

    Gupta, Ashish

    2015-01-01

    If you are a data scientist who has some experience with the Hadoop ecosystem and machine learning methods and want to try out classification on large datasets using Mahout, this book is ideal for you. Knowledge of Java is essential.

  13. CLASSIFICATION OF VIRUSES

    Indian Academy of Sciences (India)

    First page Back Continue Last page Overview Graphics. CLASSIFICATION OF VIRUSES. On basis of morphology. On basis of chemical composition. On basis of structure of genome. On basis of mode of replication. Notes:

  14. Pitch Based Sound Classification

    DEFF Research Database (Denmark)

    Nielsen, Andreas Brinch; Hansen, Lars Kai; Kjems, U

    2006-01-01

    A sound classification model is presented that can classify signals into music, noise and speech. The model extracts the pitch of the signal using the harmonic product spectrum. Based on the pitch estimate and a pitch error measure, features are created and used in a probabilistic model with soft......-max output function. Both linear and quadratic inputs are used. The model is trained on 2 hours of sound and tested on publicly available data. A test classification error below 0.05 with 1 s classification windows is achieved. Further more it is shown that linear input performs as well as a quadratic......, and that even though classification gets marginally better, not much is achieved by increasing the window size beyond 1 s....

  15. Waste classification and methods applied to specific disposal sites

    International Nuclear Information System (INIS)

    Rogers, V.C.

    1979-01-01

    An adequate definition of the classes of radioactive wastes is necessary to regulating the disposal of radioactive wastes. A classification system is proposed in which wastes are classified according to characteristics relating to their disposal. Several specific sites are analyzed with the methodology in order to gain insights into the classification of radioactive wastes. Also presented is the analysis of ocean dumping as it applies to waste classification. 5 refs

  16. Towards secondary fingerprint classification

    CSIR Research Space (South Africa)

    Msiza, IS

    2011-07-01

    Full Text Available an accuracy figure of 76.8%. This small difference between the two figures is indicative of the validity of the proposed secondary classification module. Keywords?fingerprint core; fingerprint delta; primary classifi- cation; secondary classification I..., namely, the fingerprint core and the fingerprint delta. Forensically, a fingerprint core is defined as the innermost turning point where the fingerprint ridges form a loop, while the fingerprint delta is defined as the point where these ridges form a...

  17. Expected Classification Accuracy

    Directory of Open Access Journals (Sweden)

    Lawrence M. Rudner

    2005-08-01

    Full Text Available Every time we make a classification based on a test score, we should expect some number..of misclassifications. Some examinees whose true ability is within a score range will have..observed scores outside of that range. A procedure for providing a classification table of..true and expected scores is developed for polytomously scored items under item response..theory and applied to state assessment data. A simplified procedure for estimating the..table entries is also presented.

  18. Latent classification models

    DEFF Research Database (Denmark)

    Langseth, Helge; Nielsen, Thomas Dyhre

    2005-01-01

    parametric family ofdistributions.  In this paper we propose a new set of models forclassification in continuous domains, termed latent classificationmodels. The latent classification model can roughly be seen ascombining the \\NB model with a mixture of factor analyzers,thereby relaxing the assumptions...... classification model, and wedemonstrate empirically that the accuracy of the proposed model issignificantly higher than the accuracy of other probabilisticclassifiers....

  19. 78 FR 68983 - Cotton Futures Classification: Optional Classification Procedure

    Science.gov (United States)

    2013-11-18

    ...-AD33 Cotton Futures Classification: Optional Classification Procedure AGENCY: Agricultural Marketing... regulations to allow for the addition of an optional cotton futures classification procedure--identified and... response to requests from the U.S. cotton industry and ICE, AMS will offer a futures classification option...

  20. Weight Loss Surgery

    Science.gov (United States)

    Weight loss surgery helps people with extreme obesity to lose weight. It may be an option if you cannot lose weight ... obesity. There are different types of weight loss surgery. They often limit the amount of food you ...

  1. Customer and performance rating in QFD using SVM classification

    Science.gov (United States)

    Dzulkifli, Syarizul Amri; Salleh, Mohd Najib Mohd; Leman, A. M.

    2017-09-01

    In a classification problem, where each input is associated to one output. Training data is used to create a model which predicts values to the true function. SVM is a popular method for binary classification due to their theoretical foundation and good generalization performance. However, when trained with noisy data, the decision hyperplane might deviate from optimal position because of the sum of misclassification errors in the objective function. In this paper, we introduce fuzzy in weighted learning approach for improving the accuracy of Support Vector Machine (SVM) classification. The main aim of this work is to determine appropriate weighted for SVM to adjust the parameters of learning method from a given set of noisy input to output data. The performance and customer rating in Quality Function Deployment (QFD) is used as our case study to determine implementing fuzzy SVM is highly scalable for very large data sets and generating high classification accuracy.

  2. Supernova Photometric Lightcurve Classification

    Science.gov (United States)

    Zaidi, Tayeb; Narayan, Gautham

    2016-01-01

    This is a preliminary report on photometric supernova classification. We first explore the properties of supernova light curves, and attempt to restructure the unevenly sampled and sparse data from assorted datasets to allow for processing and classification. The data was primarily drawn from the Dark Energy Survey (DES) simulated data, created for the Supernova Photometric Classification Challenge. This poster shows a method for producing a non-parametric representation of the light curve data, and applying a Random Forest classifier algorithm to distinguish between supernovae types. We examine the impact of Principal Component Analysis to reduce the dimensionality of the dataset, for future classification work. The classification code will be used in a stage of the ANTARES pipeline, created for use on the Large Synoptic Survey Telescope alert data and other wide-field surveys. The final figure-of-merit for the DES data in the r band was 60% for binary classification (Type I vs II).Zaidi was supported by the NOAO/KPNO Research Experiences for Undergraduates (REU) Program which is funded by the National Science Foundation Research Experiences for Undergraduates Program (AST-1262829).

  3. A New Classification Approach Based on Multiple Classification Rules

    OpenAIRE

    Zhongmei Zhou

    2014-01-01

    A good classifier can correctly predict new data for which the class label is unknown, so it is important to construct a high accuracy classifier. Hence, classification techniques are much useful in ubiquitous computing. Associative classification achieves higher classification accuracy than some traditional rule-based classification approaches. However, the approach also has two major deficiencies. First, it generates a very large number of association classification rules, especially when t...

  4. Training strategy for convolutional neural networks in pedestrian gender classification

    Science.gov (United States)

    Ng, Choon-Boon; Tay, Yong-Haur; Goi, Bok-Min

    2017-06-01

    In this work, we studied a strategy for training a convolutional neural network in pedestrian gender classification with limited amount of labeled training data. Unsupervised learning by k-means clustering on pedestrian images was used to learn the filters to initialize the first layer of the network. As a form of pre-training, supervised learning for the related task of pedestrian classification was performed. Finally, the network was fine-tuned for gender classification. We found that this strategy improved the network's generalization ability in gender classification, achieving better test results when compared to random weights initialization and slightly more beneficial than merely initializing the first layer filters by unsupervised learning. This shows that unsupervised learning followed by pre-training with pedestrian images is an effective strategy to learn useful features for pedestrian gender classification.

  5. Cloud field classification based on textural features

    Science.gov (United States)

    Sengupta, Sailes Kumar

    1989-01-01

    An essential component in global climate research is accurate cloud cover and type determination. Of the two approaches to texture-based classification (statistical and textural), only the former is effective in the classification of natural scenes such as land, ocean, and atmosphere. In the statistical approach that was adopted, parameters characterizing the stochastic properties of the spatial distribution of grey levels in an image are estimated and then used as features for cloud classification. Two types of textural measures were used. One is based on the distribution of the grey level difference vector (GLDV), and the other on a set of textural features derived from the MaxMin cooccurrence matrix (MMCM). The GLDV method looks at the difference D of grey levels at pixels separated by a horizontal distance d and computes several statistics based on this distribution. These are then used as features in subsequent classification. The MaxMin tectural features on the other hand are based on the MMCM, a matrix whose (I,J)th entry give the relative frequency of occurrences of the grey level pair (I,J) that are consecutive and thresholded local extremes separated by a given pixel distance d. Textural measures are then computed based on this matrix in much the same manner as is done in texture computation using the grey level cooccurrence matrix. The database consists of 37 cloud field scenes from LANDSAT imagery using a near IR visible channel. The classification algorithm used is the well known Stepwise Discriminant Analysis. The overall accuracy was estimated by the percentage or correct classifications in each case. It turns out that both types of classifiers, at their best combination of features, and at any given spatial resolution give approximately the same classification accuracy. A neural network based classifier with a feed forward architecture and a back propagation training algorithm is used to increase the classification accuracy, using these two classes

  6. Is Weight Training Safe during Pregnancy?

    Science.gov (United States)

    Work, Janis A.

    1989-01-01

    Examines the opinions of several experts on the safety of weight training during pregnancy, noting that no definitive research on weight training alone has been done. Experts agree that low-intensity weight training probably poses no harm for mother or fetus; exercise programs should be individualized. (SM)

  7. Dewey Decimal Classification for U. S. Conn: An Advantage?

    Science.gov (United States)

    Marek, Kate

    This paper examines the use of the Dewey Decimal Classification (DDC) system at the U. S. Conn Library at Wayne State College (WSC) in Nebraska. Several developments in the last 20 years which have eliminated the trend toward reclassification of academic library collections from DDC to the Library of Congress (LC) classification scheme are…

  8. Face classification using electronic synapses

    Science.gov (United States)

    Yao, Peng; Wu, Huaqiang; Gao, Bin; Eryilmaz, Sukru Burc; Huang, Xueyao; Zhang, Wenqiang; Zhang, Qingtian; Deng, Ning; Shi, Luping; Wong, H.-S. Philip; Qian, He

    2017-05-01

    Conventional hardware platforms consume huge amount of energy for cognitive learning due to the data movement between the processor and the off-chip memory. Brain-inspired device technologies using analogue weight storage allow to complete cognitive tasks more efficiently. Here we present an analogue non-volatile resistive memory (an electronic synapse) with foundry friendly materials. The device shows bidirectional continuous weight modulation behaviour. Grey-scale face classification is experimentally demonstrated using an integrated 1024-cell array with parallel online training. The energy consumption within the analogue synapses for each iteration is 1,000 × (20 ×) lower compared to an implementation using Intel Xeon Phi processor with off-chip memory (with hypothetical on-chip digital resistive random access memory). The accuracy on test sets is close to the result using a central processing unit. These experimental results consolidate the feasibility of analogue synaptic array and pave the way toward building an energy efficient and large-scale neuromorphic system.

  9. Improved motion description for action classification

    NARCIS (Netherlands)

    Jain, M.; Jégou, H.; Bouthemy, P.

    2016-01-01

    Even though the importance of explicitly integrating motion characteristics in video descriptions has been demonstrated by several recent papers on action classification, our current work concludes that adequately decomposing visual motion into dominant and residual motions, i.e., camera and scene

  10. Sub-lingual administration of a polyvalent mechanical bacterial lysate (PMBL) in patients with moderate, severe, or very severe chronic obstructive pulmonary disease (COPD) according to the GOLD spirometric classification: A multicentre, double-blind, randomised, controlled, phase IV study (AIACE study: Advanced Immunological Approach in COPD Exacerbation).

    Science.gov (United States)

    Braido, Fulvio; Melioli, Giovanni; Cazzola, Mario; Fabbri, Leonardo; Blasi, Francesco; Moretta, Lorenzo; Canonica, Giorgio Walter

    2015-08-01

    Polyvalent mechanical bacterial lysates (PMBLs) have been shown to reduce the number of infectious episodes in patients with recurrent infections of the respiratory tract. Some previous investigations have also shown the effectiveness of PMBLs in reducing exacerbations of chronic obstructive pulmonary disease (COPD). The AIACE study, which was developed according to criteria of evidence-based medicine, evaluated whether the administration of PMBLs to COPD patients, in addition to the recommended treatment, was able to reduce the number of exacerbations by 25%. Two hundred eighty-eight patients with moderate to very severe COPD were recruited and randomly assigned to either placebo or PMBLs. The placebo or PMBLs were administered according to the standard scheme. The primary outcome of the study was not achieved. However, the number of days with fever (21 days per year versus 40.15; p < 0.001), the days of hospitalisation (65 days vs 162 days; p < 0.001), the interval between the first and second exacerbations (123.89 days vs 70.36; p = 0.03) and the number of days in poor health (109 days/year vs 171 days/year; p < 0.001) were significantly better in the PMBL group than in the placebo group. In conclusion, the results of this trials showed that Ismigen, in addition to guideline-suggested treatment, could not significantly reduce the number of exacerbations in the considered population; nevertheless, the secondary outcome results demonstrated potential benefits of this compound for relevant clinical outcomes. Copyright © 2015. Published by Elsevier Ltd.

  11. Cellular image classification

    CERN Document Server

    Xu, Xiang; Lin, Feng

    2017-01-01

    This book introduces new techniques for cellular image feature extraction, pattern recognition and classification. The authors use the antinuclear antibodies (ANAs) in patient serum as the subjects and the Indirect Immunofluorescence (IIF) technique as the imaging protocol to illustrate the applications of the described methods. Throughout the book, the authors provide evaluations for the proposed methods on two publicly available human epithelial (HEp-2) cell datasets: ICPR2012 dataset from the ICPR'12 HEp-2 cell classification contest and ICIP2013 training dataset from the ICIP'13 Competition on cells classification by fluorescent image analysis. First, the reading of imaging results is significantly influenced by one’s qualification and reading systems, causing high intra- and inter-laboratory variance. The authors present a low-order LP21 fiber mode for optical single cell manipulation and imaging staining patterns of HEp-2 cells. A focused four-lobed mode distribution is stable and effective in optical...

  12. Bosniak classification system

    DEFF Research Database (Denmark)

    Graumann, Ole; Osther, Susanne Sloth; Karstoft, Jens

    2016-01-01

    BACKGROUND: The Bosniak classification was originally based on computed tomographic (CT) findings. Magnetic resonance (MR) and contrast-enhanced ultrasonography (CEUS) imaging may demonstrate findings that are not depicted at CT, and there may not always be a clear correlation between the findings...... at MR and CEUS imaging and those at CT. PURPOSE: To compare diagnostic accuracy of MR, CEUS, and CT when categorizing complex renal cystic masses according to the Bosniak classification. MATERIAL AND METHODS: From February 2011 to June 2012, 46 complex renal cysts were prospectively evaluated by three...... readers. Each mass was categorized according to the Bosniak classification and CT was chosen as gold standard. Kappa was calculated for diagnostic accuracy and data was compared with pathological results. RESULTS: CT images found 27 BII, six BIIF, seven BIII, and six BIV. Forty-three cysts could...

  13. Mindfulness Approaches and Weight Loss, Weight Maintenance, and Weight Regain.

    Science.gov (United States)

    Dunn, Carolyn; Haubenreiser, Megan; Johnson, Madison; Nordby, Kelly; Aggarwal, Surabhi; Myer, Sarah; Thomas, Cathy

    2018-03-01

    There is an urgent need for effective weight management techniques, as more than one third of US adults are overweight or obese. Recommendations for weight loss include a combination of reducing caloric intake, increasing physical activity, and behavior modification. Behavior modification includes mindful eating or eating with awareness. The purpose of this review was to summarize the literature and examine the impact of mindful eating on weight management. The practice of mindful eating has been applied to the reduction of food cravings, portion control, body mass index, and body weight. Past reviews evaluating the relationship between mindfulness and weight management did not focus on change in mindful eating as the primary outcome or mindful eating as a measured variable. This review demonstrates strong support for inclusion of mindful eating as a component of weight management programs and may provide substantial benefit to the treatment of overweight and obesity.

  14. Current concepts of severe asthma

    Science.gov (United States)

    Raundhal, Mahesh; Oriss, Timothy B.; Ray, Prabir; Wenzel, Sally E.

    2016-01-01

    The term asthma encompasses a disease spectrum with mild to very severe disease phenotypes whose traditional common characteristic is reversible airflow limitation. Unlike milder disease, severe asthma is poorly controlled by the current standard of care. Ongoing studies using advanced molecular and immunological tools along with improved clinical classification show that severe asthma does not identify a specific patient phenotype, but rather includes patients with constant medical needs, whose pathobiologic and clinical characteristics vary widely. Accordingly, in recent clinical trials, therapies guided by specific patient characteristics have had better outcomes than previous therapies directed to any subject with a diagnosis of severe asthma. However, there are still significant gaps in our understanding of the full scope of this disease that hinder the development of effective treatments for all severe asthmatics. In this Review, we discuss our current state of knowledge regarding severe asthma, highlighting different molecular and immunological pathways that can be targeted for future therapeutic development. PMID:27367183

  15. Predicting fire severity using surface fuels and moisture

    Science.gov (United States)

    Pamela G. Sikkink; Robert E. Keane

    2012-01-01

    Fire severity classifications have been used extensively in fire management over the last 30 years to describe specific environmental or ecological impacts of fire on fuels, vegetation, wildlife, and soils in recently burned areas. New fire severity classifications need to be more objective, predictive, and ultimately more useful to fire management and planning. Our...

  16. Classification of different degrees of adiposity in sedentary rats

    Energy Technology Data Exchange (ETDEWEB)

    Leopoldo, A.S.; Lima-Leopoldo, A.P. [Departamento de Desportos, Centro de Educação Física e Esportes, Universidade Federal do Espírito Santo, Vitória, ES (Brazil); Nascimento, A.F.; Luvizotto, R.A.M.; Sugizaki, M.M. [Instituto de Ciências da Saúde, Universidade Federal do Mato Grosso, Sinop, MT (Brazil); Campos, D.H.S.; Silva, D.C.T. da [Departamento de Clínica Médica, Faculdade de Medicina, Universidade Estadual Paulista, Botucatu, SP (Brazil); Padovani, C.R. [Departamento de Bioestatística, Instituto de Biociências, Universidade Estadual Paulista, Botucatu, SP (Brazil); Cicogna, A.C. [Departamento de Clínica Médica, Faculdade de Medicina, Universidade Estadual Paulista, Botucatu, SP (Brazil)

    2016-02-23

    In experimental studies, several parameters, such as body weight, body mass index, adiposity index, and dual-energy X-ray absorptiometry, have commonly been used to demonstrate increased adiposity and investigate the mechanisms underlying obesity and sedentary lifestyles. However, these investigations have not classified the degree of adiposity nor defined adiposity categories for rats, such as normal, overweight, and obese. The aim of the study was to characterize the degree of adiposity in rats fed a high-fat diet using cluster analysis and to create adiposity intervals in an experimental model of obesity. Thirty-day-old male Wistar rats were fed a normal (n=41) or a high-fat (n=43) diet for 15 weeks. Obesity was defined based on the adiposity index; and the degree of adiposity was evaluated using cluster analysis. Cluster analysis allowed the rats to be classified into two groups (overweight and obese). The obese group displayed significantly higher total body fat and a higher adiposity index compared with those of the overweight group. No differences in systolic blood pressure or nonesterified fatty acid, glucose, total cholesterol, or triglyceride levels were observed between the obese and overweight groups. The adiposity index of the obese group was positively correlated with final body weight, total body fat, and leptin levels. Despite the classification of sedentary rats into overweight and obese groups, it was not possible to identify differences in the comorbidities between the two groups.

  17. Classification of different degrees of adiposity in sedentary rats

    International Nuclear Information System (INIS)

    Leopoldo, A.S.; Lima-Leopoldo, A.P.; Nascimento, A.F.; Luvizotto, R.A.M.; Sugizaki, M.M.; Campos, D.H.S.; Silva, D.C.T. da; Padovani, C.R.; Cicogna, A.C.

    2016-01-01

    In experimental studies, several parameters, such as body weight, body mass index, adiposity index, and dual-energy X-ray absorptiometry, have commonly been used to demonstrate increased adiposity and investigate the mechanisms underlying obesity and sedentary lifestyles. However, these investigations have not classified the degree of adiposity nor defined adiposity categories for rats, such as normal, overweight, and obese. The aim of the study was to characterize the degree of adiposity in rats fed a high-fat diet using cluster analysis and to create adiposity intervals in an experimental model of obesity. Thirty-day-old male Wistar rats were fed a normal (n=41) or a high-fat (n=43) diet for 15 weeks. Obesity was defined based on the adiposity index; and the degree of adiposity was evaluated using cluster analysis. Cluster analysis allowed the rats to be classified into two groups (overweight and obese). The obese group displayed significantly higher total body fat and a higher adiposity index compared with those of the overweight group. No differences in systolic blood pressure or nonesterified fatty acid, glucose, total cholesterol, or triglyceride levels were observed between the obese and overweight groups. The adiposity index of the obese group was positively correlated with final body weight, total body fat, and leptin levels. Despite the classification of sedentary rats into overweight and obese groups, it was not possible to identify differences in the comorbidities between the two groups

  18. Fuzzy set classifier for waste classification tracking

    International Nuclear Information System (INIS)

    Gavel, D.T.

    1992-01-01

    We have developed an expert system based on fuzzy logic theory to fuse the data from multiple sensors and make classification decisions for objects in a waste reprocessing stream. Fuzzy set theory has been applied in decision and control applications with some success, particularly by the Japanese. We have found that the fuzzy logic system is rather easy to design and train, a feature that can cut development costs considerably. With proper training, the classification accuracy is quite high. We performed several tests sorting radioactive test samples using a gamma spectrometer to compare fuzzy logic to more conventional sorting schemes

  19. Minimum Error Entropy Classification

    CERN Document Server

    Marques de Sá, Joaquim P; Santos, Jorge M F; Alexandre, Luís A

    2013-01-01

    This book explains the minimum error entropy (MEE) concept applied to data classification machines. Theoretical results on the inner workings of the MEE concept, in its application to solving a variety of classification problems, are presented in the wider realm of risk functionals. Researchers and practitioners also find in the book a detailed presentation of practical data classifiers using MEE. These include multi‐layer perceptrons, recurrent neural networks, complexvalued neural networks, modular neural networks, and decision trees. A clustering algorithm using a MEE‐like concept is also presented. Examples, tests, evaluation experiments and comparison with similar machines using classic approaches, complement the descriptions.

  20. Classification of iconic images

    OpenAIRE

    Zrianina, Mariia; Kopf, Stephan

    2016-01-01

    Iconic images represent an abstract topic and use a presentation that is intuitively understood within a certain cultural context. For example, the abstract topic “global warming” may be represented by a polar bear standing alone on an ice floe. Such images are widely used in media and their automatic classification can help to identify high-level semantic concepts. This paper presents a system for the classification of iconic images. It uses a variation of the Bag of Visual Words approach wi...

  1. Casemix classification systems.

    Science.gov (United States)

    Fetter, R B

    1999-01-01

    The idea of using casemix classification to manage hospital services is not new, but has been limited by available technology. It was not until after the introduction of Medicare in the United States in 1965 that serious attempts were made to measure hospital production in order to contain spiralling costs. This resulted in a system of casemix classification known as diagnosis related groups (DRGs). This paper traces the development of DRGs and their evolution from the initial version to the All Patient Refined DRGs developed in 1991.

  2. Information gathering for CLP classification

    Directory of Open Access Journals (Sweden)

    Ida Marcello

    2011-01-01

    Full Text Available Regulation 1272/2008 includes provisions for two types of classification: harmonised classification and self-classification. The harmonised classification of substances is decided at Community level and a list of harmonised classifications is included in the Annex VI of the classification, labelling and packaging Regulation (CLP. If a chemical substance is not included in the harmonised classification list it must be self-classified, based on available information, according to the requirements of Annex I of the CLP Regulation. CLP appoints that the harmonised classification will be performed for carcinogenic, mutagenic or toxic to reproduction substances (CMR substances and for respiratory sensitisers category 1 and for other hazard classes on a case-by-case basis. The first step of classification is the gathering of available and relevant information. This paper presents the procedure for gathering information and to obtain data. The data quality is also discussed.

  3. The paradox of atheoretical classification

    DEFF Research Database (Denmark)

    Hjørland, Birger

    2016-01-01

    A distinction can be made between “artificial classifications” and “natural classifications,” where artificial classifications may adequately serve some limited purposes, but natural classifications are overall most fruitful by allowing inference and thus many different purposes. There is strong...... support for the view that a natural classification should be based on a theory (and, of course, that the most fruitful theory provides the most fruitful classification). Nevertheless, atheoretical (or “descriptive”) classifications are often produced. Paradoxically, atheoretical classifications may...... be very successful. The best example of a successful “atheoretical” classification is probably the prestigious Diagnostic and Statistical Manual of Mental Disorders (DSM) since its third edition from 1980. Based on such successes one may ask: Should the claim that classifications ideally are natural...

  4. Computer Aided Design for Soil Classification Relational Database ...

    African Journals Online (AJOL)

    unique firstlady

    engineering, several developers were asked what rules they applied to identify ... classification is actually a part of all good science. As Michalski ... by a large number of soil scientists. .... and use. The calculus relational database processing is.

  5. DTI measurements for Alzheimer’s classification

    Science.gov (United States)

    Maggipinto, Tommaso; Bellotti, Roberto; Amoroso, Nicola; Diacono, Domenico; Donvito, Giacinto; Lella, Eufemia; Monaco, Alfonso; Antonella Scelsi, Marzia; Tangaro, Sabina; Disease Neuroimaging Initiative, Alzheimer's.

    2017-03-01

    Diffusion tensor imaging (DTI) is a promising imaging technique that provides insight into white matter microstructure integrity and it has greatly helped identifying white matter regions affected by Alzheimer’s disease (AD) in its early stages. DTI can therefore be a valuable source of information when designing machine-learning strategies to discriminate between healthy control (HC) subjects, AD patients and subjects with mild cognitive impairment (MCI). Nonetheless, several studies have reported so far conflicting results, especially because of the adoption of biased feature selection strategies. In this paper we firstly analyzed DTI scans of 150 subjects from the Alzheimer’s disease neuroimaging initiative (ADNI) database. We measured a significant effect of the feature selection bias on the classification performance (p-value  informative content provided by DTI measurements for AD classification. Classification performances and biological insight, concerning brain regions related to the disease, provided by cross-validation analysis were both confirmed on the independent test.

  6. An ordinal classification approach for CTG categorization.

    Science.gov (United States)

    Georgoulas, George; Karvelis, Petros; Gavrilis, Dimitris; Stylios, Chrysostomos D; Nikolakopoulos, George

    2017-07-01

    Evaluation of cardiotocogram (CTG) is a standard approach employed during pregnancy and delivery. But, its interpretation requires high level expertise to decide whether the recording is Normal, Suspicious or Pathological. Therefore, a number of attempts have been carried out over the past three decades for development automated sophisticated systems. These systems are usually (multiclass) classification systems that assign a category to the respective CTG. However most of these systems usually do not take into consideration the natural ordering of the categories associated with CTG recordings. In this work, an algorithm that explicitly takes into consideration the ordering of CTG categories, based on binary decomposition method, is investigated. Achieved results, using as a base classifier the C4.5 decision tree classifier, prove that the ordinal classification approach is marginally better than the traditional multiclass classification approach, which utilizes the standard C4.5 algorithm for several performance criteria.

  7. Weight Gain during Pregnancy

    Science.gov (United States)

    ... Global Map Premature Birth Report Cards Careers Archives Pregnancy Before or between pregnancies Nutrition, weight & fitness Prenatal ... fitness > Weight gain during pregnancy Weight gain during pregnancy E-mail to a friend Please fill in ...

  8. Should I Gain Weight?

    Science.gov (United States)

    ... Videos for Educators Search English Español Should I Gain Weight? KidsHealth / For Teens / Should I Gain Weight? ... something about it. Why Do People Want to Gain Weight? Some of the reasons people give for ...

  9. Evaluación de la severidad, proporcionalidad y riesgo de muerte de recién nacidos de muy bajo peso con restricción del crecimiento fetal: análisis multicéntrico sudamericano An assessment of the severity, proportionality and risk of mortality of very low birth weight infants with fetal growth restriction: a multicenter South American analysis

    Directory of Open Access Journals (Sweden)

    Carlos Grandi

    2005-06-01

    Full Text Available OBJETIVOS: 1 evaluar la severidad y la proporcionalidad de los PEG para diferentes grados de prematurez; 2 estimar el riesgo de mortalidad de los PEG según la severidad y proporcionalidad. MATERIAL Y MÉTODOS: Diseño observacional y analítico. Población: todos los recién nacidos de muy bajo peso (RNMPB entre 25 y 36 semanas que mantiene el grupo NEOCOSUR (n = 1.518. Índices antropométricos: a peso de nacimiento (PN 0,55 y la transformación z del índice ponderal (Ponderal Index, PI = g/cm³ x 100. Restricción del crecimiento intrauterino (RCIU asimétrico: score z OBJECTIVES: To evaluate the clinical severity and proportionality of small for gestational age, very low birth weight neonates (< 1,500 g and to estimate the neonatal mortality risk associated with the condition of being small for gestational age according to the degree of severity and proportionality. METHODS: Observational design. All of the NEOCOSUR Collaborative Group's very low birth weight infants (25-36 weeks' gestation were included (n = 1,518. Anthropometric indices: birth weight < 3rd and 10th percentile. Severity (fetal growth ratio = observed weight/mean birth weight for gestational age; no growth restriction: fetal growth ratio 0.90-1.10, mild: fetal growth ratio 0.80-0.89, moderate: fetal growth ratio 0.75-0.79 and severe: fetal growth ratio < 0.75. Proportionality: coefficient of bimodality and z score for ponderal index (PI = g/cm³ *100. Neonatal mortality until discharge. RESULTS: < 3rd percentile: 13.5% (p < 0.001; < 10th percentile: 31% (p < 0.001; fetal growth ratio: 0.90±0.21 (p < 0.001, mild restriction: 20.8%, moderate restriction: 8.7% and severe restriction: 32.6%. Coefficient of bimodality: 0.53; PI z score < -1: 8%. Maternal hypertensive disease was systematically associated with being small for gestational age (aOR 1.20, 95% CI 0.86-1.67, fetal growth ratio < 0.89 (aOR 1.71, 1.24-2.36 and PI z score < -1 (aOR 1.60, 1.03-2.41. Adjusted odds ratios

  10. Ecosystem classification, Chapter 2

    Science.gov (United States)

    M.J. Robin-Abbott; L.H. Pardo

    2011-01-01

    The ecosystem classification in this report is based on the ecoregions developed through the Commission for Environmental Cooperation (CEC) for North America (CEC 1997). Only ecosystems that occur in the United States are included. CEC ecoregions are described, with slight modifications, below (CEC 1997) and shown in Figures 2.1 and 2.2. We chose this ecosystem...

  11. The classification of phocomelia.

    Science.gov (United States)

    Tytherleigh-Strong, G; Hooper, G

    2003-06-01

    We studied 24 patients with 44 phocomelic upper limbs. Only 11 limbs could be grouped in the classification system of Frantz and O' Rahilly. The non-classifiable limbs were further studied and their characteristics identified. It is confirmed that phocomelia is not an intercalary defect.

  12. Principles for ecological classification

    Science.gov (United States)

    Dennis H. Grossman; Patrick Bourgeron; Wolf-Dieter N. Busch; David T. Cleland; William Platts; G. Ray; C. Robins; Gary Roloff

    1999-01-01

    The principal purpose of any classification is to relate common properties among different entities to facilitate understanding of evolutionary and adaptive processes. In the context of this volume, it is to facilitate ecosystem stewardship, i.e., to help support ecosystem conservation and management objectives.

  13. Mimicking human texture classification

    NARCIS (Netherlands)

    Rogowitz, B.E.; van Rikxoort, Eva M.; van den Broek, Egon; Pappas, T.N.; Schouten, Theo E.; Daly, S.J.

    2005-01-01

    In an attempt to mimic human (colorful) texture classification by a clustering algorithm three lines of research have been encountered, in which as test set 180 texture images (both their color and gray-scale equivalent) were drawn from the OuTex and VisTex databases. First, a k-means algorithm was

  14. Classification, confusion and misclassification

    African Journals Online (AJOL)

    The classification of objects and phenomena in science and nature has fascinated academics since Carl Linnaeus, the Swedish botanist and zoologist, created his binomial description of living things in the 1700s and probably long before in accounts of others in textbooks long since gone. It must have concerned human ...

  15. Classifications in popular music

    NARCIS (Netherlands)

    van Venrooij, A.; Schmutz, V.; Wright, J.D.

    2015-01-01

    The categorical system of popular music, such as genre categories, is a highly differentiated and dynamic classification system. In this article we present work that studies different aspects of these categorical systems in popular music. Following the work of Paul DiMaggio, we focus on four

  16. Shark Teeth Classification

    Science.gov (United States)

    Brown, Tom; Creel, Sally; Lee, Velda

    2009-01-01

    On a recent autumn afternoon at Harmony Leland Elementary in Mableton, Georgia, students in a fifth-grade science class investigated the essential process of classification--the act of putting things into groups according to some common characteristics or attributes. While they may have honed these skills earlier in the week by grouping their own…

  17. Text document classification

    Czech Academy of Sciences Publication Activity Database

    Novovičová, Jana

    č. 62 (2005), s. 53-54 ISSN 0926-4981 R&D Projects: GA AV ČR IAA2075302; GA AV ČR KSK1019101; GA MŠk 1M0572 Institutional research plan: CEZ:AV0Z10750506 Keywords : document representation * categorization * classification Subject RIV: BD - Theory of Information

  18. Classification in Medical Imaging

    DEFF Research Database (Denmark)

    Chen, Chen

    Classification is extensively used in the context of medical image analysis for the purpose of diagnosis or prognosis. In order to classify image content correctly, one needs to extract efficient features with discriminative properties and build classifiers based on these features. In addition...... on characterizing human faces and emphysema disease in lung CT images....

  19. Improving Student Question Classification

    Science.gov (United States)

    Heiner, Cecily; Zachary, Joseph L.

    2009-01-01

    Students in introductory programming classes often articulate their questions and information needs incompletely. Consequently, the automatic classification of student questions to provide automated tutorial responses is a challenging problem. This paper analyzes 411 questions from an introductory Java programming course by reducing the natural…

  20. NOUN CLASSIFICATION IN ESAHIE

    African Journals Online (AJOL)

    The present work deals with noun classification in Esahie (Kwa, Niger ... phonological information influences the noun (form) class system of Esahie. ... between noun classes and (grammatical) Gender is interrogated (in the light of ..... the (A) argument6 precedes the verb and the (P) argument7 follows the verb in a simple.

  1. Dynamic Latent Classification Model

    DEFF Research Database (Denmark)

    Zhong, Shengtong; Martínez, Ana M.; Nielsen, Thomas Dyhre

    as possible. Motivated by this problem setting, we propose a generative model for dynamic classification in continuous domains. At each time point the model can be seen as combining a naive Bayes model with a mixture of factor analyzers (FA). The latent variables of the FA are used to capture the dynamics...

  2. Classification of myocardial infarction

    DEFF Research Database (Denmark)

    Saaby, Lotte; Poulsen, Tina Svenstrup; Hosbond, Susanne Elisabeth

    2013-01-01

    The classification of myocardial infarction into 5 types was introduced in 2007 as an important component of the universal definition. In contrast to the plaque rupture-related type 1 myocardial infarction, type 2 myocardial infarction is considered to be caused by an imbalance between demand...

  3. Event Classification using Concepts

    NARCIS (Netherlands)

    Boer, M.H.T. de; Schutte, K.; Kraaij, W.

    2013-01-01

    The semantic gap is one of the challenges in the GOOSE project. In this paper a Semantic Event Classification (SEC) system is proposed as an initial step in tackling the semantic gap challenge in the GOOSE project. This system uses semantic text analysis, multiple feature detectors using the BoW

  4. [Classification of Colombian children with malnutrition according to NCHS reference or WHO standard].

    Science.gov (United States)

    Velásquez, Claudia; Bermúdez, Juliana; Echeverri, Claudia; Estrada, Alejandro

    2011-12-01

    A descriptive study was conducted to evaluate the concordance of National Center for Health Statistics reference (NCHS) used to classify undernourished children from Colombia with the WHO Child Growth Standards. We used data from children aged 6 to 59 months with acute malnutrition (Z Infantil" nutrition program in Colombia. Indicators height-for-age, weight for-height were analyzed when they were admitted to the hospital and weight for-height leaving the hospital. A statistical method used to compare means was T-student. Correlation coefficient intraclass (CCI) and Kappa index evaluated the concordance between NCHS and OMS; McNemar method evaluated the changes on the nutritional classification for children according to growth devices used. Of the total number of children classified as normal by NCHS, 10.4% were classified as stunted by WHO. 64% of the children admitted to the hospital presented acute malnutrition according to NCHS, of these 44,8% presented severe emaciation according to OMS, indeed severe emaciation increased of 36,0% to 63,3% using OMS. 5% of children leaving the hospital could need to stay more days if they had been evaluated with OMS. Growth devices shown high concordance in height-for-age (CCI = 0,988; k= 0,866) and weight for-height (CCI = 0,901; k = 0,578). Concluded that OMS growth standards classified more malnourished children and more severe states, in addition more malnourished children could be hospitalized and they could stay more days.

  5. Classification of diabetic foot ulcers.

    Science.gov (United States)

    Game, Frances

    2016-01-01

    It is known that the relative importance of factors involved in the development of diabetic foot problems can vary in both their presence and severity between patients and lesions. This may be one of the reasons why outcomes seem to vary centre to centre and why some treatments may seem more effective in some people than others. There is a need therefore to classify and describe lesions of the foot in patients with diabetes in a manner that is agreed across all communities but is simple to use in clinical practice. No single system is currently in widespread use, although a number have been published. Not all are well validated outside the system from which they were derived, and it has not always been made clear the clinical purposes to which such classifications should be put to use, whether that be for research, clinical description in routine clinical care or audit. Here the currently published classification systems, their validation in clinical practice, whether they were designed for research, audit or clinical care, and the strengths and weaknesses of each are explored. Copyright © 2016 John Wiley & Sons, Ltd.

  6. Voice based gender classification using machine learning

    Science.gov (United States)

    Raahul, A.; Sapthagiri, R.; Pankaj, K.; Vijayarajan, V.

    2017-11-01

    Gender identification is one of the major problem speech analysis today. Tracing the gender from acoustic data i.e., pitch, median, frequency etc. Machine learning gives promising results for classification problem in all the research domains. There are several performance metrics to evaluate algorithms of an area. Our Comparative model algorithm for evaluating 5 different machine learning algorithms based on eight different metrics in gender classification from acoustic data. Agenda is to identify gender, with five different algorithms: Linear Discriminant Analysis (LDA), K-Nearest Neighbour (KNN), Classification and Regression Trees (CART), Random Forest (RF), and Support Vector Machine (SVM) on basis of eight different metrics. The main parameter in evaluating any algorithms is its performance. Misclassification rate must be less in classification problems, which says that the accuracy rate must be high. Location and gender of the person have become very crucial in economic markets in the form of AdSense. Here with this comparative model algorithm, we are trying to assess the different ML algorithms and find the best fit for gender classification of acoustic data.

  7. A comparative evaluation of sequence classification programs

    Directory of Open Access Journals (Sweden)

    Bazinet Adam L

    2012-05-01

    Full Text Available Abstract Background A fundamental problem in modern genomics is to taxonomically or functionally classify DNA sequence fragments derived from environmental sampling (i.e., metagenomics. Several different methods have been proposed for doing this effectively and efficiently, and many have been implemented in software. In addition to varying their basic algorithmic approach to classification, some methods screen sequence reads for ’barcoding genes’ like 16S rRNA, or various types of protein-coding genes. Due to the sheer number and complexity of methods, it can be difficult for a researcher to choose one that is well-suited for a particular analysis. Results We divided the very large number of programs that have been released in recent years for solving the sequence classification problem into three main categories based on the general algorithm they use to compare a query sequence against a database of sequences. We also evaluated the performance of the leading programs in each category on data sets whose taxonomic and functional composition is known. Conclusions We found significant variability in classification accuracy, precision, and resource consumption of sequence classification programs when used to analyze various metagenomics data sets. However, we observe some general trends and patterns that will be useful to researchers who use sequence classification programs.

  8. Random forests for classification in ecology

    Science.gov (United States)

    Cutler, D.R.; Edwards, T.C.; Beard, K.H.; Cutler, A.; Hess, K.T.; Gibson, J.; Lawler, J.J.

    2007-01-01

    Classification procedures are some of the most widely used statistical methods in ecology. Random forests (RF) is a new and powerful statistical classifier that is well established in other disciplines but is relatively unknown in ecology. Advantages of RF compared to other statistical classifiers include (1) very high classification accuracy; (2) a novel method of determining variable importance; (3) ability to model complex interactions among predictor variables; (4) flexibility to perform several types of statistical data analysis, including regression, classification, survival analysis, and unsupervised learning; and (5) an algorithm for imputing missing values. We compared the accuracies of RF and four other commonly used statistical classifiers using data on invasive plant species presence in Lava Beds National Monument, California, USA, rare lichen species presence in the Pacific Northwest, USA, and nest sites for cavity nesting birds in the Uinta Mountains, Utah, USA. We observed high classification accuracy in all applications as measured by cross-validation and, in the case of the lichen data, by independent test data, when comparing RF to other common classification methods. We also observed that the variables that RF identified as most important for classifying invasive plant species coincided with expectations based on the literature. ?? 2007 by the Ecological Society of America.

  9. A proposed United States resource classification system

    International Nuclear Information System (INIS)

    Masters, C.D.

    1980-01-01

    Energy is a world-wide problem calling for world-wide communication to resolve the many supply and distribution problems. Essential to a communication problem are a definition and comparability of elements being communicated. The US Geological Survey, with the co-operation of the US Bureau of Mines and the US Department of Energy, has devised a classification system for all mineral resources, the principles of which, it is felt, offer the possibility of world communication. At present several other systems, extant or under development (Potential Gas Committee of the USA, United Nations Resource Committee, and the American Society of Testing and Materials) are internally consistent and provide easy communication linkage. The system in use by the uranium community in the United States of America, however, ties resource quantities to forward-cost dollar values rendering them inconsistent with other classifications and therefore not comparable. This paper develops the rationale for the new USGS resource classification and notes its benefits relative to a forward-cost classification and its relationship specifically to other current classifications. (author)

  10. NEW CLASSIFICATION OF ECOPOLICES

    Directory of Open Access Journals (Sweden)

    VOROBYOV V. V.

    2016-09-01

    Full Text Available Problem statement. Ecopolices are the newest stage of the urban planning. They have to be consideredsuchas material and energy informational structures, included to the dynamic-evolutionary matrix netsofex change processes in the ecosystems. However, there are not made the ecopolice classifications, developing on suchapproaches basis. And this determined the topicality of the article. Analysis of publications on theoretical and applied aspects of the ecopolices formation showed, that the work on them is managed mainly in the context of the latest scientific and technological achievements in the various knowledge fields. These settlements are technocratic. They are connected with the morphology of space, network structures of regional and local natural ecosystems, without independent stability, can not exist without continuous man support. Another words, they do not work in with an ecopolices idea. It is come to a head for objective, symbiotic searching of ecopolices concept with the development of their classifications. Purpose statement is to develop the objective evidence for ecopolices and to propose their new classification. Conclusion. On the base of the ecopolices classification have to lie an elements correlation idea of their general plans and men activity type according with natural mechanism of accepting, reworking and transmission of material, energy and information between geo-ecosystems, planet, man, ecopolices material part and Cosmos. New ecopolices classification should be based on the principles of multi-dimensional, time-spaced symbiotic clarity with exchange ecosystem networks. The ecopolice function with this approach comes not from the subjective anthropocentric economy but from the holistic objective of Genesis paradigm. Or, otherwise - not from the Consequence, but from the Cause.

  11. Efficient Fingercode Classification

    Science.gov (United States)

    Sun, Hong-Wei; Law, Kwok-Yan; Gollmann, Dieter; Chung, Siu-Leung; Li, Jian-Bin; Sun, Jia-Guang

    In this paper, we present an efficient fingerprint classification algorithm which is an essential component in many critical security application systems e. g. systems in the e-government and e-finance domains. Fingerprint identification is one of the most important security requirements in homeland security systems such as personnel screening and anti-money laundering. The problem of fingerprint identification involves searching (matching) the fingerprint of a person against each of the fingerprints of all registered persons. To enhance performance and reliability, a common approach is to reduce the search space by firstly classifying the fingerprints and then performing the search in the respective class. Jain et al. proposed a fingerprint classification algorithm based on a two-stage classifier, which uses a K-nearest neighbor classifier in its first stage. The fingerprint classification algorithm is based on the fingercode representation which is an encoding of fingerprints that has been demonstrated to be an effective fingerprint biometric scheme because of its ability to capture both local and global details in a fingerprint image. We enhance this approach by improving the efficiency of the K-nearest neighbor classifier for fingercode-based fingerprint classification. Our research firstly investigates the various fast search algorithms in vector quantization (VQ) and the potential application in fingerprint classification, and then proposes two efficient algorithms based on the pyramid-based search algorithms in VQ. Experimental results on DB1 of FVC 2004 demonstrate that our algorithms can outperform the full search algorithm and the original pyramid-based search algorithms in terms of computational efficiency without sacrificing accuracy.

  12. Differential Classification of Dementia

    Directory of Open Access Journals (Sweden)

    E. Mohr

    1995-01-01

    Full Text Available In the absence of biological markers, dementia classification remains complex both in terms of characterization as well as early detection of the presence or absence of dementing symptoms, particularly in diseases with possible secondary dementia. An empirical, statistical approach using neuropsychological measures was therefore developed to distinguish demented from non-demented patients and to identify differential patterns of cognitive dysfunction in neurodegenerative disease. Age-scaled neurobehavioral test results (Wechsler Adult Intelligence Scale—Revised and Wechsler Memory Scale from Alzheimer's (AD and Huntington's (HD patients, matched for intellectual disability, as well as normal controls were used to derive a classification formula. Stepwise discriminant analysis accurately (99% correct distinguished controls from demented patients, and separated the two patient groups (79% correct. Variables discriminating between HD and AD patient groups consisted of complex psychomotor tasks, visuospatial function, attention and memory. The reliability of the classification formula was demonstrated with a new, independent sample of AD and HD patients which yielded virtually identical results (classification accuracy for dementia: 96%; AD versus HD: 78%. To validate the formula, the discriminant function was applied to Parkinson's (PD patients, 38% of whom were classified as demented. The validity of the classification was demonstrated by significant PD subgroup differences on measures of dementia not included in the discriminant function. Moreover, a majority of demented PD patients (65% were classified as having an HD-like pattern of cognitive deficits, in line with previous reports of the subcortical nature of PD dementia. This approach may thus be useful in classifying presence or absence of dementia and in discriminating between dementia subtypes in cases of secondary or coincidental dementia.

  13. Classification of feeding and eating disorders: review of evidence and proposals for ICD-11

    Science.gov (United States)

    UHER, RUDOLF; RUTTER, MICHAEL

    2012-01-01

    Current classification of eating disorders is failing to classify most clinical presentations; ignores continuities between child, adolescent and adult manifestations; and requires frequent changes of diagnosis to accommodate the natural course of these disorders. The classification is divorced from clinical practice, and investigators of clinical trials have felt compelled to introduce unsystematic modifications. Classification of feeding and eating disorders in ICD-11 requires substantial changes to remediate the shortcomings. We review evidence on the developmental and cross-cultural differences and continuities, course and distinctive features of feeding and eating disorders. We make the following recommendations: a) feeding and eating disorders should be merged into a single grouping with categories applicable across age groups; b) the category of anorexia nervosa should be broadened through dropping the requirement for amenorrhoea, extending the weight criterion to any significant underweight, and extending the cognitive criterion to include developmentally and culturally relevant presentations; c) a severity qualifier “with dangerously low body weight” should distinguish the severe cases of anorexia nervosa that carry the riskiest prognosis; d) bulimia nervosa should be extended to include subjective binge eating; e) binge eating disorder should be included as a specific category defined by subjective or objective binge eating in the absence of regular compensatory behaviour; f) combined eating disorder should classify subjects who sequentially or concurrently fulfil criteria for both anorexia and bulimia nervosa; g) avoidant/restrictive food intake disorder should classify restricted food intake in children or adults that is not accompanied by body weight and shape related psychopathology; h) a uniform minimum duration criterion of four weeks should apply. PMID:22654933

  14. 78 FR 54970 - Cotton Futures Classification: Optional Classification Procedure

    Science.gov (United States)

    2013-09-09

    ... Service 7 CFR Part 27 [AMS-CN-13-0043] RIN 0581-AD33 Cotton Futures Classification: Optional Classification Procedure AGENCY: Agricultural Marketing Service, USDA. ACTION: Proposed rule. SUMMARY: The... optional cotton futures classification procedure--identified and known as ``registration'' by the U.S...

  15. Weighted Polynomial Approximation for Automated Detection of Inspiratory Flow Limitation

    Directory of Open Access Journals (Sweden)

    Sheng-Cheng Huang

    2017-01-01

    Full Text Available Inspiratory flow limitation (IFL is a critical symptom of sleep breathing disorders. A characteristic flattened flow-time curve indicates the presence of highest resistance flow limitation. This study involved investigating a real-time algorithm for detecting IFL during sleep. Three categories of inspiratory flow shape were collected from previous studies for use as a development set. Of these, 16 cases were labeled as non-IFL and 78 as IFL which were further categorized into minor level (20 cases and severe level (58 cases of obstruction. In this study, algorithms using polynomial functions were proposed for extracting the features of IFL. Methods using first- to third-order polynomial approximations were applied to calculate the fitting curve to obtain the mean absolute error. The proposed algorithm is described by the weighted third-order (w.3rd-order polynomial function. For validation, a total of 1,093 inspiratory breaths were acquired as a test set. The accuracy levels of the classifications produced by the presented feature detection methods were analyzed, and the performance levels were compared using a misclassification cobweb. According to the results, the algorithm using the w.3rd-order polynomial approximation achieved an accuracy of 94.14% for IFL classification. We concluded that this algorithm achieved effective automatic IFL detection during sleep.

  16. 32 CFR 2700.22 - Classification guides.

    Science.gov (United States)

    2010-07-01

    ... SECURITY INFORMATION REGULATIONS Derivative Classification § 2700.22 Classification guides. OMSN shall... direct derivative classification, shall identify the information to be protected in specific and uniform...

  17. Skew-signings of positive weighted digraphs

    Directory of Open Access Journals (Sweden)

    Kawtar Attas

    2018-07-01

    Full Text Available An arc-weighted digraph is a pair (D , ω where D is a digraph and ω is an arc-weight function that assigns to each arc u v of D a nonzero real number ω (u v . Given an arc-weighted digraph (D , ω with vertices v 1 , … , v n , the weighted adjacency matrix of (D , ω is defined as the n × n matrix A (D , ω = [ a i j ] where a i j = ω ( v i v j if v i v j is an arc of D , and 0 otherwise. Let (D , ω be a positive arc-weighted digraph and assume that D is loopless and symmetric. A skew-signing of (D , ω is an arc-weight function ω ′ such that ω ′ (u v = ± ω (u v and ω ′ (u v ω ′ (v u < 0 for every arc u v of D . In this paper, we give necessary and sufficient conditions under which the characteristic polynomial of A (D , ω ′ is the same for all skew-signings ω ′ of (D , ω . Our main theorem generalizes a result of Cavers et al. (2012 about skew-adjacency matrices of graphs. Keywords: Arc-weighted digraphs, Skew-signing of a digraph, Weighted adjacency matrix, Mathematics Subject Classification: 05C22, 05C31, 05C50

  18. Cesarean deliveries and maternal weight retention.

    Science.gov (United States)

    Kapinos, Kandice A; Yakusheva, Olga; Weiss, Marianne

    2017-10-04

    Cesarean delivery accounts for nearly one-third of all births in the U.S. and contributes to an additional $38 billion in healthcare costs each year. Although Cesarean delivery has a long record of improving maternal and neonatal mortality and morbidity, increased utilization over time has yielded public health concerns and calls for reductions. Observational evidence suggests Cesarean delivery is associated with increased maternal postpartum weight, which may have significant implications for the obesity epidemic. Previous literature, however, typically does not address selection biases stemming from correlations of pre-pregnancy weight and reproductive health with Cesarean delivery. We used fetal malpresentation as a natural experiment as it predicts Cesarean delivery but is uncorrelated with pre-pregnancy weight or maternal health. We used hospital administrative data (including fields used in vital birth record) from the state of Wisconsin from 2006 to 2013 to create a sample of mothers with at least two births. Using propensity score methods, we compared maternal weight prior to the second pregnancy of mothers who delivered via Cesarean due to fetal malpresentation to mothers who deliver vaginally. We found no evidence that Cesarean delivery in the first pregnancy causally leads to greater maternal weight, BMI, or movement to a higher BMI classification prior to the second pregnancy. After accounting for correlations between pre-pregnancy weight, gestational weight gain, and mode of delivery, there is no evidence of a causal link between Cesarean delivery and maternal weight retention.

  19. Mechanisms of Weight Regain following Weight Loss.

    Science.gov (United States)

    Blomain, Erik Scott; Dirhan, Dara Anne; Valentino, Michael Anthony; Kim, Gilbert Won; Waldman, Scott Arthur

    2013-01-01

    Obesity is a world-wide pandemic and its incidence is on the rise along with associated comorbidities. Currently, there are few effective therapies to combat obesity. The use of lifestyle modification therapy, namely, improvements in diet and exercise, is preferable over bariatric surgery or pharmacotherapy due to surgical risks and issues with drug efficacy and safety. Although they are initially successful in producing weight loss, such lifestyle intervention strategies are generally unsuccessful in achieving long-term weight maintenance, with the vast majority of obese patients regaining their lost weight during followup. Recently, various compensatory mechanisms have been elucidated by which the body may oppose new weight loss, and this compensation may result in weight regain back to the obese baseline. The present review summarizes the available evidence on these compensatory mechanisms, with a focus on weight loss-induced changes in energy expenditure, neuroendocrine pathways, nutrient metabolism, and gut physiology. These findings have added a major focus to the field of antiobesity research. In addition to investigating pathways that induce weight loss, the present work also focuses on pathways that may instead prevent weight regain. Such strategies will be necessary for improving long-term weight loss maintenance and outcomes for patients who struggle with obesity.

  20. Preliminary Research on Grassland Fine-classification Based on MODIS

    International Nuclear Information System (INIS)

    Hu, Z W; Zhang, S; Yu, X Y; Wang, X S

    2014-01-01

    Grassland ecosystem is important for climatic regulation, maintaining the soil and water. Research on the grassland monitoring method could provide effective reference for grassland resource investigation. In this study, we used the vegetation index method for grassland classification. There are several types of climate in China. Therefore, we need to use China's Main Climate Zone Maps and divide the study region into four climate zones. Based on grassland classification system of the first nation-wide grass resource survey in China, we established a new grassland classification system which is only suitable for this research. We used MODIS images as the basic data resources, and use the expert classifier method to perform grassland classification. Based on the 1:1,000,000 Grassland Resource Map of China, we obtained the basic distribution of all the grassland types and selected 20 samples evenly distributed in each type, then used NDVI/EVI product to summarize different spectral features of different grassland types. Finally, we introduced other classification auxiliary data, such as elevation, accumulate temperature (AT), humidity index (HI) and rainfall. China's nation-wide grassland classification map is resulted by merging the grassland in different climate zone. The overall classification accuracy is 60.4%. The result indicated that expert classifier is proper for national wide grassland classification, but the classification accuracy need to be improved

  1. Textural features for image classification

    Science.gov (United States)

    Haralick, R. M.; Dinstein, I.; Shanmugam, K.

    1973-01-01

    Description of some easily computable textural features based on gray-tone spatial dependances, and illustration of their application in category-identification tasks of three different kinds of image data - namely, photomicrographs of five kinds of sandstones, 1:20,000 panchromatic aerial photographs of eight land-use categories, and ERTS multispectral imagery containing several land-use categories. Two kinds of decision rules are used - one for which the decision regions are convex polyhedra (a piecewise-linear decision rule), and one for which the decision regions are rectangular parallelpipeds (a min-max decision rule). In each experiment the data set was divided into two parts, a training set and a test set. Test set identification accuracy is 89% for the photomicrographs, 82% for the aerial photographic imagery, and 83% for the satellite imagery. These results indicate that the easily computable textural features probably have a general applicability for a wide variety of image-classification applications.

  2. Biological signals classification and analysis

    CERN Document Server

    Kiasaleh, Kamran

    2015-01-01

    This authored monograph presents key aspects of signal processing analysis in the biomedical arena. Unlike wireless communication systems, biological entities produce signals with underlying nonlinear, chaotic nature that elude classification using the standard signal processing techniques, which have been developed over the past several decades for dealing primarily with standard communication systems. This book separates what is random from that which appears to be random, and yet is truly deterministic with random appearance. At its core, this work gives the reader a perspective on biomedical signals and the means to classify and process such signals. In particular, a review of random processes along with means to assess the behavior of random signals is also provided. The book also includes a general discussion of biological signals in order to demonstrate the inefficacy of the well-known techniques to correctly extract meaningful information from such signals. Finally, a thorough discussion of recently ...

  3. A review and analysis of neural networks for classification of remotely sensed multispectral imagery

    Science.gov (United States)

    Paola, Justin D.; Schowengerdt, Robert A.

    1993-01-01

    A literature survey and analysis of the use of neural networks for the classification of remotely sensed multispectral imagery is presented. As part of a brief mathematical review, the backpropagation algorithm, which is the most common method of training multi-layer networks, is discussed with an emphasis on its application to pattern recognition. The analysis is divided into five aspects of neural network classification: (1) input data preprocessing, structure, and encoding; (2) output encoding and extraction of classes; (3) network architecture, (4) training algorithms; and (5) comparisons to conventional classifiers. The advantages of the neural network method over traditional classifiers are its non-parametric nature, arbitrary decision boundary capabilities, easy adaptation to different types of data and input structures, fuzzy output values that can enhance classification, and good generalization for use with multiple images. The disadvantages of the method are slow training time, inconsistent results due to random initial weights, and the requirement of obscure initialization values (e.g., learning rate and hidden layer size). Possible techniques for ameliorating these problems are discussed. It is concluded that, although the neural network method has several unique capabilities, it will become a useful tool in remote sensing only if it is made faster, more predictable, and easier to use.

  4. IAEA Classification of Uranium Deposits

    International Nuclear Information System (INIS)

    Bruneton, Patrice

    2014-01-01

    Classifications of uranium deposits follow two general approaches, focusing on: • descriptive features such as the geotectonic position, the host rock type, the orebody morphology, …… : « geologic classification »; • or on genetic aspects: « genetic classification »

  5. Classification of Osteogenesis Imperfecta revisited

    NARCIS (Netherlands)

    van Dijk, F. S.; Pals, G.; van Rijn, R. R.; Nikkels, P. G. J.; Cobben, J. M.

    2010-01-01

    In 1979 Sillence proposed a classification of Osteogenesis Imperfecta (OI) in OI types I, II, III and IV. In 2004 and 2007 this classification was expanded with OI types V-VIII because of distinct clinical features and/or different causative gene mutations. We propose a revised classification of OI

  6. The future of general classification

    DEFF Research Database (Denmark)

    Mai, Jens Erik

    2013-01-01

    Discusses problems related to accessing multiple collections using a single retrieval language. Surveys the concepts of interoperability and switching language. Finds that mapping between more indexing languages always will be an approximation. Surveys the issues related to general classification...... and contrasts that to special classifications. Argues for the use of general classifications to provide access to collections nationally and internationally....

  7. EPA`s program for risk assessment guidelines: Cancer classification issues

    Energy Technology Data Exchange (ETDEWEB)

    Wiltse, J. [Environmental Protection Agency, Washington, DC (United States)

    1990-12-31

    Issues presented are related to classification of weight of evidence in cancer risk assessments. The focus in this paper is on lines of evidence used in constructing a conclusion about potential human carcinogenicity. The paper also discusses issues that are mistakenly addressed as classification issues but are really part of the risk assessment process. 2 figs.

  8. Proven Weight Loss Methods

    Science.gov (United States)

    Fact Sheet Proven Weight Loss Methods What can weight loss do for you? Losing weight can improve your health in a number of ways. It can lower ... at www.hormone.org/Spanish . Proven Weight Loss Methods Fact Sheet www.hormone.org

  9. 42 CFR 412.620 - Patient classification system.

    Science.gov (United States)

    2010-10-01

    ...-mix group classifications and weighting factors. We may periodically adjust the case-mix groups and... rehabilitation facilities into mutually exclusive case-mix groups. (2) For purposes of this subpart, case-mix... assessments under § 412.610(c)(1) are used to classify a Medicare patient into an appropriate case-mix group...

  10. A new classification scheme of plastic wastes based upon recycling labels.

    Science.gov (United States)

    Özkan, Kemal; Ergin, Semih; Işık, Şahin; Işıklı, Idil

    2015-01-01

    Since recycling of materials is widely assumed to be environmentally and economically beneficial, reliable sorting and processing of waste packaging materials such as plastics is very important for recycling with high efficiency. An automated system that can quickly categorize these materials is certainly needed for obtaining maximum classification while maintaining high throughput. In this paper, first of all, the photographs of the plastic bottles have been taken and several preprocessing steps were carried out. The first preprocessing step is to extract the plastic area of a bottle from the background. Then, the morphological image operations are implemented. These operations are edge detection, noise removal, hole removing, image enhancement, and image segmentation. These morphological operations can be generally defined in terms of the combinations of erosion and dilation. The effect of bottle color as well as label are eliminated using these operations. Secondly, the pixel-wise intensity values of the plastic bottle images have been used together with the most popular subspace and statistical feature extraction methods to construct the feature vectors in this study. Only three types of plastics are considered due to higher existence ratio of them than the other plastic types in the world. The decision mechanism consists of five different feature extraction methods including as Principal Component Analysis (PCA), Kernel PCA (KPCA), Fisher's Linear Discriminant Analysis (FLDA), Singular Value Decomposition (SVD) and Laplacian Eigenmaps (LEMAP) and uses a simple experimental setup with a camera and homogenous backlighting. Due to the giving global solution for a classification problem, Support Vector Machine (SVM) is selected to achieve the classification task and majority voting technique is used as the decision mechanism. This technique equally weights each classification result and assigns the given plastic object to the class that the most classification

  11. [Headache: classification and diagnosis].

    Science.gov (United States)

    Carbaat, P A T; Couturier, E G M

    2016-11-01

    There are many types of headache and, moreover, many people have different types of headache at the same time. Adequate treatment is possible only on the basis of the correct diagnosis. Technically and in terms of content the current diagnostics process for headache is based on the 'International Classification of Headache Disorders' (ICHD-3-beta) that was produced under the auspices of the International Headache Society. This classification is based on a distinction between primary and secondary headaches. The most common primary headache types are the tension type headache, migraine and the cluster headache. Application of uniform diagnostic concepts is essential to come to the most appropriate treatment of the various types of headache.

  12. Classification of hand eczema

    DEFF Research Database (Denmark)

    Agner, T; Aalto-Korte, K; Andersen, K E

    2015-01-01

    BACKGROUND: Classification of hand eczema (HE) is mandatory in epidemiological and clinical studies, and also important in clinical work. OBJECTIVES: The aim was to test a recently proposed classification system of HE in clinical practice in a prospective multicentre study. METHODS: Patients were...... recruited from nine different tertiary referral centres. All patients underwent examination by specialists in dermatology and were checked using relevant allergy testing. Patients were classified into one of the six diagnostic subgroups of HE: allergic contact dermatitis, irritant contact dermatitis, atopic...... system investigated in the present study was useful, being able to give an appropriate main diagnosis for 89% of HE patients, and for another 7% when using two main diagnoses. The fact that more than half of the patients had one or more additional diagnoses illustrates that HE is a multifactorial disease....

  13. Sound classification of dwellings

    DEFF Research Database (Denmark)

    Rasmussen, Birgit

    2012-01-01

    National schemes for sound classification of dwellings exist in more than ten countries in Europe, typically published as national standards. The schemes define quality classes reflecting different levels of acoustical comfort. Main criteria concern airborne and impact sound insulation between...... dwellings, facade sound insulation and installation noise. The schemes have been developed, implemented and revised gradually since the early 1990s. However, due to lack of coordination between countries, there are significant discrepancies, and new standards and revisions continue to increase the diversity...... is needed, and a European COST Action TU0901 "Integrating and Harmonizing Sound Insulation Aspects in Sustainable Urban Housing Constructions", has been established and runs 2009-2013, one of the main objectives being to prepare a proposal for a European sound classification scheme with a number of quality...

  14. Classification and regression trees

    CERN Document Server

    Breiman, Leo; Olshen, Richard A; Stone, Charles J

    1984-01-01

    The methodology used to construct tree structured rules is the focus of this monograph. Unlike many other statistical procedures, which moved from pencil and paper to calculators, this text's use of trees was unthinkable before computers. Both the practical and theoretical sides have been developed in the authors' study of tree methods. Classification and Regression Trees reflects these two sides, covering the use of trees as a data analysis method, and in a more mathematical framework, proving some of their fundamental properties.

  15. CLASSIFICATION OF CRIMINAL GROUPS

    OpenAIRE

    Natalia Romanova

    2013-01-01

    New types of criminal groups are emerging in modern society.  These types have their special criminal subculture. The research objective is to develop new parameters of classification of modern criminal groups, create a new typology of criminal groups and identify some features of their subculture. Research methodology is based on the system approach that includes using the method of analysis of documentary sources (materials of a criminal case), method of conversations with themembers of the...

  16. Decimal Classification Editions

    Directory of Open Access Journals (Sweden)

    Zenovia Niculescu

    2009-01-01

    Full Text Available The study approaches the evolution of Dewey Decimal Classification editions from the perspective of updating the terminology, reallocating and expanding the main and auxilary structure of Dewey indexing language. The comparative analysis of DDC editions emphasizes the efficiency of Dewey scheme from the point of view of improving the informational offer, through basic index terms, revised and developed, as well as valuing the auxilary notations.

  17. Decimal Classification Editions

    OpenAIRE

    Zenovia Niculescu

    2009-01-01

    The study approaches the evolution of Dewey Decimal Classification editions from the perspective of updating the terminology, reallocating and expanding the main and auxilary structure of Dewey indexing language. The comparative analysis of DDC editions emphasizes the efficiency of Dewey scheme from the point of view of improving the informational offer, through basic index terms, revised and developed, as well as valuing the auxilary notations.

  18. Disorder-specific predictive classification of adolescents with attention deficit hyperactivity disorder (ADHD relative to autism using structural magnetic resonance imaging.

    Directory of Open Access Journals (Sweden)

    Lena Lim

    Full Text Available Attention Deficit Hyperactivity Disorder (ADHD is a neurodevelopmental disorder, but diagnosed by subjective clinical and rating measures. The study's aim was to apply Gaussian process classification (GPC to grey matter (GM volumetric data, to assess whether individual ADHD adolescents can be accurately differentiated from healthy controls based on objective, brain structure measures and whether this is disorder-specific relative to autism spectrum disorder (ASD.Twenty-nine adolescent ADHD boys and 29 age-matched healthy and 19 boys with ASD were scanned. GPC was applied to make disorder-specific predictions of ADHD diagnostic status based on individual brain structure patterns. In addition, voxel-based morphometry (VBM analysis tested for traditional univariate group level differences in GM.The pattern of GM correctly classified 75.9% of patients and 82.8% of controls, achieving an overall classification accuracy of 79.3%. Furthermore, classification was disorder-specific relative to ASD. The discriminating GM patterns showed higher classification weights for ADHD in earlier developing ventrolateral/premotor fronto-temporo-limbic and stronger classification weights for healthy controls in later developing dorsolateral fronto-striato-parieto-cerebellar networks. Several regions were also decreased in GM in ADHD relative to healthy controls in the univariate VBM analysis, suggesting they are GM deficit areas.The study provides evidence that pattern recognition analysis can provide significant individual diagnostic classification of ADHD patients and healthy controls based on distributed GM patterns with 79.3% accuracy and that this is disorder-specific relative to ASD. Findings are a promising first step towards finding an objective differential diagnostic tool based on brain imaging measures to aid with the subjective clinical diagnosis of ADHD.

  19. [Bronchopulmonary dysplasia: definitions and classifications].

    Science.gov (United States)

    Sánchez Luna, M; Moreno Hernando, J; Botet Mussons, F; Fernández Lorenzo, J R; Herranz Carrillo, G; Rite Gracia, S; Salguero García, E; Echaniz Urcelay, I

    2013-10-01

    Bronchopulmonary dysplasia is the most common sequelae related to very low birth weight infants, mostly with those of extremely low birth weight. Even with advances in prevention and treatment of respiratory distress syndrome associated with prematurity, there is still no decrease in the incidence in this population, although a change in its clinical expression and severity has been observed. There are, however, differences in its frequency between health centres, probably due to a non-homogeneously used clinical definition. In this article, the Committee of Standards of the Spanish Society of Neonatology wishes to review the current diagnosis criteria of bronchopulmonary dysplasia to reduce, as much as possible, these inter-centre differences. Copyright © 2013 Asociación Española de Pediatría. Published by Elsevier Espana. All rights reserved.

  20. Classifications of track structures

    International Nuclear Information System (INIS)

    Paretzke, H.G.

    1984-01-01

    When ionizing particles interact with matter they produce random topological structures of primary activations which represent the initial boundary conditions for all subsequent physical, chemical and/or biological reactions. There are two important aspects of research on such track structures, namely their experimental or theoretical determination on one hand and the quantitative classification of these complex structures which is a basic pre-requisite for the understanding of mechanisms of radiation actions. This paper deals only with the latter topic, i.e. the problems encountered in and possible approaches to quantitative ordering and grouping of these multidimensional objects by their degrees of similarity with respect to their efficiency in producing certain final radiation effects, i.e. to their ''radiation quality.'' Various attempts of taxonometric classification with respect to radiation efficiency have been made in basic and applied radiation research including macro- and microdosimetric concepts as well as track entities and stopping power based theories. In this paper no review of those well-known approaches is given but rather an outline and discussion of alternative methods new to this field of radiation research which have some very promising features and which could possibly solve at least some major classification problems

  1. An automated cirrus classification

    Science.gov (United States)

    Gryspeerdt, Edward; Quaas, Johannes; Goren, Tom; Klocke, Daniel; Brueck, Matthias

    2018-05-01

    Cirrus clouds play an important role in determining the radiation budget of the earth, but many of their properties remain uncertain, particularly their response to aerosol variations and to warming. Part of the reason for this uncertainty is the dependence of cirrus cloud properties on the cloud formation mechanism, which itself is strongly dependent on the local meteorological conditions. In this work, a classification system (Identification and Classification of Cirrus or IC-CIR) is introduced to identify cirrus clouds by the cloud formation mechanism. Using reanalysis and satellite data, cirrus clouds are separated into four main types: orographic, frontal, convective and synoptic. Through a comparison to convection-permitting model simulations and back-trajectory-based analysis, it is shown that these observation-based regimes can provide extra information on the cloud-scale updraughts and the frequency of occurrence of liquid-origin ice, with the convective regime having higher updraughts and a greater occurrence of liquid-origin ice compared to the synoptic regimes. Despite having different cloud formation mechanisms, the radiative properties of the regimes are not distinct, indicating that retrieved cloud properties alone are insufficient to completely describe them. This classification is designed to be easily implemented in GCMs, helping improve future model-observation comparisons and leading to improved parametrisations of cirrus cloud processes.

  2. Comparison of Danish dichotomous and BI-RADS classifications of mammographic density

    DEFF Research Database (Denmark)

    Hodge, Rebecca; Hellmann, Sophie Sell; von Euler-Chelpin, My

    2014-01-01

    BACKGROUND: In the Copenhagen mammography screening program from 1991 to 2001, mammographic density was classified either as fatty or mixed/dense. This dichotomous mammographic density classification system is unique internationally, and has not been validated before. PURPOSE: To compare the Danish...... dichotomous mammographic density classification system from 1991 to 2001 with the density BI-RADS classifications, in an attempt to validate the Danish classification system. MATERIAL AND METHODS: The study sample consisted of 120 mammograms taken in Copenhagen in 1991-2001, which tested false positive......, and which were in 2012 re-assessed and classified according to the BI-RADS classification system. We calculated inter-rater agreement between the Danish dichotomous mammographic classification as fatty or mixed/dense and the four-level BI-RADS classification by the linear weighted Kappa statistic. RESULTS...

  3. Body weight satisfaction and disordered eating among youth who are active in sport in Singapore

    Directory of Open Access Journals (Sweden)

    Michael Chia

    2015-04-01

    Full Text Available Purpose : The research examined the relationship between body weight satisfaction and disordered eating among youth who are active in sport in Singapore. Method : 137 youths (82 boys and 55 girls; age 12-13 enrolled in school sport completed two self-report questionnaires- SCOFF for disordered eating and body weight satisfaction- on two separate occasions that were six months apart (T1 vs. T2. Results : Body mass index for age classifications revealed that 5.1% were severely underweight; 1.5% underweight; 88.3% acceptable weight; 4.4% overweight and 0.7% were severely overweight. Conclusions : (i the prevalence of disordered eating was 46% at baseline measurement and this remained stable at 45.3% six months later; (ii there was no sex difference for disordered eating on the two measurement occasions (T1 vs. T2, p>0.05; (iii the prevalence of youths unsure of their bodyweight satisfaction was 26.6-21.2% which compared to 88.3% adjudged to be of healthy weight; across T1 and T2, more male subjects wanted to gain bodyweight while more female subjects wanted to lose bodyweight; and (iv subjects who were dissatisfied with their bodyweight had significantly greater odds of being at risk for developing DE. Holistic education programmes based upon body image and nutrition, are recommended.

  4. Classification of Complex Sounds.

    Science.gov (United States)

    1992-10-31

    spectral weights may be useful in developing signal enhancement techniques based on psychological aspects of the listener (providing a complement to...Journals) Green, D.M., and Berg, B.G. (1991). Spectral weights and the profile bowl. Quarterly Journal of Experimental Psychology , 43A, 449-458. Dai, H...Macmillan and C.D. Creelman . Cambridge/NY: Cambridge Universi- ty Press, 1991.) J. Math. Psych., in press. Training Currently, there are two graduate

  5. Treatment Options for Severe Obesity in the Pediatric Population: Current Limitations and Future Opportunities.

    Science.gov (United States)

    Ryder, Justin R; Fox, Claudia K; Kelly, Aaron S

    2018-06-01

    Severe obesity is the only obesity classification increasing in prevalence among children and adolescents. Treatment options that produce meaningful and sustained weight loss and comorbidity resolution are urgently needed. The purpose of this review is to provide a brief overview of the current treatment options for pediatric severe obesity and offer suggestions regarding future opportunities for accelerating the development and evaluation of innovative treatment strategies. At present, there are three treatment options for youth with severe obesity: lifestyle modification therapy, pharmacotherapy, and bariatric surgery. Lifestyle modification therapy can be useful for improving many chronic disease risk factors and comorbid conditions but often fails to achieve clinically meaningful and sustainable weight loss. Pharmacotherapy holds promise as an effective adjunctive treatment but remains in the primordial stages of development in the pediatric population. Bariatric surgery provides robust weight loss and risk factor/comorbidity improvements but is accompanied by higher risks and lower uptake compared to lifestyle modification therapy and pharmacotherapy. New areas worth pursuing include combination pharmacotherapy, device therapy, identification of predictors of response aimed at precision treatment, and interventions in the postbariatric surgical setting to improve long-term outcomes. Treating pediatric severe obesity effectively and safely is extremely challenging. Some progress has been made, but substantially more effort and innovation are needed in the future to combat this serious and ongoing medical and public health issue. © 2018 The Obesity Society.

  6. Maximum mutual information regularized classification

    KAUST Repository

    Wang, Jim Jing-Yan

    2014-09-07

    In this paper, a novel pattern classification approach is proposed by regularizing the classifier learning to maximize mutual information between the classification response and the true class label. We argue that, with the learned classifier, the uncertainty of the true class label of a data sample should be reduced by knowing its classification response as much as possible. The reduced uncertainty is measured by the mutual information between the classification response and the true class label. To this end, when learning a linear classifier, we propose to maximize the mutual information between classification responses and true class labels of training samples, besides minimizing the classification error and reducing the classifier complexity. An objective function is constructed by modeling mutual information with entropy estimation, and it is optimized by a gradient descend method in an iterative algorithm. Experiments on two real world pattern classification problems show the significant improvements achieved by maximum mutual information regularization.

  7. Maximum mutual information regularized classification

    KAUST Repository

    Wang, Jim Jing-Yan; Wang, Yi; Zhao, Shiguang; Gao, Xin

    2014-01-01

    In this paper, a novel pattern classification approach is proposed by regularizing the classifier learning to maximize mutual information between the classification response and the true class label. We argue that, with the learned classifier, the uncertainty of the true class label of a data sample should be reduced by knowing its classification response as much as possible. The reduced uncertainty is measured by the mutual information between the classification response and the true class label. To this end, when learning a linear classifier, we propose to maximize the mutual information between classification responses and true class labels of training samples, besides minimizing the classification error and reducing the classifier complexity. An objective function is constructed by modeling mutual information with entropy estimation, and it is optimized by a gradient descend method in an iterative algorithm. Experiments on two real world pattern classification problems show the significant improvements achieved by maximum mutual information regularization.

  8. Correction Equations to Adjust Self-Reported Height and Weight for Obesity Estimates among College Students

    Science.gov (United States)

    Mozumdar, Arupendra; Liguori, Gary

    2011-01-01

    The purposes of this study were to generate correction equations for self-reported height and weight quartiles and to test the accuracy of the body mass index (BMI) classification based on corrected self-reported height and weight among 739 male and 434 female college students. The BMIqc (from height and weight quartile-specific, corrected…

  9. The effectiveness of a non-pharmacological intervention for weight gain management in severe mental disorders: results from a national multicentric study Efetividade de uma intervenção não farmacológica para manejo do ganho de peso em pacientes com transtornos mentais graves: resultados de um estudo multicêntrico

    Directory of Open Access Journals (Sweden)

    Cecília Attux

    2011-06-01

    Full Text Available OBJECTIVE: To evaluate the effectiveness of a non-pharmacological intervention for weight gain management in severe mental disorders. METHOD: An open, multicentre interventional study was conducted in 93 mental health services. Patients concerned with weight gain were included in this study and received a 12-week 1-hour group intervention focused on nutrition counseling, lifestyle, physical activity and self-esteem. Weight, waist circumference and blood pressure were measured before and after the intervention. RESULTS: 1,071 patients were enrolled in the study, and 73.9% completed the 12-week intervention. Significant weight loss (Mean difference: 0.41, CI 95%: 0.18 to 0.64, p = 0.001 and a significant BMI reduction (Mean difference: 0.13, CI 95%: 0.04 to 0.22, p = 0.006 were observed. During the intervention 37 (4.4% patients lost > 7% of their initial weight, 780 (92.5% maintained their weight, and 26 (3.1% of the patients had a meaningful weight gain (> 7%. There was a significant increase in the proportion of patients undertaking physical activity after the intervention (70.8%, p OBJETIVO: Avaliar a efetividade de uma intervenção não farmacológica no manejo do ganho de peso para pacientes com transtornos mentais graves. MÉTODO: Foi realizado um estudo aberto multicêntrico longitudinal em 93 serviços de saúde. Pacientes preocupados com o peso foram incluídos e participaram de uma intervenção em grupo de uma hora de duração durante 12 semanas com foco em educação alimentar, atividade física e autoestima. Peso, circunferência da cintura e press��o arterial foram avaliados antes e após a intervenção. RESULTADOS: 1071 pacientes foram incluídos no estudo, 73,9% completaram a intervenção. Foram observados diminuição de peso e índice de massa corporal significativos (peso: diferença da média: 0,41, IC 95%: 0,18-0,64, p = 0,001; índice de massa corporal: diferença da média: 0,13, IC 95%: 0,04-0,22, p = 0,006. Ap

  10. Classification of proteins: available structural space for molecular modeling.

    Science.gov (United States)

    Andreeva, Antonina

    2012-01-01

    The wealth of available protein structural data provides unprecedented opportunity to study and better understand the underlying principles of protein folding and protein structure evolution. A key to achieving this lies in the ability to analyse these data and to organize them in a coherent classification scheme. Over the past years several protein classifications have been developed that aim to group proteins based on their structural relationships. Some of these classification schemes explore the concept of structural neighbourhood (structural continuum), whereas other utilize the notion of protein evolution and thus provide a discrete rather than continuum view of protein structure space. This chapter presents a strategy for classification of proteins with known three-dimensional structure. Steps in the classification process along with basic definitions are introduced. Examples illustrating some fundamental concepts of protein folding and evolution with a special focus on the exceptions to them are presented.

  11. Predicting sample size required for classification performance

    Directory of Open Access Journals (Sweden)

    Figueroa Rosa L

    2012-02-01

    Full Text Available Abstract Background Supervised learning methods need annotated data in order to generate efficient models. Annotated data, however, is a relatively scarce resource and can be expensive to obtain. For both passive and active learning methods, there is a need to estimate the size of the annotated sample required to reach a performance target. Methods We designed and implemented a method that fits an inverse power law model to points of a given learning curve created using a small annotated training set. Fitting is carried out using nonlinear weighted least squares optimization. The fitted model is then used to predict the classifier's performance and confidence interval for larger sample sizes. For evaluation, the nonlinear weighted curve fitting method was applied to a set of learning curves generated using clinical text and waveform classification tasks with active and passive sampling methods, and predictions were validated using standard goodness of fit measures. As control we used an un-weighted fitting method. Results A total of 568 models were fitted and the model predictions were compared with the observed performances. Depending on the data set and sampling method, it took between 80 to 560 annotated samples to achieve mean average and root mean squared error below 0.01. Results also show that our weighted fitting method outperformed the baseline un-weighted method (p Conclusions This paper describes a simple and effective sample size prediction algorithm that conducts weighted fitting of learning curves. The algorithm outperformed an un-weighted algorithm described in previous literature. It can help researchers determine annotation sample size for supervised machine learning.

  12. CLASSIFICATION AND DIAGNOSTICS OF ANEMIA IN CHILDREN

    OpenAIRE

    A. G. Rumyantsev

    2011-01-01

    Anemia in children is one of the most frequent somatic diseases. Criteria of anemia diagnosis are strictly regulated as decrease of hemoglobin/erythrocytes level accompanies majority of infectious, inflammatory, autoimmune, hereditary diseases and, in several cases, it is estimated as transitory disease in some periods of children’s growth and development. The article presents main classification and differential diagnostic schemes of anemia. Diagnostics makes accent on laboratory analysis; t...

  13. Evolutionary Algorithms For Neural Networks Binary And Real Data Classification

    Directory of Open Access Journals (Sweden)

    Dr. Hanan A.R. Akkar

    2015-08-01

    Full Text Available Artificial neural networks are complex networks emulating the way human rational neurons process data. They have been widely used generally in prediction clustering classification and association. The training algorithms that used to determine the network weights are almost the most important factor that influence the neural networks performance. Recently many meta-heuristic and Evolutionary algorithms are employed to optimize neural networks weights to achieve better neural performance. This paper aims to use recently proposed algorithms for optimizing neural networks weights comparing these algorithms performance with other classical meta-heuristic algorithms used for the same purpose. However to evaluate the performance of such algorithms for training neural networks we examine such algorithms to classify four opposite binary XOR clusters and classification of continuous real data sets such as Iris and Ecoli.

  14. Nonlinear Inertia Classification Model and Application

    Directory of Open Access Journals (Sweden)

    Mei Wang

    2014-01-01

    Full Text Available Classification model of support vector machine (SVM overcomes the problem of a big number of samples. But the kernel parameter and the punishment factor have great influence on the quality of SVM model. Particle swarm optimization (PSO is an evolutionary search algorithm based on the swarm intelligence, which is suitable for parameter optimization. Accordingly, a nonlinear inertia convergence classification model (NICCM is proposed after the nonlinear inertia convergence (NICPSO is developed in this paper. The velocity of NICPSO is firstly defined as the weighted velocity of the inertia PSO, and the inertia factor is selected to be a nonlinear function. NICPSO is used to optimize the kernel parameter and a punishment factor of SVM. Then, NICCM classifier is trained by using the optical punishment factor and the optical kernel parameter that comes from the optimal particle. Finally, NICCM is applied to the classification of the normal state and fault states of online power cable. It is experimentally proved that the iteration number for the proposed NICPSO to reach the optimal position decreases from 15 to 5 compared with PSO; the training duration is decreased by 0.0052 s and the recognition precision is increased by 4.12% compared with SVM.

  15. Analysis of composition-based metagenomic classification.

    Science.gov (United States)

    Higashi, Susan; Barreto, André da Motta Salles; Cantão, Maurício Egidio; de Vasconcelos, Ana Tereza Ribeiro

    2012-01-01

    An essential step of a metagenomic study is the taxonomic classification, that is, the identification of the taxonomic lineage of the organisms in a given sample. The taxonomic classification process involves a series of decisions. Currently, in the context of metagenomics, such decisions are usually based on empirical studies that consider one specific type of classifier. In this study we propose a general framework for analyzing the impact that several decisions can have on the classification problem. Instead of focusing on any specific classifier, we define a generic score function that provides a measure of the difficulty of the classification task. Using this framework, we analyze the impact of the following parameters on the taxonomic classification problem: (i) the length of n-mers used to encode the metagenomic sequences, (ii) the similarity measure used to compare sequences, and (iii) the type of taxonomic classification, which can be conventional or hierarchical, depending on whether the classification process occurs in a single shot or in several steps according to the taxonomic tree. We defined a score function that measures the degree of separability of the taxonomic classes under a given configuration induced by the parameters above. We conducted an extensive computational experiment and found out that reasonable values for the parameters of interest could be (i) intermediate values of n, the length of the n-mers; (ii) any similarity measure, because all of them resulted in similar scores; and (iii) the hierarchical strategy, which performed better in all of the cases. As expected, short n-mers generate lower configuration scores because they give rise to frequency vectors that represent distinct sequences in a similar way. On the other hand, large values for n result in sparse frequency vectors that represent differently metagenomic fragments that are in fact similar, also leading to low configuration scores. Regarding the similarity measure, in

  16. Molecular weight distribution of Athabasca bitumen

    Energy Technology Data Exchange (ETDEWEB)

    Champagne, P J; Manolakis, E; Ternan, M

    1985-03-01

    A sample of whole Athabasca bitumen has been fractionated by preparative g.p.c. The weights of the fractions have been determined and their molecular weights measured by several methods. In contras to previously published data, consistent results were obtained using different solvents (THF, benzene/water) and using different techniques (v.p.o., f.p.d. and g.c.-m.s.). This has resulted in a accurate definition of the molecular weight distribution of Athabasca bitumen.

  17. SPORT FOOD ADDITIVE CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    I. P. Prokopenko

    2015-01-01

    Full Text Available Correctly organized nutritive and pharmacological support is an important component of an athlete's preparation for competitions, an optimal shape maintenance, fast recovery and rehabilitation after traumas and defatigation. Special products of enhanced biological value (BAS for athletes nutrition are used with this purpose. Easy-to-use energy sources are administered into athlete's organism, yielded materials and biologically active substances which regulate and activate exchange reactions which proceed with difficulties during certain physical trainings. The article presents sport supplements classification which can be used before warm-up and trainings, after trainings and in competitions breaks.

  18. Radioactive facilities classification criteria

    International Nuclear Information System (INIS)

    Briso C, H.A.; Riesle W, J.

    1992-01-01

    Appropriate classification of radioactive facilities into groups of comparable risk constitutes one of the problems faced by most Regulatory Bodies. Regarding the radiological risk, the main facts to be considered are the radioactive inventory and the processes to which these radionuclides are subjected. Normally, operations are ruled by strict safety procedures. Thus, the total activity of the radionuclides existing in a given facility is the varying feature that defines its risk. In order to rely on a quantitative criterion and, considering that the Annual Limits of Intake are widely accepted references, an index based on these limits, to support decisions related to radioactive facilities, is proposed. (author)

  19. PROGRESSIVE DENSIFICATION AND REGION GROWING METHODS FOR LIDAR DATA CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    J. L. Pérez-García

    2012-07-01

    Full Text Available At present, airborne laser scanner systems are one of the most frequent methods used to obtain digital terrain elevation models. While having the advantage of direct measurement on the object, the point cloud obtained has the need for classification of their points according to its belonging to the ground. This need for classification of raw data has led to appearance of multiple filters focused LiDAR classification information. According this approach, this paper presents a classification method that combines LiDAR data segmentation techniques and progressive densification to carry out the location of the points belonging to the ground. The proposed methodology is tested on several datasets with different terrain characteristics and data availability. In all case, we analyze the advantages and disadvantages that have been obtained compared with the individual techniques application and, in a special way, the benefits derived from the integration of both classification techniques. In order to provide a more comprehensive quality control of the classification process, the obtained results have been compared with the derived from a manual procedure, which is used as reference classification. The results are also compared with other automatic classification methodologies included in some commercial software packages, highly contrasted by users for LiDAR data treatment.

  20. A simplified immunohistochemical classification of skeletal muscle fibres in mouse

    Directory of Open Access Journals (Sweden)

    M. Kammoun

    2014-06-01

    Full Text Available The classification of muscle fibres is of particular interest for the study of the skeletal muscle properties in a wide range of scientific fields, especially animal phenotyping. It is therefore important to define a reliable method for classifying fibre types. The aim of this study was to establish a simplified method for the immunohistochemical classification of fibres in mouse. To carry it out, we first tested a combination of several anti myosin heavy chain (MyHC antibodies in order to choose a minimum number of antibodies to implement a semi-automatic classification. Then, we compared the classification of fibres to the MyHC electrophoretic pattern on the same samples. Only two anti MyHC antibodies on serial sections with the fluorescent labeling of the Laminin were necessary to classify properly fibre types in Tibialis Anterior and Soleus mouse muscles in normal physiological conditions. This classification was virtually identical to the classification realized by the electrophoretic separation of MyHC. This immunohistochemical classification can be applied to the total area of Tibialis Anterior and Soleus mouse muscles. Thus, we provide here a useful, simple and time-efficient method for immunohistochemical classification of fibres, applicable for research in mouse

  1. Constructions and classifications of projective Poisson varieties

    Science.gov (United States)

    Pym, Brent

    2018-03-01

    This paper is intended both as an introduction to the algebraic geometry of holomorphic Poisson brackets, and as a survey of results on the classification of projective Poisson manifolds that have been obtained in the past 20 years. It is based on the lecture series delivered by the author at the Poisson 2016 Summer School in Geneva. The paper begins with a detailed treatment of Poisson surfaces, including adjunction, ruled surfaces and blowups, and leading to a statement of the full birational classification. We then describe several constructions of Poisson threefolds, outlining the classification in the regular case, and the case of rank-one Fano threefolds (such as projective space). Following a brief introduction to the notion of Poisson subspaces, we discuss Bondal's conjecture on the dimensions of degeneracy loci on Poisson Fano manifolds. We close with a discussion of log symplectic manifolds with simple normal crossings degeneracy divisor, including a new proof of the classification in the case of rank-one Fano manifolds.

  2. Constructions and classifications of projective Poisson varieties.

    Science.gov (United States)

    Pym, Brent

    2018-01-01

    This paper is intended both as an introduction to the algebraic geometry of holomorphic Poisson brackets, and as a survey of results on the classification of projective Poisson manifolds that have been obtained in the past 20 years. It is based on the lecture series delivered by the author at the Poisson 2016 Summer School in Geneva. The paper begins with a detailed treatment of Poisson surfaces, including adjunction, ruled surfaces and blowups, and leading to a statement of the full birational classification. We then describe several constructions of Poisson threefolds, outlining the classification in the regular case, and the case of rank-one Fano threefolds (such as projective space). Following a brief introduction to the notion of Poisson subspaces, we discuss Bondal's conjecture on the dimensions of degeneracy loci on Poisson Fano manifolds. We close with a discussion of log symplectic manifolds with simple normal crossings degeneracy divisor, including a new proof of the classification in the case of rank-one Fano manifolds.

  3. Automatic liver volume segmentation and fibrosis classification

    Science.gov (United States)

    Bal, Evgeny; Klang, Eyal; Amitai, Michal; Greenspan, Hayit

    2018-02-01

    In this work, we present an automatic method for liver segmentation and fibrosis classification in liver computed-tomography (CT) portal phase scans. The input is a full abdomen CT scan with an unknown number of slices, and the output is a liver volume segmentation mask and a fibrosis grade. A multi-stage analysis scheme is applied to each scan, including: volume segmentation, texture features extraction and SVM based classification. Data contains portal phase CT examinations from 80 patients, taken with different scanners. Each examination has a matching Fibroscan grade. The dataset was subdivided into two groups: first group contains healthy cases and mild fibrosis, second group contains moderate fibrosis, severe fibrosis and cirrhosis. Using our automated algorithm, we achieved an average dice index of 0.93 ± 0.05 for segmentation and a sensitivity of 0.92 and specificity of 0.81for classification. To the best of our knowledge, this is a first end to end automatic framework for liver fibrosis classification; an approach that, once validated, can have a great potential value in the clinic.

  4. Weighted network modules

    International Nuclear Information System (INIS)

    Farkas, Illes; Abel, Daniel; Palla, Gergely; Vicsek, Tamas

    2007-01-01

    The inclusion of link weights into the analysis of network properties allows a deeper insight into the (often overlapping) modular structure of real-world webs. We introduce a clustering algorithm clique percolation method with weights (CPMw) for weighted networks based on the concept of percolating k-cliques with high enough intensity. The algorithm allows overlaps between the modules. First, we give detailed analytical and numerical results about the critical point of weighted k-clique percolation on (weighted) Erdos-Renyi graphs. Then, for a scientist collaboration web and a stock correlation graph we compute three-link weight correlations and with the CPMw the weighted modules. After reshuffling link weights in both networks and computing the same quantities for the randomized control graphs as well, we show that groups of three or more strong links prefer to cluster together in both original graphs

  5. Preventing Weight Gain

    Science.gov (United States)

    ... Local Programs Related Topics Diabetes Nutrition Preventing Weight Gain Language: English (US) Español (Spanish) Recommend on Facebook ... cancer. Choosing an Eating Plan to Prevent Weight Gain So, how do you choose a healthful eating ...

  6. Content Abstract Classification Using Naive Bayes

    Science.gov (United States)

    Latif, Syukriyanto; Suwardoyo, Untung; Aldrin Wihelmus Sanadi, Edwin

    2018-03-01

    This study aims to classify abstract content based on the use of the highest number of words in an abstract content of the English language journals. This research uses a system of text mining technology that extracts text data to search information from a set of documents. Abstract content of 120 data downloaded at www.computer.org. Data grouping consists of three categories: DM (Data Mining), ITS (Intelligent Transport System) and MM (Multimedia). Systems built using naive bayes algorithms to classify abstract journals and feature selection processes using term weighting to give weight to each word. Dimensional reduction techniques to reduce the dimensions of word counts rarely appear in each document based on dimensional reduction test parameters of 10% -90% of 5.344 words. The performance of the classification system is tested by using the Confusion Matrix based on comparative test data and test data. The results showed that the best classification results were obtained during the 75% training data test and 25% test data from the total data. Accuracy rates for categories of DM, ITS and MM were 100%, 100%, 86%. respectively with dimension reduction parameters of 30% and the value of learning rate between 0.1-0.5.

  7. Cirse Quality Assurance Document and Standards for Classification of Complications: The Cirse Classification System.

    Science.gov (United States)

    Filippiadis, D K; Binkert, C; Pellerin, O; Hoffmann, R T; Krajina, A; Pereira, P L

    2017-08-01

    Interventional radiology provides a wide variety of vascular, nonvascular, musculoskeletal, and oncologic minimally invasive techniques aimed at therapy or palliation of a broad spectrum of pathologic conditions. Outcome data for these techniques are globally evaluated by hospitals, insurance companies, and government agencies targeting in a high-quality health care policy, including reimbursement strategies. To analyze effectively the outcome of a technique, accurate reporting of complications is necessary. Throughout the literature, numerous classification systems for complications grading and classification have been reported. Until now, there has been no method for uniform reporting of complications both in terms of definition and grading. The purpose of this CIRSE guideline is to provide a classification system of complications based on combining outcome and severity of sequelae. The ultimate challenge will be the adoption of this system by practitioners in different countries and health economies within the European Union and beyond.

  8. Weight management in pregnancy

    OpenAIRE

    Olander, E. K.

    2015-01-01

    Key learning points:\\ud - Women who start pregnancy in an overweight or obese weight category have increased health risks\\ud - Irrespective of pre-pregnancy weight category, there are health risks associated with gaining too much weight in pregnancy for both mother and baby\\ud - There are currently no official weight gain guidelines for pregnancy in the UK, thus focus needs to be on supporting pregnant women to eat healthily and keep active

  9. On weights which admit the reproducing kernel of Bergman type

    Directory of Open Access Journals (Sweden)

    Zbigniew Pasternak-Winiarski

    1992-01-01

    Full Text Available In this paper we consider (1 the weights of integration for which the reproducing kernel of the Bergman type can be defined, i.e., the admissible weights, and (2 the kernels defined by such weights. It is verified that the weighted Bergman kernel has the analogous properties as the classical one. We prove several sufficient conditions and necessary and sufficient conditions for a weight to be an admissible weight. We give also an example of a weight which is not of this class. As a positive example we consider the weight μ(z=(Imz2 defined on the unit disk in ℂ.

  10. Gradient Weight in Phonology

    Science.gov (United States)

    Ryan, Kevin Michael

    2011-01-01

    Research on syllable weight in generative phonology has focused almost exclusively on systems in which weight is treated as an ordinal hierarchy of clearly delineated categories (e.g. light and heavy). As I discuss, canonical weight-sensitive phenomena in phonology, including quantitative meter and quantity-sensitive stress, can also treat weight…

  11. Gestational weight gain.

    Science.gov (United States)

    Kominiarek, Michelle A; Peaceman, Alan M

    2017-12-01

    Prenatal care providers are advised to evaluate maternal weight at each regularly scheduled prenatal visit, monitor progress toward meeting weight gain goals, and provide individualized counseling if significant deviations from a woman's goals occur. Today, nearly 50% of women exceed their weight gain goals with overweight and obese women having the highest prevalence of excessive weight gain. Risks of inadequate weight gain include low birthweight and failure to initiate breast-feeding whereas the risks of excessive weight gain include cesarean deliveries and postpartum weight retention for the mother and large-for-gestational-age infants, macrosomia, and childhood overweight or obesity for the offspring. Prenatal care providers have many resources and tools to incorporate weight and other health behavior counseling into routine prenatal practices. Because many women are motivated to improve health behaviors, pregnancy is often considered the optimal time to intervene for issues related to eating habits and physical activity to prevent excessive weight gain. Gestational weight gain is a potentially modifiable risk factor for a number of adverse maternal and neonatal outcomes and meta-analyses of randomized controlled trials report that diet or exercise interventions during pregnancy can help reduce excessive weight gain. However, health behavior interventions for gestational weight gain have not significantly improved other maternal and neonatal outcomes and have limited effectiveness in overweight and obese women. Copyright © 2017 Elsevier Inc. All rights reserved.

  12. Supply chain planning classification

    Science.gov (United States)

    Hvolby, Hans-Henrik; Trienekens, Jacques; Bonde, Hans

    2001-10-01

    Industry experience a need to shift in focus from internal production planning towards planning in the supply network. In this respect customer oriented thinking becomes almost a common good amongst companies in the supply network. An increase in the use of information technology is needed to enable companies to better tune their production planning with customers and suppliers. Information technology opportunities and supply chain planning systems facilitate companies to monitor and control their supplier network. In spite if these developments, most links in today's supply chains make individual plans, because the real demand information is not available throughout the chain. The current systems and processes of the supply chains are not designed to meet the requirements now placed upon them. For long term relationships with suppliers and customers, an integrated decision-making process is needed in order to obtain a satisfactory result for all parties. Especially when customized production and short lead-time is in focus. An effective value chain makes inventory available and visible among the value chain members, minimizes response time and optimizes total inventory value held throughout the chain. In this paper a supply chain planning classification grid is presented based current manufacturing classifications and supply chain planning initiatives.

  13. Waste classification sampling plan

    International Nuclear Information System (INIS)

    Landsman, S.D.

    1998-01-01

    The purpose of this sampling is to explain the method used to collect and analyze data necessary to verify and/or determine the radionuclide content of the B-Cell decontamination and decommissioning waste stream so that the correct waste classification for the waste stream can be made, and to collect samples for studies of decontamination methods that could be used to remove fixed contamination present on the waste. The scope of this plan is to establish the technical basis for collecting samples and compiling quantitative data on the radioactive constituents present in waste generated during deactivation activities in B-Cell. Sampling and radioisotopic analysis will be performed on the fixed layers of contamination present on structural material and internal surfaces of process piping and tanks. In addition, dose rate measurements on existing waste material will be performed to determine the fraction of dose rate attributable to both removable and fixed contamination. Samples will also be collected to support studies of decontamination methods that are effective in removing the fixed contamination present on the waste. Sampling performed under this plan will meet criteria established in BNF-2596, Data Quality Objectives for the B-Cell Waste Stream Classification Sampling, J. M. Barnett, May 1998

  14. Cluster Based Text Classification Model

    DEFF Research Database (Denmark)

    Nizamani, Sarwat; Memon, Nasrullah; Wiil, Uffe Kock

    2011-01-01

    We propose a cluster based classification model for suspicious email detection and other text classification tasks. The text classification tasks comprise many training examples that require a complex classification model. Using clusters for classification makes the model simpler and increases...... the accuracy at the same time. The test example is classified using simpler and smaller model. The training examples in a particular cluster share the common vocabulary. At the time of clustering, we do not take into account the labels of the training examples. After the clusters have been created......, the classifier is trained on each cluster having reduced dimensionality and less number of examples. The experimental results show that the proposed model outperforms the existing classification models for the task of suspicious email detection and topic categorization on the Reuters-21578 and 20 Newsgroups...

  15. Classification of smooth Fano polytopes

    DEFF Research Database (Denmark)

    Øbro, Mikkel

    A simplicial lattice polytope containing the origin in the interior is called a smooth Fano polytope, if the vertices of every facet is a basis of the lattice. The study of smooth Fano polytopes is motivated by their connection to toric varieties. The thesis concerns the classification of smooth...... Fano polytopes up to isomorphism. A smooth Fano -polytope can have at most vertices. In case of vertices an explicit classification is known. The thesis contains the classification in case of vertices. Classifications of smooth Fano -polytopes for fixed exist only for . In the thesis an algorithm...... for the classification of smooth Fano -polytopes for any given is presented. The algorithm has been implemented and used to obtain the complete classification for ....

  16. Small-scale classification schemes

    DEFF Research Database (Denmark)

    Hertzum, Morten

    2004-01-01

    Small-scale classification schemes are used extensively in the coordination of cooperative work. This study investigates the creation and use of a classification scheme for handling the system requirements during the redevelopment of a nation-wide information system. This requirements...... classification inherited a lot of its structure from the existing system and rendered requirements that transcended the framework laid out by the existing system almost invisible. As a result, the requirements classification became a defining element of the requirements-engineering process, though its main...... effects remained largely implicit. The requirements classification contributed to constraining the requirements-engineering process by supporting the software engineers in maintaining some level of control over the process. This way, the requirements classification provided the software engineers...

  17. Classification and valuation of postoperative complications in a randomized trial of open versus laparoscopic ventral herniorrhaphy.

    Science.gov (United States)

    Kaafarani, H M A; Hur, K; Campasano, M; Reda, D J; Itani, K M F

    2010-06-01

    Generic instruments used for the valuation of health states (e.g., EuroQol) often lack sensitivity to notable differences that are relevant to particular diseases or interventions. We developed a valuation methodology specifically for complications following ventral incisional herniorrhaphy (VIH). Between 2004 and 2006, 146 patients were prospectively randomized to undergo laparoscopic (n = 73) or open (n = 73) VIH. The primary outcome of the trial was complications at 8 weeks. A three-step methodology was used to assign severity weights to complications. First, each complication was graded using the Clavien classification. Second, five reviewers were asked to independently and directly rate their perception of the severity of each class using a non-categorized visual analog scale. Zero represented an uncomplicated postoperative course, while 100 represented postoperative death. Third, the median, lowest, and highest values assigned to each class of complications were used to derive weighted complication scores for open and laparoscopic VIH. Open VIH had more complications than laparoscopic VIH (47.9 vs. 31.5%, respectively; P = 0.026). However, complications of laparoscopic VIH were more severe than those of open VIH. Non-parametric analysis revealed a statistically higher weighted complication score for open VIH (interquartile range: 0-20 for open vs. 0-10 for laparoscopic; P = 0.049). In the sensitivity analysis, similar results were obtained using the median, highest, and lowest weights. We describe a new methodology for the valuation of complications following VIH that allows a direct outcome comparison of procedures with different complication profiles. Further testing of the validity, reliability, and generalizability of this method is warranted.

  18. Active Learning for Text Classification

    OpenAIRE

    Hu, Rong

    2011-01-01

    Text classification approaches are used extensively to solve real-world challenges. The success or failure of text classification systems hangs on the datasets used to train them, without a good dataset it is impossible to build a quality system. This thesis examines the applicability of active learning in text classification for the rapid and economical creation of labelled training data. Four main contributions are made in this thesis. First, we present two novel selection strategies to cho...

  19. Validation of a new classification system for interprosthetic femoral fractures.

    Science.gov (United States)

    Pires, Robinson Esteves Santos; Silveira, Marcelo Peixoto Sena; Resende, Alessandra Regina da Silva; Junior, Egidio Oliveira Santana; Campos, Tulio Vinicius Oliveira; Santos, Leandro Emilio Nascimento; Balbachevsky, Daniel; Andrade, Marco Antônio Percope de

    2017-07-01

    Interprosthetic femoral fracture (IFF) incidence is gradually increasing as the population is progressively ageing. However, treatment remains challenging due to several contributing factors, such as poor bone quality, patient comorbidities, small interprosthetic fragment, and prostheses instability. An effective and specific classification system is essential to optimize treatment management, therefore diminishing complication rates. This study aims to validate a previously described classification system for interprosthetic femoral fractures. Copyright © 2017 Elsevier Ltd. All rights reserved.

  20. Standardizing foot-type classification using arch index values.

    Science.gov (United States)

    Wong, Christopher Kevin; Weil, Rich; de Boer, Emily

    2012-01-01

    The lack of a reliable classification standard for foot type makes drawing conclusions from existing research and clinical decisions difficult, since different foot types may move and respond to treatment differently. The purpose of this study was to determine interrater agreement for foot-type classification based on photo-box-derived arch index values. For this correlational study with two raters, a sample of 11 healthy volunteers with normal to obese body mass indices was recruited from both a community weight-loss programme and a programme in physical therapy. Arch index was calculated using AutoCAD software from footprint photographs obtained via mirrored photo-box. Classification as high-arched, normal, or low-arched foot type was based on arch index values. Reliability of the arch index was determined with intra-class correlations; agreement on foot-type classification was determined using quadratic weighted kappa (κw). Average arch index was 0.215 for one tester and 0.219 for the second tester, with an overall range of 0.017 to 0.370. Both testers classified 6 feet as low-arched, 9 feet as normal, and 7 feet as high-arched. Interrater reliability for the arch index was ICC=0.90; interrater agreement for foot-type classification was κw=0.923. Classification of foot type based on arch index values derived from plantar footprint photographs obtained via mirrored photo-box showed excellent reliability in people with varying BMI. Foot-type classification may help clinicians and researchers subdivide sample populations to better differentiate mobility, gait, or treatment effects among foot types.

  1. Standardizing Foot-Type Classification Using Arch Index Values

    Science.gov (United States)

    Weil, Rich; de Boer, Emily

    2012-01-01

    ABSTRACT Purpose: The lack of a reliable classification standard for foot type makes drawing conclusions from existing research and clinical decisions difficult, since different foot types may move and respond to treatment differently. The purpose of this study was to determine interrater agreement for foot-type classification based on photo-box-derived arch index values. Method: For this correlational study with two raters, a sample of 11 healthy volunteers with normal to obese body mass indices was recruited from both a community weight-loss programme and a programme in physical therapy. Arch index was calculated using AutoCAD software from footprint photographs obtained via mirrored photo-box. Classification as high-arched, normal, or low-arched foot type was based on arch index values. Reliability of the arch index was determined with intra-class correlations; agreement on foot-type classification was determined using quadratic weighted kappa (κw). Results: Average arch index was 0.215 for one tester and 0.219 for the second tester, with an overall range of 0.017 to 0.370. Both testers classified 6 feet as low-arched, 9 feet as normal, and 7 feet as high-arched. Interrater reliability for the arch index was ICC=0.90; interrater agreement for foot-type classification was κw=0.923. Conclusions: Classification of foot type based on arch index values derived from plantar footprint photographs obtained via mirrored photo-box showed excellent reliability in people with varying BMI. Foot-type classification may help clinicians and researchers subdivide sample populations to better differentiate mobility, gait, or treatment effects among foot types. PMID:23729964

  2. Weighted Watson-Crick automata

    Energy Technology Data Exchange (ETDEWEB)

    Tamrin, Mohd Izzuddin Mohd [Department of Information System, Kulliyyah of Information and Communication Technology, International Islamic University Malaysia, 50728 Gombak, Selangor (Malaysia); Turaev, Sherzod; Sembok, Tengku Mohd Tengku [Department of Computer Science, Kulliyyah of Information and Communication Technology, International Islamic University Malaysia, 50728 Gombak, Selangor (Malaysia)

    2014-07-10

    There are tremendous works in biotechnology especially in area of DNA molecules. The computer society is attempting to develop smaller computing devices through computational models which are based on the operations performed on the DNA molecules. A Watson-Crick automaton, a theoretical model for DNA based computation, has two reading heads, and works on double-stranded sequences of the input related by a complementarity relation similar with the Watson-Crick complementarity of DNA nucleotides. Over the time, several variants of Watson-Crick automata have been introduced and investigated. However, they cannot be used as suitable DNA based computational models for molecular stochastic processes and fuzzy processes that are related to important practical problems such as molecular parsing, gene disease detection, and food authentication. In this paper we define new variants of Watson-Crick automata, called weighted Watson-Crick automata, developing theoretical models for molecular stochastic and fuzzy processes. We define weighted Watson-Crick automata adapting weight restriction mechanisms associated with formal grammars and automata. We also study the generative capacities of weighted Watson-Crick automata, including probabilistic and fuzzy variants. We show that weighted variants of Watson-Crick automata increase their generative power.

  3. Weighted Watson-Crick automata

    International Nuclear Information System (INIS)

    Tamrin, Mohd Izzuddin Mohd; Turaev, Sherzod; Sembok, Tengku Mohd Tengku

    2014-01-01

    There are tremendous works in biotechnology especially in area of DNA molecules. The computer society is attempting to develop smaller computing devices through computational models which are based on the operations performed on the DNA molecules. A Watson-Crick automaton, a theoretical model for DNA based computation, has two reading heads, and works on double-stranded sequences of the input related by a complementarity relation similar with the Watson-Crick complementarity of DNA nucleotides. Over the time, several variants of Watson-Crick automata have been introduced and investigated. However, they cannot be used as suitable DNA based computational models for molecular stochastic processes and fuzzy processes that are related to important practical problems such as molecular parsing, gene disease detection, and food authentication. In this paper we define new variants of Watson-Crick automata, called weighted Watson-Crick automata, developing theoretical models for molecular stochastic and fuzzy processes. We define weighted Watson-Crick automata adapting weight restriction mechanisms associated with formal grammars and automata. We also study the generative capacities of weighted Watson-Crick automata, including probabilistic and fuzzy variants. We show that weighted variants of Watson-Crick automata increase their generative power

  4. Reliability of Oronasal Fistula Classification.

    Science.gov (United States)

    Sitzman, Thomas J; Allori, Alexander C; Matic, Damir B; Beals, Stephen P; Fisher, David M; Samson, Thomas D; Marcus, Jeffrey R; Tse, Raymond W

    2018-01-01

    Objective Oronasal fistula is an important complication of cleft palate repair that is frequently used to evaluate surgical quality, yet reliability of fistula classification has never been examined. The objective of this study was to determine the reliability of oronasal fistula classification both within individual surgeons and between multiple surgeons. Design Using intraoral photographs of children with repaired cleft palate, surgeons rated the location of palatal fistulae using the Pittsburgh Fistula Classification System. Intrarater and interrater reliability scores were calculated for each region of the palate. Participants Eight cleft surgeons rated photographs obtained from 29 children. Results Within individual surgeons reliability for each region of the Pittsburgh classification ranged from moderate to almost perfect (κ = .60-.96). By contrast, reliability between surgeons was lower, ranging from fair to substantial (κ = .23-.70). Between-surgeon reliability was lowest for the junction of the soft and hard palates (κ = .23). Within-surgeon and between-surgeon reliability were almost perfect for the more general classification of fistula in the secondary palate (κ = .95 and κ = .83, respectively). Conclusions This is the first reliability study of fistula classification. We show that the Pittsburgh Fistula Classification System is reliable when used by an individual surgeon, but less reliable when used among multiple surgeons. Comparisons of fistula occurrence among surgeons may be subject to less bias if they use the more general classification of "presence or absence of fistula of the secondary palate" rather than the Pittsburgh Fistula Classification System.

  5. [New International Classification of Chronic Pancreatitis (M-ANNHEIM multifactor classification system, 2007): principles, merits, and demerits].

    Science.gov (United States)

    Tsimmerman, Ia S

    2008-01-01

    The new International Classification of Chronic Pancreatitis (designated as M-ANNHEIM) proposed by a group of German specialists in late 2007 is reviewed. All its sections are subjected to analysis (risk group categories, clinical stages and phases, variants of clinical course, diagnostic criteria for "established" and "suspected" pancreatitis, instrumental methods and functional tests used in the diagnosis, evaluation of the severity of the disease using a scoring system, stages of elimination of pain syndrome). The new classification is compared with the earlier classification proposed by the author. Its merits and demerits are discussed.

  6. Thyroid weight with age

    International Nuclear Information System (INIS)

    Raulier-Fabry, C.; Hammer, R.

    1965-01-01

    A large number of data on thyroid weight of euthyroid subjects have been collected from the literature in this study. The most probable average weight of the gland appears to be 20 g in the adult and 2 g in the newborn. A decrease in weight has been observed during the first year of life (1 g at 6 months) and only in the second year of life the initial birth weight is reached again. The weight curve may be considered as consisting of three straight lines: from 2 to 7, from 7 to 18 and from 18 to 25 years, their slopes being respectively 0.6, 0.9 and 0.5 g/year. The variations in weight of the thyroid during adulthood are sufficiently small to consider it as having constant value between 25 and 55 years. The available information points to a negligible weight difference between sexes. (authors) [fr

  7. Consensus classification of posterior cortical atrophy.

    Science.gov (United States)

    Crutch, Sebastian J; Schott, Jonathan M; Rabinovici, Gil D; Murray, Melissa; Snowden, Julie S; van der Flier, Wiesje M; Dickerson, Bradford C; Vandenberghe, Rik; Ahmed, Samrah; Bak, Thomas H; Boeve, Bradley F; Butler, Christopher; Cappa, Stefano F; Ceccaldi, Mathieu; de Souza, Leonardo Cruz; Dubois, Bruno; Felician, Olivier; Galasko, Douglas; Graff-Radford, Jonathan; Graff-Radford, Neill R; Hof, Patrick R; Krolak-Salmon, Pierre; Lehmann, Manja; Magnin, Eloi; Mendez, Mario F; Nestor, Peter J; Onyike, Chiadi U; Pelak, Victoria S; Pijnenburg, Yolande; Primativo, Silvia; Rossor, Martin N; Ryan, Natalie S; Scheltens, Philip; Shakespeare, Timothy J; Suárez González, Aida; Tang-Wai, David F; Yong, Keir X X; Carrillo, Maria; Fox, Nick C

    2017-08-01

    A classification framework for posterior cortical atrophy (PCA) is proposed to improve the uniformity of definition of the syndrome in a variety of research settings. Consensus statements about PCA were developed through a detailed literature review, the formation of an international multidisciplinary working party which convened on four occasions, and a Web-based quantitative survey regarding symptom frequency and the conceptualization of PCA. A three-level classification framework for PCA is described comprising both syndrome- and disease-level descriptions. Classification level 1 (PCA) defines the core clinical, cognitive, and neuroimaging features and exclusion criteria of the clinico-radiological syndrome. Classification level 2 (PCA-pure, PCA-plus) establishes whether, in addition to the core PCA syndrome, the core features of any other neurodegenerative syndromes are present. Classification level 3 (PCA attributable to AD [PCA-AD], Lewy body disease [PCA-LBD], corticobasal degeneration [PCA-CBD], prion disease [PCA-prion]) provides a more formal determination of the underlying cause of the PCA syndrome, based on available pathophysiological biomarker evidence. The issue of additional syndrome-level descriptors is discussed in relation to the challenges of defining stages of syndrome severity and characterizing phenotypic heterogeneity within the PCA spectrum. There was strong agreement regarding the definition of the core clinico-radiological syndrome, meaning that the current consensus statement should be regarded as a refinement, development, and extension of previous single-center PCA criteria rather than any wholesale alteration or redescription of the syndrome. The framework and terminology may facilitate the interpretation of research data across studies, be applicable across a broad range of research scenarios (e.g., behavioral interventions, pharmacological trials), and provide a foundation for future collaborative work. Copyright © 2017 The Authors

  8. Monitoring Severe Accidents Using AI Techniques

    International Nuclear Information System (INIS)

    No, Young Gyu; Kim, Ju Hyun; Na, Man Gyun; Ahn, Kwang Il

    2011-01-01

    It is very difficult for nuclear power plant operators to monitor and identify the major severe accident scenarios following an initiating event by staring at temporal trends of important parameters. The objective of this study is to develop and verify the monitoring for severe accidents using artificial intelligence (AI) techniques such as support vector classification (SVC), probabilistic neural network (PNN), group method of data handling (GMDH) and fuzzy neural network (FNN). The SVC and PNN are used for event classification among the severe accidents. Also, GMDH and FNN are used to monitor for severe accidents. The inputs to AI techniques are initial time-integrated values obtained by integrating measurement signals during a short time interval after reactor scram. In this study, 3 types of initiating events such as the hot-leg LOCA, the cold-leg LOCA and SGTR are considered and it is verified how well the proposed scenario identification algorithm using the GMDH and FNN models identifies the timings when the reactor core will be uncovered, when CET will exceed 1200 .deg. F and when the reactor vessel will fail. In cases that an initiating event develops into a severe accident, the proposed algorithm showed accurate classification of initiating events. Also, it well predicted timings for important occurrences during severe accident progression scenarios, which is very helpful for operators to perform severe accident management

  9. Yogurt and weight management.

    Science.gov (United States)

    Jacques, Paul F; Wang, Huifen

    2014-05-01

    A large body of observational studies and randomized controlled trials (RCTs) has examined the role of dairy products in weight loss and maintenance of healthy weight. Yogurt is a dairy product that is generally very similar to milk, but it also has some unique properties that may enhance its possible role in weight maintenance. This review summarizes the human RCT and prospective observational evidence on the relation of yogurt consumption to the management and maintenance of body weight and composition. The RCT evidence is limited to 2 small, short-term, energy-restricted trials. They both showed greater weight losses with yogurt interventions, but the difference between the yogurt intervention and the control diet was only significant in one of these trials. There are 5 prospective observational studies that have examined the association between yogurt and weight gain. The results of these studies are equivocal. Two of these studies reported that individuals with higher yogurt consumption gained less weight over time. One of these same studies also considered changes in waist circumference (WC) and showed that higher yogurt consumption was associated with smaller increases in WC. A third study was inconclusive because of low statistical power. A fourth study observed no association between changes in yogurt intake and weight gain, but the results suggested that those with the largest increases in yogurt intake during the study also had the highest increase in WC. The final study examined weight and WC change separately by sex and baseline weight status and showed benefits for both weight and WC changes for higher yogurt consumption in overweight men, but it also found that higher yogurt consumption in normal-weight women was associated with a greater increase in weight over follow-up. Potential underlying mechanisms for the action of yogurt on weight are briefly discussed.

  10. Intelligent Computer Vision System for Automated Classification

    International Nuclear Information System (INIS)

    Jordanov, Ivan; Georgieva, Antoniya

    2010-01-01

    In this paper we investigate an Intelligent Computer Vision System applied for recognition and classification of commercially available cork tiles. The system is capable of acquiring and processing gray images using several feature generation and analysis techniques. Its functionality includes image acquisition, feature extraction and preprocessing, and feature classification with neural networks (NN). We also discuss system test and validation results from the recognition and classification tasks. The system investigation also includes statistical feature processing (features number and dimensionality reduction techniques) and classifier design (NN architecture, target coding, learning complexity and performance, and training with our own metaheuristic optimization method). The NNs trained with our genetic low-discrepancy search method (GLPτS) for global optimisation demonstrated very good generalisation abilities. In our view, the reported testing success rate of up to 95% is due to several factors: combination of feature generation techniques; application of Analysis of Variance (ANOVA) and Principal Component Analysis (PCA), which appeared to be very efficient for preprocessing the data; and use of suitable NN design and learning method.

  11. Inherited epidermolysis bullosa : Updated recommendations on diagnosis and classification

    NARCIS (Netherlands)

    Fine, Jo-David; Bruckner-Tuderman, Leena; Eady, Robin A. J.; Bauer, Eugene A.; Bauer, Johann W.; Has, Cristina; Heagerty, Adrian; Hintner, Helmut; Hovnanian, Alain; Jonkman, Marcel F.; Leigh, Irene; Marinkovich, M. Peter; Martinez, Anna E.; McGrath, John A.; Mellerio, Jemima E.; Moss, Celia; Murrell, Dedee F.; Shimizu, Hiroshi; Uitto, Jouni; Woodley, David; Zambruno, Giovanna

    Background: Several newtargeted genes and clinical subtypes have been identified since publication in 2008 of the report of the last international consensus meeting on diagnosis and classification of epidermolysis bullosa (EB). As a correlate, new clinical manifestations have been seen in several

  12. Classification of radioactive waste

    International Nuclear Information System (INIS)

    1994-01-01

    Radioactive wastes are generated in a number of different kinds of facilities and arise in a wide range of concentrations of radioactive materials and in a variety of physical and chemical forms. To simplify their management, a number of schemes have evolved for classifying radioactive waste according to the physical, chemical and radiological properties of significance to those facilities managing this waste. These schemes have led to a variety of terminologies, differing from country to country and even between facilities in the same country. This situation makes it difficult for those concerned to communicate with one another regarding waste management practices. This document revises and updates earlier IAEA references on radioactive waste classification systems given in IAEA Technical Reports Series and Safety Series. Guidance regarding exemption of materials from regulatory control is consistent with IAEA Safety Series and the RADWASS documents published under IAEA Safety Series. 11 refs, 2 figs, 2 tab

  13. Nonlinear estimation and classification

    CERN Document Server

    Hansen, Mark; Holmes, Christopher; Mallick, Bani; Yu, Bin

    2003-01-01

    Researchers in many disciplines face the formidable task of analyzing massive amounts of high-dimensional and highly-structured data This is due in part to recent advances in data collection and computing technologies As a result, fundamental statistical research is being undertaken in a variety of different fields Driven by the complexity of these new problems, and fueled by the explosion of available computer power, highly adaptive, non-linear procedures are now essential components of modern "data analysis," a term that we liberally interpret to include speech and pattern recognition, classification, data compression and signal processing The development of new, flexible methods combines advances from many sources, including approximation theory, numerical analysis, machine learning, signal processing and statistics The proposed workshop intends to bring together eminent experts from these fields in order to exchange ideas and forge directions for the future

  14. Modification of Hidden Layer Weight in Extreme Learning Machine Using Gain Ratio

    Directory of Open Access Journals (Sweden)

    Anggraeny Fetty Tri

    2016-01-01

    Full Text Available Extreme Learning Machine (ELM is a method of learning feed forward neural network quickly and has a fairly good accuracy. This method is devoted to a feed forward neural network with one hidden layer where the parameters (i.e. weight and bias are adjusted one time randomly at the beginning of the learning process. In neural network, the input layer is connected to all characteristics/features, and the output layer is connected to all classes of species. This research used three datasets from UCI database, which were Iris, Breast Wisconsin, and Dermatology, with each dataset having several features. Each characteristic/feature of the data has a role in the process of classification levels, starting from the most influencing role to non-influencing at all. Gain ratio was used to extract each feature role on each datasets. Gain ratio is a method to extract feature role in order to develop a decision tree structure. In this study, ELM structure has been modified, where the random weights of the hidden layer were adjusted to the level of each feature role in determining the species class, so as to improve the level of training and testing accuracy. The proposed method has higher classification accuracy rate than basic ELM on all three datasets, which were 99%, 96%, and 82%, respectively.

  15. Added sugars: Definitions, classifications, metabolism and health implications

    Directory of Open Access Journals (Sweden)

    Tailane SCAPIN

    Full Text Available ABSTRACT The sugars added to foods have been featured in recent scientific research, including the publication of the World Health Organization recommendation to limit consumption of added sugars, based on studies on weight gain and dental caries. However, it is possible that there is evidence of an association between excessive consumption and other pathologies, but scientific studies have yet to investigate these associations. Moreover, there is no consensus on the descriptions and definitions of these sugars, with several terms and components used to designate them. In Brazil, there are few studies investigating added sugars, identifying a lack of discussion on this subject. This paper presents a literature review of sugars added to foods, from their definitions and classifications to the metabolism and health effects. The search was performed without limiting dates in the following databases: Web of Science, Scopus, PubMed and SciELO, as well as in national and international official sites. Keywords in Portuguese and English related to sugars added to foods were used, in combination with terms related to systematic review and meta-analysis studies, in order to find research linking added sugars consumption with health damage. The literature indicates that there is a relationship between excessive consumption of added sugars and various health outcomes, including weight gain, type 2 diabetes Mellitus, cancer, and cardiovascular diseases. The different descriptions of sugars in foods may confuse both food consumers and researchers, since each term includes different components. Thus, it is suggested to use the standardized term “added sugar” as the most suitable term for the broader population to understand, because it indicates that those sugars are not natural food components.

  16. Classification of labour markets in the Silesian Province (Poland

    Directory of Open Access Journals (Sweden)

    Sitek Sławomir

    2015-03-01

    Full Text Available The purpose of this article is to try to classify labour markets of the Silesian Province on the municipality level. The proposed solution of grouping labour markets is based on three criteria: the size of the labour market measured by a number of jobs, the weight of the labour market expressed with a proportion of the number of jobs to the size of the population and that scale of the impact that is a proportion of the commuters to the ones leaving for work. As a result of the assumed criteria the municipalities have been grouped according to their meaning on the labour market, at the same time identifying weaker and stronger labour markets. The first stage of the research was to divide the municipal labour markets according to the number of the employed. As a result territorial units were grouped into 4 classes (small, medium, big and huge including in total 9 subclasses. Then the municipal labour markets were sorted according to their weight and the scale of their impact, verifying their position in this way. The research pointed out that a lot of labour markets in the Katowice conurbation showed lower levels than the assumptions. Consequently, it suggests polarization of the labour market of this urban unit that is mainly focused on Katowice and Gliwice. Higher parameters than the assumed ones were reached by several municipalities that are small or medium labour markets. In many cases these are municipalities where there are huge businesses connected with coal mining. A beneficial situation was noted in the southern part of the province that has a relatively steady situation on the labour market. The presented classification of labour markets can support the management process of local and regional development.

  17. Prediction and classification of respiratory motion

    CERN Document Server

    Lee, Suk Jin

    2014-01-01

    This book describes recent radiotherapy technologies including tools for measuring target position during radiotherapy and tracking-based delivery systems. This book presents a customized prediction of respiratory motion with clustering from multiple patient interactions. The proposed method contributes to the improvement of patient treatments by considering breathing pattern for the accurate dose calculation in radiotherapy systems. Real-time tumor-tracking, where the prediction of irregularities becomes relevant, has yet to be clinically established. The statistical quantitative modeling for irregular breathing classification, in which commercial respiration traces are retrospectively categorized into several classes based on breathing pattern are discussed as well. The proposed statistical classification may provide clinical advantages to adjust the dose rate before and during the external beam radiotherapy for minimizing the safety margin. In the first chapter following the Introduction  to this book, we...

  18. A Classification-based Review Recommender

    Science.gov (United States)

    O'Mahony, Michael P.; Smyth, Barry

    Many online stores encourage their users to submit product/service reviews in order to guide future purchasing decisions. These reviews are often listed alongside product recommendations but, to date, limited attention has been paid as to how best to present these reviews to the end-user. In this paper, we describe a supervised classification approach that is designed to identify and recommend the most helpful product reviews. Using the TripAdvisor service as a case study, we compare the performance of several classification techniques using a range of features derived from hotel reviews. We then describe how these classifiers can be used as the basis for a practical recommender that automatically suggests the mosthelpful contrasting reviews to end-users. We present an empirical evaluation which shows that our approach achieves a statistically significant improvement over alternative review ranking schemes.

  19. Deep-learnt classification of light curves

    DEFF Research Database (Denmark)

    Mahabal, Ashish; Gieseke, Fabian; Pai, Akshay Sadananda Uppinakudru

    2017-01-01

    is to derive statistical features from the time series and to use machine learning methods, generally supervised, to separate objects into a few of the standard classes. In this work, we transform the time series to two-dimensional light curve representations in order to classify them using modern deep......Astronomy light curves are sparse, gappy, and heteroscedastic. As a result standard time series methods regularly used for financial and similar datasets are of little help and astronomers are usually left to their own instruments and techniques to classify light curves. A common approach...... learning techniques. In particular, we show that convolutional neural networks based classifiers work well for broad characterization and classification. We use labeled datasets of periodic variables from CRTS survey and show how this opens doors for a quick classification of diverse classes with several...

  20. Cataract in small animals: classification and treatment

    Directory of Open Access Journals (Sweden)

    Fahiano Montiani Ferreira

    1997-02-01

    Full Text Available Cataract means any opacity present in the lens, lens capsule or both. The opacities may vary in size, location, shape and rate of progression. By slit-lamp biomicroscopy it is possible to examine them with precision, determining its exact location and peculiarities, resulting in a safe, accurate diagnosis. Due to its variable origin and appearance, several methods of classification have been used. Classification by aetiology, grade of maturity, location and age of the patients are presented in this review. Surgical removal is the only effective therapy for this disease. Among the surgical techniques available to this day, endocapsular phacoemulsification excells for its better results, despite of its high cost, if compared to classical intra and extra capsular facectomies.

  1. Classifications of objects on hyperspectral images

    DEFF Research Database (Denmark)

    Kucheryavskiy, Sergey

    . In the present work a classification method that combines classic image classification approach and MIA is proposed. The basic idea is to group all pixels and calculate spectral properties of the pixel group to be used further as a vector of predictors for calibration and class prediction. The grouping can...... be done with mathematical morphology methods applied to a score image where objects are well separated. In the case of small overlapping a watershed transformation can be applied to disjoint the objects. The method has been tested on several simulated and real cases and showed good results and significant...... improvements in comparison with a standard MIA approach. The results as well as method details will be reported....

  2. A Java-based tool for the design of classification microarrays.

    Science.gov (United States)

    Meng, Da; Broschat, Shira L; Call, Douglas R

    2008-08-04

    Classification microarrays are used for purposes such as identifying strains of bacteria and determining genetic relationships to understand the epidemiology of an infectious disease. For these cases, mixed microarrays, which are composed of DNA from more than one organism, are more effective than conventional microarrays composed of DNA from a single organism. Selection of probes is a key factor in designing successful mixed microarrays because redundant sequences are inefficient and limited representation of diversity can restrict application of the microarray. We have developed a Java-based software tool, called PLASMID, for use in selecting the minimum set of probe sequences needed to classify different groups of plasmids or bacteria. The software program was successfully applied to several different sets of data. The utility of PLASMID was illustrated using existing mixed-plasmid microarray data as well as data from a virtual mixed-genome microarray constructed from different strains of Streptococcus. Moreover, use of data from expression microarray experiments demonstrated the generality of PLASMID. In this paper we describe a new software tool for selecting a set of probes for a classification microarray. While the tool was developed for the design of mixed microarrays-and mixed-plasmid microarrays in particular-it can also be used to design expression arrays. The user can choose from several clustering methods (including hierarchical, non-hierarchical, and a model-based genetic algorithm), several probe ranking methods, and several different display methods. A novel approach is used for probe redundancy reduction, and probe selection is accomplished via stepwise discriminant analysis. Data can be entered in different formats (including Excel and comma-delimited text), and dendrogram, heat map, and scatter plot images can be saved in several different formats (including jpeg and tiff). Weights generated using stepwise discriminant analysis can be stored for

  3. Predictors of severe late radiotherapy-related toxicity after hyperfractionated radiotherapy with or without concomitant cisplatin in locally advanced head and neck cancer. Secondary retrospective analysis of a randomized phase III trial (SAKK 10/94)

    International Nuclear Information System (INIS)

    Ghadjar, Pirus; Simcock, Mathew; Zimmermann, Frank; Betz, Michael; Bodis, Stephan; Bernier, Jacques; Studer, Gabriela; Aebersold, Daniel M.

    2012-01-01

    Background and purpose: This secondary analysis was performed to identify predictive factors for severe late radiotherapy (RT)-related toxicity after treatment with hyperfractionated RT +/− concomitant cisplatin in locally advanced head and neck cancer. Materials and methods: Patients were retrospectively analyzed from the previously reported randomized phase III trial: SAKK 10/94. Severe late RT-related toxicity was defined as late RTOG ⩾ grade 3 toxicity starting 3 months after end of RT and/or potential treatment-related death within 3 years of randomization. Results: Two hundred and thirteen randomized patients were analyzed; 84 (39%) experienced severe late RT-related toxicity. With median follow-up of 9.7 years (range, 0.4–15.4 years), median time to severe late RT-related toxicity was 9.6 years. In the univariate Cox proportional hazards model the following variables were associated with severe late RT-related toxicity: advanced N-classification (p < 0.001); technically unresectable disease (p = 0.04); weight loss ratio (p = 0.003); supportive measures (p = 0.009) and severe acute dysphagia (p = 0.001). In the subsequent multivariate analysis all variables except use of supportive measures remained statistically significant. Conclusions: Chemotherapy did not appear to affect severe late RT-related toxicity, but advanced N-classification, technically unresectable disease, weight loss ratio, and severe acute dysphagia were independent predictive factors for severe late RT-related toxicity.

  4. Validation of ICDPIC software injury severity scores using a large regional trauma registry.

    Science.gov (United States)

    Greene, Nathaniel H; Kernic, Mary A; Vavilala, Monica S; Rivara, Frederick P

    2015-10-01

    Administrative or quality improvement registries may or may not contain the elements needed for investigations by trauma researchers. International Classification of Diseases Program for Injury Categorisation (ICDPIC), a statistical program available through Stata, is a powerful tool that can extract injury severity scores from ICD-9-CM codes. We conducted a validation study for use of the ICDPIC in trauma research. We conducted a retrospective cohort validation study of 40,418 patients with injury using a large regional trauma registry. ICDPIC-generated AIS scores for each body region were compared with trauma registry AIS scores (gold standard) in adult and paediatric populations. A separate analysis was conducted among patients with traumatic brain injury (TBI) comparing the ICDPIC tool with ICD-9-CM embedded severity codes. Performance in characterising overall injury severity, by the ISS, was also assessed. The ICDPIC tool generated substantial correlations in thoracic and abdominal trauma (weighted κ 0.87-0.92), and in head and neck trauma (weighted κ 0.76-0.83). The ICDPIC tool captured TBI severity better than ICD-9-CM code embedded severity and offered the advantage of generating a severity value for every patient (rather than having missing data). Its ability to produce an accurate severity score was consistent within each body region as well as overall. The ICDPIC tool performs well in classifying injury severity and is superior to ICD-9-CM embedded severity for TBI. Use of ICDPIC demonstrates substantial efficiency and may be a preferred tool in determining injury severity for large trauma datasets, provided researchers understand its limitations and take caution when examining smaller trauma datasets. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  5. Hazard classification or risk assessment

    DEFF Research Database (Denmark)

    Hass, Ulla

    2013-01-01

    The EU classification of substances for e.g. reproductive toxicants is hazard based and does not to address the risk suchsubstances may pose through normal, or extreme, use. Such hazard classification complies with the consumer's right to know. It is also an incentive to careful use and storage...

  6. Seismic texture classification. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Vinther, R.

    1997-12-31

    The seismic texture classification method, is a seismic attribute that can both recognize the general reflectivity styles and locate variations from these. The seismic texture classification performs a statistic analysis for the seismic section (or volume) aiming at describing the reflectivity. Based on a set of reference reflectivities the seismic textures are classified. The result of the seismic texture classification is a display of seismic texture categories showing both the styles of reflectivity from the reference set and interpolations and extrapolations from these. The display is interpreted as statistical variations in the seismic data. The seismic texture classification is applied to seismic sections and volumes from the Danish North Sea representing both horizontal stratifications and salt diapers. The attribute succeeded in recognizing both general structure of successions and variations from these. Also, the seismic texture classification is not only able to display variations in prospective areas (1-7 sec. TWT) but can also be applied to deep seismic sections. The seismic texture classification is tested on a deep reflection seismic section (13-18 sec. TWT) from the Baltic Sea. Applied to this section the seismic texture classification succeeded in locating the Moho, which could not be located using conventional interpretation tools. The seismic texture classification is a seismic attribute which can display general reflectivity styles and deviations from these and enhance variations not found by conventional interpretation tools. (LN)

  7. Efficient AUC optimization for classification

    NARCIS (Netherlands)

    Calders, T.; Jaroszewicz, S.; Kok, J.N.; Koronacki, J.; Lopez de Mantaras, R.; Matwin, S.; Mladenic, D.; Skowron, A.

    2007-01-01

    In this paper we show an efficient method for inducing classifiers that directly optimize the area under the ROC curve. Recently, AUC gained importance in the classification community as a mean to compare the performance of classifiers. Because most classification methods do not optimize this

  8. Dewey Decimal Classification: A Quagmire.

    Science.gov (United States)

    Gamaluddin, Ahmad Fouad

    1980-01-01

    A survey of 660 Pennsylvania school librarians indicates that, though there is limited professional interest in the Library of Congress Classification system, Dewey Decimal Classification (DDC) appears to be firmly entrenched. This article also discusses the relative merits of DDC, the need for a uniform system, librarianship preparation, and…

  9. 45 CFR 601.5 - Derivative classification.

    Science.gov (United States)

    2010-10-01

    ... CLASSIFICATION AND DECLASSIFICATION OF NATIONAL SECURITY INFORMATION § 601.5 Derivative classification. Distinct... 45 Public Welfare 3 2010-10-01 2010-10-01 false Derivative classification. 601.5 Section 601.5... classification guide, need not possess original classification authority. (a) If a person who applies derivative...

  10. 12 CFR 403.4 - Derivative classification.

    Science.gov (United States)

    2010-01-01

    ... SAFEGUARDING OF NATIONAL SECURITY INFORMATION § 403.4 Derivative classification. (a) Use of derivative classification. (1) Unlike original classification which is an initial determination, derivative classification... 12 Banks and Banking 4 2010-01-01 2010-01-01 false Derivative classification. 403.4 Section 403.4...

  11. 32 CFR 2001.15 - Classification guides.

    Science.gov (United States)

    2010-07-01

    ... 32 National Defense 6 2010-07-01 2010-07-01 false Classification guides. 2001.15 Section 2001.15..., NATIONAL ARCHIVES AND RECORDS ADMINISTRATION CLASSIFIED NATIONAL SECURITY INFORMATION Classification § 2001.15 Classification guides. (a) Preparation of classification guides. Originators of classification...

  12. [Definition, etiology, classification and presentation forms].

    Science.gov (United States)

    Mas Garriga, Xavier

    2014-01-01

    Osteoarthritis is defined as a degenerative process affecting the joints as a result of mechanical and biological disorders that destabilize the balance between the synthesis and degradation of joint cartilage, stimulating the growth of subchondral bone; chronic synovitis is also present. Currently, the joint is considered as a functional unit that includes distinct tissues, mainly cartilage, the synovial membrane, and subchondral bone, all of which are involved in the pathogenesis of the disease. Distinct risk factors for the development of osteoarthritis have been described: general, unmodifiable risk factors (age, sex, and genetic makeup), general, modifiable risk factors (obesity and hormonal factors) and local risk factors (prior joint anomalies and joint overload). Notable among the main factors related to disease progression are joint alignment defects and generalized osteoarthritis. Several classifications of osteoarthritis have been proposed but none is particularly important for the primary care management of the disease. These classifications include etiological (primary or idiopathic forms and secondary forms) and topographical (typical and atypical localizations) classifications, the Kellgren and Lawrence classification (radiological repercussions) and that of the American College of Rheumatology for osteoarthritis of the hand, hip and knee. The prevalence of knee osteoarthritis is 10.2% in Spain and shows a marked discrepancy between clinical and radiological findings. Hand osteoarthritis, with a prevalence of symptomatic involvement of around 6.2%, has several forms of presentation (nodal osteoarthritis, generalized osteoarthritis, rhizarthrosis, and erosive osteoarthritis). Symptomatic osteoarthritis of the hip affects between 3.5% and 5.6% of persons older than 50 years and has different radiological patterns depending on femoral head migration. Copyright © 2014 Elsevier España, S.L. All rights reserved.

  13. Determinants of weight regain after bariatric surgery.

    Science.gov (United States)

    Bastos, Emanuelle Cristina Lins; Barbosa, Emília Maria Wanderley Gusmão; Soriano, Graziele Moreira Silva; dos Santos, Ewerton Amorim; Vasconcelos, Sandra Mary Lima

    2013-01-01

    Bariatric surgery leads to an average loss of 60-75% of excess body weight with maximum weight loss in the period between 18 and 24 months postoperatively. However, several studies show that weight is regained from two years of operation. To identify the determinants of weight regain in post-bariatric surgery users. Prospective cross-sectional study with 64 patients who underwent bariatric surgery with postoperative time > 2 years valued at significant weight regain. The variables analyzed were age, sex, education, socioeconomic status, work activity related to food, time after surgery, BMI, percentage of excess weight loss, weight gain, attendance monitoring nutrition, lifestyle, eating habits, self-perception of appetite, daily use of nutritional supplements and quality of life. There were 57 (89%) women and 7 (11%) men, aged 41.76 ± 7.93 years and mean postoperative period of 53.4 ± 18.4 months. The average weight and BMI were respectively 127.48 ± 24.2 kg and 49.56 ± 6.7 kg/m2 at surgery. The minimum weight and BMI were achieved 73.0 ± 18.6 kg and 28.3 ± 5.5 kg/m2, reached in 23.7 ± 12 months postoperatively. Regained significant weight occurred in 18 (28.1%) cases. The mean postoperative period of 66 ± 8.3 months and work activities related to food showed statistical significance (p=000 and p=0.003) for the regained weight. Bariatric surgery promotes adequate reduction of excess body weight, with significant weight regain observed after five years; post-operative time and work activity related to eating out as determining factors for the occurrence of weight regain.

  14. Classification of diffuse lung diseases: why and how.

    Science.gov (United States)

    Hansell, David M

    2013-09-01

    The understanding of complex lung diseases, notably the idiopathic interstitial pneumonias and small airways diseases, owes as much to repeated attempts over the years to classify them as to any single conceptual breakthrough. One of the many benefits of a successful classification scheme is that it allows workers, within and between disciplines, to be clear that they are discussing the same disease. This may be of particular importance in the recruitment of individuals for a clinical trial that requires a standardized and homogeneous study population. Different specialties require fundamentally different things from a classification: for epidemiologic studies, a classification that requires categorization of individuals according to histopathologic pattern is not usually practicable. Conversely, a scheme that simply divides diffuse parenchymal disease into inflammatory and noninflammatory categories is unlikely to further the understanding about the pathogenesis of disease. Thus, for some disease groupings, for example, pulmonary vasculopathies, there may be several appropriate classifications, each with its merits and demerits. There has been an interesting shift in the past few years, from the accepted primacy of histopathology as the sole basis on which the classification of parenchymal lung disease has rested, to new ways of considering how these entities relate to each other. Some inventive thinking has resulted in new classifications that undoubtedly benefit patients and clinicians in their endeavor to improve management and outcome. The challenge of understanding the logic behind current classifications and their shortcomings are explored in various examples of lung diseases.

  15. Predictors of weight maintenance

    NARCIS (Netherlands)

    Pasman, W.J.; Saris, W.H.M.; Westerterp-Plantenga, M.S.

    1999-01-01

    Objective: To obtain predictors of weight maintenance after a weight-loss intervention. Research Methods and Procedures: An overall analysis of data from two-long intervention studies [n = 67 women; age: 37.9±1.0 years; body weight (BW): 87.0±1.2 kg; body mass index: 32.1±0.5 kg·m-2; % body fat:

  16. Robustness of weighted networks

    Science.gov (United States)

    Bellingeri, Michele; Cassi, Davide

    2018-01-01

    Complex network response to node loss is a central question in different fields of network science because node failure can cause the fragmentation of the network, thus compromising the system functioning. Previous studies considered binary networks where the intensity (weight) of the links is not accounted for, i.e. a link is either present or absent. However, in real-world networks the weights of connections, and thus their importance for network functioning, can be widely different. Here, we analyzed the response of real-world and model networks to node loss accounting for link intensity and the weighted structure of the network. We used both classic binary node properties and network functioning measure, introduced a weighted rank for node importance (node strength), and used a measure for network functioning that accounts for the weight of the links (weighted efficiency). We find that: (i) the efficiency of the attack strategies changed using binary or weighted network functioning measures, both for real-world or model networks; (ii) in some cases, removing nodes according to weighted rank produced the highest damage when functioning was measured by the weighted efficiency; (iii) adopting weighted measure for the network damage changed the efficacy of the attack strategy with respect the binary analyses. Our results show that if the weighted structure of complex networks is not taken into account, this may produce misleading models to forecast the system response to node failure, i.e. consider binary links may not unveil the real damage induced in the system. Last, once weighted measures are introduced, in order to discover the best attack strategy, it is important to analyze the network response to node loss using nodes rank accounting the intensity of the links to the node.

  17. ILAE Classification of the Epilepsies Position Paper of the ILAE Commission for Classification and Terminology

    Science.gov (United States)

    Scheffer, Ingrid E; Berkovic, Samuel; Capovilla, Giuseppe; Connolly, Mary B; French, Jacqueline; Guilhoto, Laura; Hirsch, Edouard; Jain, Satish; Mathern, Gary W.; Moshé, Solomon L; Nordli, Douglas R; Perucca, Emilio; Tomson, Torbjörn; Wiebe, Samuel; Zhang, Yue-Hua; Zuberi, Sameer M

    2017-01-01

    Summary The ILAE Classification of the Epilepsies has been updated to reflect our gain in understanding of the epilepsies and their underlying mechanisms following the major scientific advances which have taken place since the last ratified classification in 1989. As a critical tool for the practising clinician, epilepsy classification must be relevant and dynamic to changes in thinking, yet robust and translatable to all areas of the globe. Its primary purpose is for diagnosis of patients, but it is also critical for epilepsy research, development of antiepileptic therapies and communication around the world. The new classification originates from a draft document submitted for public comments in 2013 which was revised to incorporate extensive feedback from the international epilepsy community over several rounds of consultation. It presents three levels, starting with seizure type where it assumes that the patient is having epileptic seizures as defined by the new 2017 ILAE Seizure Classification. After diagnosis of the seizure type, the next step is diagnosis of epilepsy type, including focal epilepsy, generalized epilepsy, combined generalized and focal epilepsy, and also an unknown epilepsy group. The third level is that of epilepsy syndrome where a specific syndromic diagnosis can be made. The new classification incorporates etiology along each stage, emphasizing the need to consider etiology at each step of diagnosis as it often carries significant treatment implications. Etiology is broken into six subgroups, selected because of their potential therapeutic consequences. New terminology is introduced such as developmental and epileptic encephalopathy. The term benign is replaced by the terms self-limited and pharmacoresponsive, to be used where appropriate. It is hoped that this new framework will assist in improving epilepsy care and research in the 21st century. PMID:28276062

  18. A classification system for tableting behaviors of binary powder mixtures

    Directory of Open Access Journals (Sweden)

    Changquan Calvin Sun

    2016-08-01

    Full Text Available The ability to predict tableting properties of a powder mixture from individual components is of both fundamental and practical importance to the efficient formulation development of tablet products. A common tableting classification system (TCS of binary powder mixtures facilitates the systematic development of new knowledge in this direction. Based on the dependence of tablet tensile strength on weight fraction in a binary mixture, three main types of tableting behavior are identified. Each type is further divided to arrive at a total of 15 sub-classes. The proposed classification system lays a framework for a better understanding of powder interactions during compaction. Potential applications and limitations of this classification system are discussed.

  19. Classification of Pulse Waveforms Using Edit Distance with Real Penalty

    Directory of Open Access Journals (Sweden)

    Zhang Dongyu

    2010-01-01

    Full Text Available Abstract Advances in sensor and signal processing techniques have provided effective tools for quantitative research in traditional Chinese pulse diagnosis (TCPD. Because of the inevitable intraclass variation of pulse patterns, the automatic classification of pulse waveforms has remained a difficult problem. In this paper, by referring to the edit distance with real penalty (ERP and the recent progress in -nearest neighbors (KNN classifiers, we propose two novel ERP-based KNN classifiers. Taking advantage of the metric property of ERP, we first develop an ERP-induced inner product and a Gaussian ERP kernel, then embed them into difference-weighted KNN classifiers, and finally develop two novel classifiers for pulse waveform classification. The experimental results show that the proposed classifiers are effective for accurate classification of pulse waveform.

  20. Weight self-regulation process in adolescence: the relationship between control weight attitudes, behaviors and body weight status

    Directory of Open Access Journals (Sweden)

    Jordi ePich

    2015-05-01

    Full Text Available Adolescents’ self-control weight behaviors were assessed (n= 1961; 12-17 years old; 2007-2008 in the Balearic Islands, Spain. The study analyzed the relationships between body weight status, body image and self-weight concern, and actual attempts to lose weight by restrained eating and/or increased exercising. In terms of regulatory focus theory (RFT, we considered that efforts to lose or to maintain weight (successful or failed would be motivated either by a promotion focus (to show an attractive body, a prevention focus (to avoid social rejection of fatness, or both. Results showed that 41% of overweight boys and 25% of obese boys stated that they had never made any attempt to lose weight, and 13% and 4% in females. Around half of overweight boys and around a quarter of obese boys stated that they were Not at all concerned about weight gain, and girls’ percentages decreased to 13% and 11% respectively. By contrast 57% of normal weight girls monitored their weight and stated that they had tried to slim at least once. Weight self-regulation in females attempted to combine diet and exercise, while boys relied almost exclusively on exercise. Apparent lack of consciousness of body weight status among overweight boys, and more important, subsequent absence of behaviors to reduce their weight clearly challenges efforts to prevent obesity. We argue that several causes may be involved in this outcome, including unconscious emotional (self-defense and cognitive (dissonance mechanisms driven by perceived social stigmatization of obesity. The active participation of social values of male and female body image (strong vs. pretty and the existence of social habituation to overweight are suggested. A better knowledge of psychosocial mechanisms underlying adolescent weight self-control may improve obesity epidemics.