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Sample records for classifications severity weighting

  1. Weighted Radial Variation for Node Feature Classification

    CERN Document Server

    Andris, C

    2011-01-01

    Connections created from a node-edge matrix have been traditionally difficult to visualize and analyze because of the number of flows to be rendered in a limited feature or cartographic space. Because analyzing connectivity patterns is useful for understanding the complex dynamics of human and information flow that connect non-adjacent space, techniques that allow for visual data mining or static representations of system dynamics are a growing field of research. Here, we create a Weighted Radial Variation (WRV) technique to classify a set of nodes based on the configuration of their radially-emanating vector flows. Each entity's vector is syncopated in terms of cardinality, direction, length, and flow magnitude. The WRV process unravels each star-like entity's individual flow vectors on a 0-360{\\deg} spectrum, to form a unique signal whose distribution depends on the flow presence at each step around the entity, and is further characterized by flow distance and magnitude. The signals are processed with an un...

  2. Weighted Chebyshev distance classification method for hyperspectral imaging

    Science.gov (United States)

    Demirci, S.; Erer, I.; Ersoy, O.

    2015-06-01

    The main objective of classification is to partition the surface materials into non-overlapping regions by using some decision rules. For supervised classification, the hyperspectral imagery (HSI) is compared with the reflectance spectra of the material containing similar spectral characteristic. As being a spectral similarity based classification method, prediction of different level of upper and lower spectral boundaries of all classes spectral signatures across spectral bands constitutes the basic principles of the Multi-Scale Vector Tunnel Algorithm (MS-VTA) classification algorithm. The vector tunnel (VT) scaling parameters obtained from means and standard deviations of the class references are used. In this study, MS-VT method is improved and a spectral similarity based technique referred to as Weighted Chebyshev Distance (WCD) method for the supervised classification of HSI is introduced. This is also shown to be equivalent to the use of the WCD in which the weights are chosen as an inverse power of the standard deviation per spectral band. The use of WCD measures in terms of the inverse power of standard deviations and optimization of power parameter constitute the most important side of the study. The algorithms are trained with the same kinds of training sets, and their performances are calculated for the power of the standard deviation. During these studies, various levels of the power parameters are evaluated based on the efficiency of the algorithms for choosing the best values of the weights.

  3. A Common Weight Linear Optimization Approach for Multicriteria ABC Inventory Classification

    Directory of Open Access Journals (Sweden)

    S. M. Hatefi

    2015-01-01

    Full Text Available Organizations typically employ the ABC inventory classification technique to have an efficient control on a huge amount of inventory items. The ABC inventory classification problem is classification of a large amount of items into three groups: A, very important; B, moderately important; and C, relatively unimportant. The traditional ABC classification only accounts for one criterion, namely, the annual dollar usage of the items. But, there are other important criteria in real world which strongly affect the ABC classification. This paper proposes a novel methodology based on a common weight linear optimization model to solve the multiple criteria inventory classification problem. The proposed methodology enables the classification of inventory items via a set of common weights which is very essential in a fair classification. It has a remarkable computational saving when compared with the existing approaches and at the same time it needs no subjective information. Furthermore, it is easy enough to apply for managers. The proposed model is applied on an illustrative example and a case study taken from the literature. Both numerical results and qualitative comparisons with the existing methods reveal several merits of the proposed approach for ABC analysis.

  4. 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....

  5. Major depression and severe weight loss

    Directory of Open Access Journals (Sweden)

    Ntrogkounta Α.

    2015-10-01

    Full Text Available Α 25-year old patient was referred to the casualty department of the Community Mental Health Center of Central Sector of Thessaloniki from the emergency department of the Psychiatric Hospital of Thessaloniki, in order to manage symptoms of depression as long as her life- threating loss of weight. A. appeared to have depressive feelings, lack of appetite, lack of interest, withdrawal, sleep disorders, sexual disorders, low self-esteem and ideas of guilt. There were held 27 conferences. In the beginning there were supportive intervations in order to improve the depressive symptoms and to gain weight. Moreover we applied medication (SSRI's that after 6 months was stopped gradually, without any setback. There was an increase of weight, about 10 kg, which remained until the follow up one year later.

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

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    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.

  7. Epidemiology, severity classification, and outcome of moderate and severe traumatic brain injury: a prospective multicenter study

    NARCIS (Netherlands)

    Andriessen, T.M.J.C.; Horn, J.; Franschman, G.; Naalt, J. van der; Haitsma, I.; Jacobs, B.; Steyerberg, E.W.; Vos, P.E.

    2011-01-01

    Changes in the demographics, approach, and treatment of traumatic brain injury (TBI) patients require regular evaluation of epidemiological profiles, injury severity classification, and outcomes. This prospective multicenter study provides detailed information on TBI-related variables of 508 moderat

  8. Epidemiology, Severity Classification, and Outcome of Moderate and Severe Traumatic Brain Injury: A Prospective Multicenter Study

    NARCIS (Netherlands)

    T.M.J.C. Andriessen; J. Horn; G. Franschman; J. van der Naalt; I. Haitsma; B. Jacobs; E.W. Steyerberg; P.E. Vos

    2011-01-01

    Changes in the demographics, approach, and treatment of traumatic brain injury (TBI) patients require regular evaluation of epidemiological profiles, injury severity classification, and outcomes. This prospective multicenter study provides detailed information on TBI-related variables of 508 moderat

  9. Epidemiology, Severity Classification, and Outcome of Moderate and Severe Traumatic Brain Injury : A Prospective Multicenter Study

    NARCIS (Netherlands)

    Andriessen, Teuntje M. J. C.; Horn, Janneke; Franschman, Gaby; van der Naalt, Joukje; Haitsma, Iain; Jacobs, Bram; Steyerberg, Ewout W.; Vos, Pieter E.

    2011-01-01

    Changes in the demographics, approach, and treatment of traumatic brain injury (TBI) patients require regular evaluation of epidemiological profiles, injury severity classification, and outcomes. This prospective multicenter study provides detailed information on TBI-related variables of 508 moderat

  10. Combining atlas based segmentation and intensity classification with nearest neighbor transform and accuracy weighted vote.

    Science.gov (United States)

    Sdika, Michaël

    2010-04-01

    In this paper, different methods to improve atlas based segmentation are presented. The first technique is a new mapping of the labels of an atlas consistent with a given intensity classification segmentation. This new mapping combines the two segmentations using the nearest neighbor transform and is especially effective for complex and folded regions like the cortex where the registration is difficult. Then, in a multi atlas context, an original weighting is introduced to combine the segmentation of several atlases using a voting procedure. This weighting is derived from statistical classification theory and is computed offline using the atlases as a training dataset. Concretely, the accuracy map of each atlas is computed and the vote is weighted by the accuracy of the atlases. Numerical experiments have been performed on publicly available in vivo datasets and show that, when used together, the two techniques provide an important improvement of the segmentation accuracy.

  11. Weight-Loss Surgery Pays Off for Severely Obese Teens

    Science.gov (United States)

    ... page: https://medlineplus.gov/news/fullstory_161700.html Weight-Loss Surgery Pays Off for Severely Obese Teens Boosts ... 26, 2016 WEDNESDAY, Oct. 26, 2016 (HealthDay News) -- Weight-loss surgeries can help severely obese teens shed pounds. ...

  12. Classification of CT examinations for COPD visual severity analysis

    Science.gov (United States)

    Tan, Jun; Zheng, Bin; Wang, Xingwei; Pu, Jiantao; Gur, David; Sciurba, Frank C.; Leader, J. Ken

    2012-03-01

    In this study we present a computational method of CT examination classification into visual assessed emphysema severity. The visual severity categories ranged from 0 to 5 and were rated by an experienced radiologist. The six categories were none, trace, mild, moderate, severe and very severe. Lung segmentation was performed for every input image and all image features are extracted from the segmented lung only. We adopted a two-level feature representation method for the classification. Five gray level distribution statistics, six gray level co-occurrence matrix (GLCM), and eleven gray level run-length (GLRL) features were computed for each CT image depicted segment lung. Then we used wavelets decomposition to obtain the low- and high-frequency components of the input image, and again extract from the lung region six GLCM features and eleven GLRL features. Therefore our feature vector length is 56. The CT examinations were classified using the support vector machine (SVM) and k-nearest neighbors (KNN) and the traditional threshold (density mask) approach. The SVM classifier had the highest classification performance of all the methods with an overall sensitivity of 54.4% and a 69.6% sensitivity to discriminate "no" and "trace visually assessed emphysema. We believe this work may lead to an automated, objective method to categorically classify emphysema severity on CT exam.

  13. Clinical definition of COPD exacerbations and classification of their severity.

    Science.gov (United States)

    Caramori, Gaetano; Adcock, Ian M; Papi, Alberto

    2009-03-01

    A standardized definition of chronic obstructive pulmonary disease (COPD) exacerbation still represents an unmet need in respiratory medicine; definitions currently rely on clinical empiricism with little evidence-based scientific support. Exacerbations of COPD are certainly clear events in the mind of practicing physicians. However, when one tries to provide simple concepts such as their definition and classification of severity, one realizes how little we know. Current symptom- and event-based definitions of a COPD exacerbation, as well as the classifications of the severity of COPD exacerbations, all have their own limitations. Efforts to assess the efficacy of new therapies in the treatment and prevention of COPD exacerbations have been hampered by the lack of a widely agreed upon and consistently used definition. There is a need for greater investment in research on COPD exacerbations in order to promote a better understanding of COPD exacerbations.

  14. A multiple-point spatially weighted k-NN method for object-based classification

    Science.gov (United States)

    Tang, Yunwei; Jing, Linhai; Li, Hui; Atkinson, Peter M.

    2016-10-01

    Object-based classification, commonly referred to as object-based image analysis (OBIA), is now commonly regarded as able to produce more appealing classification maps, often of greater accuracy, than pixel-based classification and its application is now widespread. Therefore, improvement of OBIA using spatial techniques is of great interest. In this paper, multiple-point statistics (MPS) is proposed for object-based classification enhancement in the form of a new multiple-point k-nearest neighbour (k-NN) classification method (MPk-NN). The proposed method first utilises a training image derived from a pre-classified map to characterise the spatial correlation between multiple points of land cover classes. The MPS borrows spatial structures from other parts of the training image, and then incorporates this spatial information, in the form of multiple-point probabilities, into the k-NN classifier. Two satellite sensor images with a fine spatial resolution were selected to evaluate the new method. One is an IKONOS image of the Beijing urban area and the other is a WorldView-2 image of the Wolong mountainous area, in China. The images were object-based classified using the MPk-NN method and several alternatives, including the k-NN, the geostatistically weighted k-NN, the Bayesian method, the decision tree classifier (DTC), and the support vector machine classifier (SVM). It was demonstrated that the new spatial weighting based on MPS can achieve greater classification accuracy relative to the alternatives and it is, thus, recommended as appropriate for object-based classification.

  15. Deep neck infections - classification in levels of severity

    Directory of Open Access Journals (Sweden)

    Coelho, Marina Serrato

    2009-06-01

    Full Text Available Introduction: The cervical spaces infections compose severe pictures and result in a high degree of mortality when they evolve with complications. Objective: To set up a graduation protocol of the cervical abscesses and organize a sequence to treat these patients. Method: We carried out a retrospective study of 150 patients with cervical abscess in which we evaluated the clinical impression, general state, respiratory state, locoregional state, antibiotics used and comorbidity. Then we organized a classification with severity levels. Results: The mean age was of 31 years old and in 37% of the cases the origin was dental. In the locoregional evaluation in 67% the affection expanded up to level I and II. According to the severity, the patients were classified as follows: Level I (46%, II (36%, III (15% and IV (3%. Only antibiotic therapy was used in 27% of the cases. The association with surgery occurred in 73% Conclusion: The therapeutic procedure standardization and its classification in severity is essential for the service systematization and reduction of morbimortality.

  16. The Influence of Weight-Loss Expectations on Weight Loss and of Weight-Loss Satisfaction on Weight Maintenance in Severe Obesity.

    Science.gov (United States)

    Calugi, Simona; Marchesini, Giulio; El Ghoch, Marwan; Gavasso, Ilaria; Dalle Grave, Riccardo

    2017-01-01

    Conflicting evidence exists as to whether cognitive mechanisms contribute to weight loss and maintenance. To assess the influence of weight-loss expectations on weight loss, and of weight-loss satisfaction on weight maintenance, in individuals with severe obesity. A randomized controlled trial comparing two types of energy-restricted diets (high protein vs high carbohydrate) combined with weight-loss cognitive behavioral therapy, conducted over 51 weeks and divided into two phases: weight-loss phase (3 weeks of inpatient treatment and 24 weeks of outpatient treatment) and weight maintenance phase (24 weeks of outpatient treatment). Eighty-eight participants with severe obesity (mean age=46.7 years and mean body mass index=45.6), referred to an eating and weight disorders clinical service, were studied. Body weight was assessed at baseline, and after 3, 27 (end of weight-loss phase), and 51 weeks (end of weight maintenance phase). Weight loss expectations were assessed at the time of enrollment, and weight-loss satisfaction was assessed after 27 weeks. The relationship between weight-loss expectations and weight loss was assessed using a linear mixed model. The association between weight-loss satisfaction and final outcomes was tested by linear regression. The two groups had similar weight-loss expectations and satisfaction, and their results were therefore pooled. In general, the total amount of expected weight loss (in kilograms), but not the percentage of expected weight loss, predicted weight loss, and both satisfaction with weight loss and the amount of weight lost (in kilograms) were independent predictors of weight maintenance. Higher expected weight loss improves weight loss, and both the total amount of weight lost and satisfaction with weight loss are associated with weight-loss maintenance at 1-year follow-up. Copyright © 2017 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.

  17. Rome III functional dyspepsia symptoms classification: Severity vs frequency.

    Science.gov (United States)

    Carbone, F; Holvoet, L; Vanuytsel, T; Tack, J

    2017-06-01

    The Rome III criteria subdivide functional dyspepsia (FD) in the epigastric pain syndrome (EPS) and the postprandial distress syndrome (PDS) based on the frequency of the symptoms to optimize the diagnostic and therapeutic approach. However, it is unclear to which extent the frequency of the symptoms is related to their severity. Our aim was to explore the frequency and severity of dyspeptic symptoms and their relationship in FD patients. Functional dyspepsia patients fulfilling the Rome III diagnostic completed a questionnaire that evaluated the frequency and severity of FD symptoms. The concordance between the severity and frequency categories was analyzed by means of spearman correlation and the concordance correlation coefficient (ρc ). In the entire patient cohort (n=421), the classification of symptoms severity and frequency showed good concordance for all symptoms. In the EPS subgroup (n=….), the symptom severity and frequency score of epigastric pain showed a poor correlation (r=.28; ρc =0.07). The PDS subgroup (n=…) showed a good correlation for most of the symptoms. Due to its limited occurrence in this group, the correlation of the severity and frequency scores for epigastric pain is of little relevance (r=.79; ρc =0.58). The overlap EPS-PDS group showed good correlation for most of the symptoms, except for epigastric pain (pain r=.24; ρc =0.09). We conclude that the information given by the assessment of frequency and severity of PDS symptoms is comparable and hence one of the scores sufficiently identifies symptom pattern in PDS patients. In EPS patients, both the symptom frequency and severity should be taken into account as two separate entities. © 2017 John Wiley & Sons Ltd.

  18. Severe acute malnutrition in very low birth weight preterm infants.

    Science.gov (United States)

    Enweronu-Laryea, Christabel C; Aryee, Irene N A; Adei, Eunice A P

    2012-05-01

    Malnutrition in preterm low birth weight infants has adverse long-term metabolic, growth, and neurodevelopmental effects. In the past 3 decades, parenteral nutrition, enriched preterm formula, and fortification of human milk have been used to alleviate these adverse effects. Unfortified human breast milk does not provide sufficient nutrients for the growth and development of preterm infants at the volumes recommended; however, it is usually the only source of nutrition available for such infants in low-resource countries. Many newborns, including very low birth weight infants, are surviving in these countries because of concerted efforts to achieve the fourth millennium development goal. These efforts have not addressed the nutrition needs of sick preterm very low birth weight infants. The authors report 3 cases of severe acute malnutrition in very low birth weight newborns and suggest possible interventions.

  19. Classification algorithms for predicting sleepiness and sleep apnea severity.

    Science.gov (United States)

    Eiseman, Nathaniel A; Westover, M Brandon; Mietus, Joseph E; Thomas, Robert J; Bianchi, Matt T

    2012-02-01

    Identifying predictors of subjective sleepiness and severity of sleep apnea are important yet challenging goals in sleep medicine. Classification algorithms may provide insights, especially when large data sets are available. We analyzed polysomnography and clinical features available from the Sleep Heart Health Study. The Epworth Sleepiness Scale and the apnea-hypopnea index were the targets of three classifiers: k-nearest neighbor, naive Bayes and support vector machine algorithms. Classification was based on up to 26 features including demographics, polysomnogram, and electrocardiogram (spectrogram). Naive Bayes was best for predicting abnormal Epworth class (0-10 versus 11-24), although prediction was weak: polysomnogram features had 16.7% sensitivity and 88.8% specificity; spectrogram features had 5.3% sensitivity and 96.5% specificity. The support vector machine performed similarly to naive Bayes for predicting sleep apnea class (0-5 versus >5): 59.0% sensitivity and 74.5% specificity using clinical features and 43.4% sensitivity and 83.5% specificity using spectrographic features compared with the naive Bayes classifier, which had 57.5% sensitivity and 73.7% specificity (clinical), and 39.0% sensitivity and 82.7% specificity (spectrogram). Mutual information analysis confirmed the minimal dependency of the Epworth score on any feature, while the apnea-hypopnea index showed modest dependency on body mass index, arousal index, oxygenation and spectrogram features. Apnea classification was modestly accurate, using either clinical or spectrogram features, and showed lower sensitivity and higher specificity than common sleep apnea screening tools. Thus, clinical prediction of sleep apnea may be feasible with easily obtained demographic and electrocardiographic analysis, but the utility of the Epworth is questioned by its minimal relation to clinical, electrocardiographic, or polysomnographic features.

  20. [Classification and several mechanical properties of core composite resins].

    Science.gov (United States)

    Yamada, T; Hosoda, H; Tsurugai, T

    1990-03-01

    According to the classification proposed by Hosoda, six core resins could be divided into two categories on the basis of the elemental composition and size distribution of filler particles by SEM observation and EDX analysis. Furthermore, several mechanical properties of the resins were determined. The following facts were found: Bell Feel Core, Clearfil Core, Clearfil PhotoCore, Core Max, and Core Max II resins were classified as a semihybrid resin, and Microrest Core resin as a hybrid type resin. The elements detected in the resins by the EDX were Si, Zr, Al, Ba and La. The mechanical properties of the resins were shown to be highly stable at one day or one week after curing. The mechanical properties of the resins suggest that the subsequent crown preparation and impression taking should be postponed until the next appointment.

  1. A Weighted Block Dictionary Learning Algorithm for Classification

    OpenAIRE

    Zhongrong Shi

    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...

  2. Vertebral degenerative disc disease severity evaluation using random forest classification

    Science.gov (United States)

    Munoz, Hector E.; Yao, Jianhua; Burns, Joseph E.; Pham, Yasuyuki; Stieger, James; Summers, Ronald M.

    2014-03-01

    Degenerative disc disease (DDD) develops in the spine as vertebral discs degenerate and osseous excrescences or outgrowths naturally form to restabilize unstable segments of the spine. These osseous excrescences, or osteophytes, may progress or stabilize in size as the spine reaches a new equilibrium point. We have previously created a CAD system that detects DDD. This paper presents a new system to determine the severity of DDD of individual vertebral levels. This will be useful to monitor the progress of developing DDD, as rapid growth may indicate that there is a greater stabilization problem that should be addressed. The existing DDD CAD system extracts the spine from CT images and segments the cortical shell of individual levels with a dual-surface model. The cortical shell is unwrapped, and is analyzed to detect the hyperdense regions of DDD. Three radiologists scored the severity of DDD of each disc space of 46 CT scans. Radiologists' scores and features generated from CAD detections were used to train a random forest classifier. The classifier then assessed the severity of DDD at each vertebral disc level. The agreement between the computer severity score and the average radiologist's score had a quadratic weighted Cohen's kappa of 0.64.

  3. Dynamic & Attribute Weighted KNN for Document Classification Using Bootstrap Sampling

    Directory of Open Access Journals (Sweden)

    Dharmendra S Panwar,

    2014-11-01

    Full Text Available Although publicly accessible databases containing speech documents. It requires a great deal of time and effort required to keep them up to date is often burdensome. In an effort to help identify speaker of speech if text is available, text-mining tools, from the machine learning discipline, it can be applied to help in this process also. Here, we describe and evaluate document classification algorithms i.e. a combo pack of text mining and classification. This task asked participants to design classifiers for identifying documents containing speech related information in the main literature, and evaluated them against one another. Expected systems utilizes a novel approach of k -nearest neighbour classification and compare its performance by taking different values of k.

  4. 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... the Federal Food, Drug and Cosmetic Act. (3) The payment rate determined for an APC group...

  5. 78 FR 9349 - Medical Devices; Ophthalmic Devices; Classification of the Eyelid Weight

    Science.gov (United States)

    2013-02-08

    ... HUMAN SERVICES Food and Drug Administration 21 CFR Part 886 Medical Devices; Ophthalmic Devices; Classification of the Eyelid Weight AGENCY: Food and Drug Administration, HHS. ACTION: Proposed rule. SUMMARY: The Food and Drug Administration (FDA) is proposing to classify the eyelid weight into class...

  6. Pairwise FCM based feature weighting for improved classification of vertebral column disorders.

    Science.gov (United States)

    Unal, Yavuz; Polat, Kemal; Erdinc Kocer, H

    2014-03-01

    In this paper, an innovative data pre-processing method to improve the classification performance and to determine automatically the vertebral column disorders including disk hernia (DH), spondylolisthesis (SL) and normal (NO) groups has been proposed. In the classification of vertebral column disorders' dataset with three classes, a pairwise fuzzy C-means (FCM) based feature weighting method has been proposed. In this method, first of all, the vertebral column dataset has been grouped as pairwise (DH-SL, DH-NO, and SL-NO) and then these pairwise groups have been weighted using a FCM based feature set. These weighted groups have been classified using classifier algorithms including multilayer perceptron (MLP), k-nearest neighbor (k-NN), Naive Bayes, and support vector machine (SVM). The general classification performance has been obtained by averaging of classification accuracies obtained from pairwise classifier algorithms. To evaluate the performance of the proposed method, the classification accuracy, sensitivity, specificity, ROC curves, and f-measure have been used. Without the proposed feature weighting, the obtained f-measure values were 0.7738 for MLP classifier, 0.7021 for k-NN, 0.7263 for Naive Bayes, and 0.7298 for SVM classifier algorithms in the classification of vertebral column disorders' dataset with three classes. With the pairwise fuzzy C-means based feature weighting method, the obtained f-measure values were 0.9509 for MLP, 0.9313 for k-NN, 0.9603 for Naive Bayes, and 0.9468 for SVM classifier algorithms. The experimental results demonstrated that the proposed pairwise fuzzy C-means based feature weighting method is robust and effective in the classification of vertebral column disorders' dataset. In the future, this method could be used confidently for medical datasets with more classes.

  7. 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

  8. Evaluation of the traumatic coma data bank computed tomography classification for severe head injury

    NARCIS (Netherlands)

    Vos, P E; van Voskuilen, A C; Beems, T; Krabbe, P F; Vogels, O J

    2004-01-01

    This study determines the interrater and intrarater reliability of the Traumatic Coma Data Bank (TCDB) computed tomography (CT) scan classification for severe head injury. This classification grades the severity of the injury as follows: I = normal, II = diffuse injury, III = diffuse injury with swe

  9. Weighted K-Nearest Neighbor Classification Algorithm Based on Genetic Algorithm

    Directory of Open Access Journals (Sweden)

    Xuesong Yan

    2013-10-01

    Full Text Available K-Nearest Neighbor (KNN is one of the most popular algorithms for data classification. Many researchers have found that the KNN algorithm accomplishes very good performance in their experiments on different datasets. The traditional KNN text classification algorithm has limitations: calculation complexity, the performance is solely dependent on the training set, and so on. To overcome these limitations, an improved version of KNN is proposed in this paper, we use genetic algorithm combined with weighted KNN to improve its classification performance. and the experiment results shown that our proposed algorithm outperforms the KNN with greater accuracy.

  10. Using Discrete Loss Functions and Weighted Kappa for Classification: An Illustration Based on Bayesian Network Analysis

    Science.gov (United States)

    Zwick, Rebecca; Lenaburg, Lubella

    2009-01-01

    In certain data analyses (e.g., multiple discriminant analysis and multinomial log-linear modeling), classification decisions are made based on the estimated posterior probabilities that individuals belong to each of several distinct categories. In the Bayesian network literature, this type of classification is often accomplished by assigning…

  11. 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.

  12. Learning Weight Uncertainty with Stochastic Gradient MCMC for Shape Classification

    Energy Technology Data Exchange (ETDEWEB)

    Li, Chunyuan; Stevens, Andrew J.; Chen, Changyou; Pu, Yunchen; Gan, Zhe; Carin, Lawrence

    2016-08-10

    Learning the representation of shape cues in 2D & 3D objects for recognition is a fundamental task in computer vision. Deep neural networks (DNNs) have shown promising performance on this task. Due to the large variability of shapes, accurate recognition relies on good estimates of model uncertainty, ignored in traditional training of DNNs, typically learned via stochastic optimization. This paper leverages recent advances in stochastic gradient Markov Chain Monte Carlo (SG-MCMC) to learn weight uncertainty in DNNs. It yields principled Bayesian interpretations for the commonly used Dropout/DropConnect techniques and incorporates them into the SG-MCMC framework. Extensive experiments on 2D & 3D shape datasets and various DNN models demonstrate the superiority of the proposed approach over stochastic optimization. Our approach yields higher recognition accuracy when used in conjunction with Dropout and Batch-Normalization.

  13. Classification of finger extension and flexion of EMG and Cyberglove data with modified ICA weight matrix.

    Science.gov (United States)

    Naik, Ganesh R; Acharyya, Amit; Nguyen, Hung T

    2014-01-01

    This paper reports the classification of finger flexion and extension of surface Electromyography (EMG) and Cyberglove data using the modified Independent Component Analysis (ICA) weight matrix. The finger flexion and extension data are processed through Principal Component Analysis (PCA), and next separated using modified ICA for each individual with customized weight matrix. The extension and flexion features of sEMG and Cyberglove (extracted from modified ICA) were classified using Linear Discriminant Analysis (LDA) with near 90% classification accuracy. The applications of this study include Human Computer Interface (HCI), virtual reality and neural prosthetics.

  14. Algorithm for optimizing bipolar interconnection weights with applications in associative memories and multitarget classification.

    Science.gov (United States)

    Chang, S; Wong, K W; Zhang, W; Zhang, Y

    1999-08-10

    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.

  15. 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.

  16. Influence of Weight Classification on Walking and Jogging Energy Expenditure Prediction in Women

    Science.gov (United States)

    Heden, Timothy D.; LeCheminant, James D.; Smith, John D.

    2012-01-01

    The purpose of this study was to determine the influence of weight classification on predicting energy expenditure (EE) in women. Twelve overweight (body mass index [BMI] = 25-29.99 kg/m[superscript 2]) and 12 normal-weight (BMI = 18.5-24.99 kg/m[superscript 2]) women walked and jogged 1,609 m at 1.34 m.s[superscript -1] and 2.23 m.s[superscript…

  17. Discriminative likelihood score weighting based on acoustic-phonetic classification for speaker identification

    Science.gov (United States)

    Suh, Youngjoo; Kim, Hoirin

    2014-12-01

    In this paper, a new discriminative likelihood score weighting technique is proposed for speaker identification. The proposed method employs a discriminative weighting of frame-level log-likelihood scores with acoustic-phonetic classification in the Gaussian mixture model (GMM)-based speaker identification. Experiments performed on the Aurora noise-corrupted TIMIT database showed that the proposed approach provides meaningful performance improvement with an overall relative error reduction of 15.8% over the maximum likelihood-based baseline GMM approach.

  18. 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.

  19. Hidden semi-Markov Model based earthquake classification system using Weighted Finite-State Transducers

    Directory of Open Access Journals (Sweden)

    M. Beyreuther

    2011-02-01

    Full Text Available Automatic earthquake detection and classification is required for efficient analysis of large seismic datasets. Such techniques are particularly important now because access to measures of ground motion is nearly unlimited and the target waveforms (earthquakes are often hard to detect and classify. Here, we propose to use models from speech synthesis which extend the double stochastic models from speech recognition by integrating a more realistic duration of the target waveforms. The method, which has general applicability, is applied to earthquake detection and classification. First, we generate characteristic functions from the time-series. The Hidden semi-Markov Models are estimated from the characteristic functions and Weighted Finite-State Transducers are constructed for the classification. We test our scheme on one month of continuous seismic data, which corresponds to 370 151 classifications, showing that incorporating the time dependency explicitly in the models significantly improves the results compared to Hidden Markov Models.

  20. The clinical utility of the GOLD classification of COPD disease severity in pulmonary rehabilitation

    NARCIS (Netherlands)

    Huijsmans, Rosalie J.; de Haan, Arnold; ten Hacken, Nick N. H. T.; Straver, Renata V. M.; van't Hu, Alex J.

    2008-01-01

    The Global Initiative for Chronic Obstructive Lung Disease (GOLD) has introduced a four-stage classification of chronic obstructive pulmonary disease (COPD) severity. The present study investigated the discriminatory capacity of the GOLD classification for health status outcomes in patients with COP

  1. Hyperspectral Image Classification Based on the Weighted Probabilistic Fusion of Multiple Spectral-spatial Features

    Directory of Open Access Journals (Sweden)

    ZHANG Chunsen

    2015-08-01

    Full Text Available A hyperspectral images classification method based on the weighted probabilistic fusion of multiple spectral-spatial features was proposed in this paper. First, the minimum noise fraction (MNF approach was employed to reduce the dimension of hyperspectral image and extract the spectral feature from the image, then combined the spectral feature with the texture feature extracted based on gray level co-occurrence matrix (GLCM, the multi-scale morphological feature extracted based on OFC operator and the end member feature extracted based on sequential maximum angle convex cone (SMACC method to form three spectral-spatial features. Afterwards, support vector machine (SVM classifier was used for the classification of each spectral-spatial feature separately. Finally, we established the weighted probabilistic fusion model and applied the model to fuse the SVM outputs for the final classification result. In order to verify the proposed method, the ROSIS and AVIRIS image were used in our experiment and the overall accuracy reached 97.65% and 96.62% separately. The results indicate that the proposed method can not only overcome the limitations of traditional single-feature based hyperspectral image classification, but also be superior to conventional VS-SVM method and probabilistic fusion method. The classification accuracy of hyperspectral images was improved effectively.

  2. Fast weighted K-view-voting algorithm for image texture classification

    Science.gov (United States)

    Liu, Hong; Lan, Yihua; Wang, Qian; Jin, Renchao; Song, Enmin; Hung, Chih-Cheng

    2012-02-01

    We propose an innovative and efficient approach to improve K-view-template (K-view-T) and K-view-datagram (K-view-D) algorithms for image texture classification. The proposed approach, called the weighted K-view-voting algorithm (K-view-V), uses a novel voting method for texture classification and an accelerating method based on the efficient summed square image (SSI) scheme as well as fast Fourier transform (FFT) to enable overall faster processing. Decision making, which assigns a pixel to a texture class, occurs by using our weighted voting method among the ``promising'' members in the neighborhood of a classified pixel. In other words, this neighborhood consists of all the views, and each view has a classified pixel in its territory. Experimental results on benchmark images, which are randomly taken from Brodatz Gallery and natural and medical images, show that this new classification algorithm gives higher classification accuracy than existing K-view algorithms. In particular, it improves the accurate classification of pixels near the texture boundary. In addition, the proposed acceleration method improves the processing speed of K-view-V as it requires much less computation time than other K-view algorithms. Compared with the results of earlier developed K-view algorithms and the gray level co-occurrence matrix (GLCM), the proposed algorithm is more robust, faster, and more accurate.

  3. Improving land cover classification using input variables derived from a geographically weighted principal components analysis

    Science.gov (United States)

    Comber, Alexis J.; Harris, Paul; Tsutsumida, Narumasa

    2016-09-01

    This study demonstrates the use of a geographically weighted principal components analysis (GWPCA) of remote sensing imagery to improve land cover classification accuracy. A principal components analysis (PCA) is commonly applied in remote sensing but generates global, spatially-invariant results. GWPCA is a local adaptation of PCA that locally transforms the image data, and in doing so, can describe spatial change in the structure of the multi-band imagery, thus directly reflecting that many landscape processes are spatially heterogenic. In this research the GWPCA localised loadings of MODIS data are used as textural inputs, along with GWPCA localised ranked scores and the image bands themselves to three supervised classification algorithms. Using a reference data set for land cover to the west of Jakarta, Indonesia the classification procedure was assessed via training and validation data splits of 80/20, repeated 100 times. For each classification algorithm, the inclusion of the GWPCA loadings data was found to significantly improve classification accuracy. Further, but more moderate improvements in accuracy were found by additionally including GWPCA ranked scores as textural inputs, data that provide information on spatial anomalies in the imagery. The critical importance of considering both spatial structure and spatial anomalies of the imagery in the classification is discussed, together with the transferability of the new method to other studies. Research topics for method refinement are also suggested.

  4. A Framework for Security Components Anomalies Severity Evaluation and Classification

    Directory of Open Access Journals (Sweden)

    Kamel Karoui

    2013-07-01

    Full Text Available Security components such as firewalls, IDS and IPS, are the most widely adopted security devices fornetwork protection.These components are often implemented with several errors (or anomalies that aresometimes critical. To ensure the security of their networks, administrators should detect these anomaliesand correct them. Before correcting the detected anomalies, the administrator should evaluate and classifythese latter to determine the best strategy to correct them. In this work, we propose a framework to assessand classify the detected anomalies using a three evaluation criteria: a quantitative evaluation, a semanticevaluation and multi-anomalies evaluation. The proposed process, convenient in an audit process, will bedetailed by a case study to demonstrate its usefulness

  5. Contextual convolutional neural networks for lung nodule classification using Gaussian-weighted average image patches

    Science.gov (United States)

    Lee, Haeil; Lee, Hansang; Park, Minseok; Kim, Junmo

    2017-03-01

    Lung cancer is the most common cause of cancer-related death. To diagnose lung cancers in early stages, numerous studies and approaches have been developed for cancer screening with computed tomography (CT) imaging. In recent years, convolutional neural networks (CNN) have become one of the most common and reliable techniques in computer aided detection (CADe) and diagnosis (CADx) by achieving state-of-the-art-level performances for various tasks. In this study, we propose a CNN classification system for false positive reduction of initially detected lung nodule candidates. First, image patches of lung nodule candidates are extracted from CT scans to train a CNN classifier. To reflect the volumetric contextual information of lung nodules to 2D image patch, we propose a weighted average image patch (WAIP) generation by averaging multiple slice images of lung nodule candidates. Moreover, to emphasize central slices of lung nodules, slice images are locally weighted according to Gaussian distribution and averaged to generate the 2D WAIP. With these extracted patches, 2D CNN is trained to achieve the classification of WAIPs of lung nodule candidates into positive and negative labels. We used LUNA 2016 public challenge database to validate the performance of our approach for false positive reduction in lung CT nodule classification. Experiments show our approach improves the classification accuracy of lung nodules compared to the baseline 2D CNN with patches from single slice image.

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

    OpenAIRE

    E. Parvinnia; M. Sabeti; M. Zolghadri Jahromi; Boostani, R

    2014-01-01

    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 near...

  7. 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.…

  8. Local classification: Locally weighted-partial least squares-discriminant analysis (LW-PLS-DA).

    Science.gov (United States)

    Bevilacqua, Marta; Marini, Federico

    2014-08-01

    The possibility of devising a simple, flexible and accurate non-linear classification method, by extending the locally weighted partial least squares (LW-PLS) approach to the cases where the algorithm is used in a discriminant way (partial least squares discriminant analysis, PLS-DA), is presented. In particular, to assess which category an unknown sample belongs to, the proposed algorithm operates by identifying which training objects are most similar to the one to be predicted and building a PLS-DA model using these calibration samples only. Moreover, the influence of the selected training samples on the local model can be further modulated by adopting a not uniform distance-based weighting scheme which allows the farthest calibration objects to have less impact than the closest ones. The performances of the proposed locally weighted-partial least squares-discriminant analysis (LW-PLS-DA) algorithm have been tested on three simulated data sets characterized by a varying degree of non-linearity: in all cases, a classification accuracy higher than 99% on external validation samples was achieved. Moreover, when also applied to a real data set (classification of rice varieties), characterized by a high extent of non-linearity, the proposed method provided an average correct classification rate of about 93% on the test set. By the preliminary results, showed in this paper, the performances of the proposed LW-PLS-DA approach have proved to be comparable and in some cases better than those obtained by other non-linear methods (k nearest neighbors, kernel-PLS-DA and, in the case of rice, counterpropagation neural networks).

  9. 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.

  10. Reduction from cost-sensitive ordinal ranking to weighted binary classification.

    Science.gov (United States)

    Lin, Hsuan-Tien; Li, Ling

    2012-05-01

    We present a reduction framework from ordinal ranking to binary classification. The framework consists of three steps: extracting extended examples from the original examples, learning a binary classifier on the extended examples with any binary classification algorithm, and constructing a ranker from the binary classifier. Based on the framework, we show that a weighted 0/1 loss of the binary classifier upper-bounds the mislabeling cost of the ranker, both error-wise and regret-wise. Our framework allows not only the design of good ordinal ranking algorithms based on well-tuned binary classification approaches, but also the derivation of new generalization bounds for ordinal ranking from known bounds for binary classification. In addition, our framework unifies many existing ordinal ranking algorithms, such as perceptron ranking and support vector ordinal regression. When compared empirically on benchmark data sets, some of our newly designed algorithms enjoy advantages in terms of both training speed and generalization performance over existing algorithms. In addition, the newly designed algorithms lead to better cost-sensitive ordinal ranking performance, as well as improved listwise ranking performance.

  11. Methods for Determining the Statistical Significance of Enrichment or Depletion of Gene Ontology Classifications under Weighted Membership

    Directory of Open Access Journals (Sweden)

    Ernesto eIacucci

    2012-02-01

    Full Text Available High-throughput molecular biology studies, such as microarray assays of gene expression, two-hybrid experiments for detecting protein interactions, or ChIP-Seq experiments for transcription factor binding, often result in an interesting set of genes—say, genes that are co-expressed or bound by the same factor. One way of understanding the biological meaning of such a set is to consider what processes or functions, as defined in an ontology, are over-represented (enriched or under-represented (depleted among genes in the set. Usually, the significance of enrichment or depletion scores is based on simple statistical models and on the membership of genes in different classifications. We consider the more general problem of computing p-values for arbitrary integer additive statistics, or weighted membership functions. Such membership functions can be used to represent, for example, prior knowledge on the role of certain genes or classifications, differential importance of different classifications or genes to the experimenter, hierarchical relationships between classifications, or different degrees of interestingness or evidence for specific genes. We describe a generic dynamic programming algorithm that can compute exact p-values for arbitrary integer additive statistics. We also describe several optimizations for important special cases, which can provide orders-of-magnitude speed up in the computations. We apply our methods to datasets describing oxidative phosphorylation and parturition and compare p-values based on computations of several different statistics for measuring enrichment. We find major differences between p-values resulting from these statistics, and that some statistics recover gold standard annotations of the data better than others. Our work establishes a theoretical and algorithmic basis for far richer notions of enrichment or depletion of gene sets with respect to gene ontologies than has previously been available.

  12. 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

  13. [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

  14. Evaluation of the traditional and revised WHO classifications of Dengue disease severity.

    Directory of Open Access Journals (Sweden)

    Federico Narvaez

    2011-11-01

    Full Text Available Dengue is a major public health problem worldwide and continues to increase in incidence. Dengue virus (DENV infection leads to a range of outcomes, including subclinical infection, undifferentiated febrile illness, Dengue Fever (DF, life-threatening syndromes with fluid loss and hypotensive shock, or other severe manifestations such as bleeding and organ failure. The long-standing World Health Organization (WHO dengue classification and management scheme was recently revised, replacing DF, Dengue Hemorrhagic Fever (DHF, and Dengue Shock Syndrome (DSS with Dengue without Warning Signs, Dengue with Warning Signs (abdominal pain, persistent vomiting, fluid accumulation, mucosal bleeding, lethargy, liver enlargement, increasing hematocrit with decreasing platelets and Severe Dengue (SD; dengue with severe plasma leakage, severe bleeding, or organ failure. We evaluated the traditional and revised classification schemes against clinical intervention levels to determine how each captures disease severity using data from five years (2005-2010 of a hospital-based study of pediatric dengue in Managua, Nicaragua. Laboratory-confirmed dengue cases (n = 544 were categorized using both classification schemes and by level of care (I-III. Category I was out-patient care, Category II was in-patient care that did not meet criteria for Category III, which included ICU admission, ventilation, administration of inotropic drugs, or organ failure. Sensitivity and specificity to capture Category III care for DHF/DSS were 39.0% and 75.5%, respectively; sensitivity and specificity for SD were 92.1% and 78.5%, respectively. In this data set, DENV-2 was found to be significantly associated with DHF/DSS; however, this association was not observed with the revised classification. Among dengue-confirmed cases, the revised WHO classification for severe dengue appears to have higher sensitivity and specificity to identify cases in need of heightened care, although it is no

  15. 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. Method

  16. Performance of Burn-Severity Metrics and Classification in Oak Woodlands and Grasslands

    Directory of Open Access Journals (Sweden)

    Michael C. Stambaugh

    2015-08-01

    Full Text Available Burn severity metrics and classification have yet to be tested for many eastern U.S. deciduous vegetation types, but, if suitable, would be valuable for documenting and monitoring landscape-scale restoration projects that employ prescribed fire treatments. Here we present a performance analysis of the Composite Burn Index (CBI and its relationship to spectral data (differenced Normalized Burn Ratio (dNBR and its relative form (RdNBR across an oak woodland - grassland landscape in southwestern Oklahoma, USA. Correlation and regression analyses were used to compare CBI strata, assess models describing burn severity, and determine thresholds for burn severity classes. Confusion matrices were used to assess burn severity classification accuracy. Our findings suggest that dNBR and RdNBR, thresholded using total CBI, can produce an accurate burn severity map in oak woodlands, particularly from an initial assessment period. Lower accuracies occurred for burn severity classifications of grasslands and raises questions related to definitions and detection of burn severity for grasslands, particularly in transition to more densely treed structures such as savannas and woodlands.

  17. Smartphone application for classification of motor impairment severity in Parkinson's disease.

    Science.gov (United States)

    Printy, Blake P; Renken, Lindsey M; Herrmann, John P; Lee, Isac; Johnson, Bryant; Knight, Emily; Varga, Georgeta; Whitmer, Diane

    2014-01-01

    Advanced hardware components embedded in modern smartphones have the potential to serve as widely available medical diagnostic devices, particularly when used in conjunction with custom software and tested algorithms. The goal of the present pilot study was to develop a smartphone application that could quantify the severity of Parkinson's disease (PD) motor symptoms, and in particular, bradykinesia. We developed an iPhone application that collected kinematic data from a small cohort of PD patients during guided movement tasks and extracted quantitative features using signal processing techniques. These features were used in a classification model trained to differentiate between overall motor impairment of greater and lesser severity using standard clinical scores provided by a trained neurologist. Using a support vector machine classifier, a classification accuracy of 0.945 was achieved under 6-fold cross validation, and several features were shown to be highly discriminatory between more severe and less severe motor impairment by area under the receiver operating characteristic curve (AUC > 0.85). Accurate classification for discriminating between more severe and less severe bradykinesia was not achieved with these methods. We discuss future directions of this work and suggest that this platform is a first step toward development of a smartphone application that has the potential to provide clinicians with a method for monitoring patients between clinical appointments.

  18. 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.

  19. 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.

  20. Classification of Cruciate Ligament Dysplasia and the Severity of Congenital Fibular Deficiency.

    Science.gov (United States)

    Walker, Janet L; Milbrandt, Todd A; Iwinski, Henry J; Talwalkar, Vishwas R

    2016-12-22

    Dysplasia of the cruciate ligaments has been found in many patients with congenital fibular deficiency. A recent classification system has shown that radiographic tibial spine changes can predict the hypoplasia and aplasia of the cruciate ligaments. We used this radiographic classification to determine the frequency of these abnormalities and how they correlate with the severity of fibular deficiency and lateral femoral condylar hypoplasia. Using a hospital database search for fibular deficiency, 99 patients ≥6 years with unilateral fibular deficiency were identified. Existing radiographs of both knees were available for 75 patients and reviewed for the tibial spine changes and Achterman and Kalamchi classification of the fibular deficiency. Measurements of femoral condyle heights in 74 of 75 patients were recorded before any surgery to the distal femoral physis to assess lateral femoral condylar hypoplasia. Twenty-two patients had hypoplasia of the lateral tibial spine+normal medial spine, 29 had absence of the lateral tibial spine+hypoplastic medial spine, and 11 had absence of both tibial spines. Five tibial spines were normal and 8 were unclassifiable. The severity of the tibial spine dysplasia, particularly absence of the lateral tibial spine, correlated with the severity of the fibular deficiency. (Pdysplasia in fibular deficiency is directly correlated with the severity of fibular absence, lateral femoral condylar hypoplasia, and the absence of foot rays. This suggests that the embryological factors involved have a complex interplay for all of these clinical findings. Level III.

  1. Classification tree analysis of postal questionnaire data to identify risk of excessive gestational weight gain.

    Science.gov (United States)

    Fuller-Tyszkiewicz, Matthew; Skouteris, Helen; Hill, Briony; Teede, Helena; McPhie, Skye

    2016-01-01

    overweight/obese weight status during pregnancy increases risk of a range of adverse health outcomes for mother and child. Whereas identification of those who are overweight/obese pre-pregnancy and in early pregnancy is straightforward, prediction of who will experience excessive gestational weight gain (EGWG), and thus be at greater risk of becoming overweight or obese during pregnancy is more challenging. The present study sought to better identify those at risk of EGWG by exploring pre-pregnancy BMI as well as a range of psychosocial risk factors identified as risk factors in prior research. 225 pregnant women completed self-reported via postal survey measures of height, weight, and psychosocial variables at 16-18 weeks gestation, and reported their weight again at 32-34 weeks to calculate GWG. Classification and regression tree analysis (CART) was used to find subgroups in the data with increased risk of EGWG based on their pre-pregnancy BMI and psychosocial risk factor scores at Time 1. CART confirmed that self-reported BMI status was a strong predictor of EGWG risk for women who were overweight/obese pre-pregnancy. Normal weight women with low motivation to maintain a healthy diet and who reported lower levels of partner support were also at considerable risk of EGWG. present findings offer support for inclusion of psychosocial measures (in addition to BMI) in early antenatal visits to detect risk of EGWG. However, these findings also underscore the need for further consideration of effect modifiers that place women at increased or decreased risk of EGWG. Proposed additional constructs are discussed to direct further theory-driven research. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

  2. Semi Supervised Weighted K-Means Clustering for Multi Class Data Classification

    Directory of Open Access Journals (Sweden)

    Vijaya Geeta Dharmavaram

    2013-01-01

    Full Text Available Supervised Learning techniques require large number of labeled examples to train a classifier model. Research on Semi Supervised Learning is motivated by the availability of unlabeled examples in abundance even in domains with limited number of labeled examples. In such domains semi supervised classifier uses the results of clustering for classifier development since clustering does not rely only on labeled examples as it groups the objects based on their similarities. In this paper, the authors propose a new algorithm for semi supervised classification namely Semi Supervised Weighted K-Means (SSWKM. In this algorithm, the authors suggest the usage of weighted Euclidean distance metric designed as per the purpose of clustering for estimating the proximity between a pair of points and used it for building semi supervised classifier. The authors propose a new approach for estimating the weights of features by appropriately adopting the results of multiple discriminant analysis. The proposed method was then tested on benchmark datasets from UCI repository with varied percentage of labeled examples and found to be consistent and promising.

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

    NARCIS (Netherlands)

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

    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 (RI). The objective of this study was to evaluate weight loss and nutrition

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

    Science.gov (United States)

    Smith, Taylor F; Anastopoulos, Arthur D; Garrett, Melanie E; Arias-Vasquez, Alejandro; Franke, Barbara; Oades, Robert D; Sonuga-Barke, Edmund; Asherson, Philip; Gill, Michael; Buitelaar, Jan K; Sergeant, Joseph A; Kollins, Scott H; Faraone, Stephen V; Ashley-Koch, Allison

    2014-12-01

    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 biological pathways moderate the relationship between birth weight and ADHD symptom severity. A total of 398 youth from two multi-site, family-based studies of ADHD were included in the analysis. The sample consisted of 360 ADHD probands, 21 affected siblings, and 17 unaffected siblings. A set of 164 SNPs from 31 candidate genes, representing five biological pathways, were included in our analyses. Birth weight and gestational age data were collected from a state birth registry, medical records, and parent report. Generalized Estimating Equations tested for main effects and interactions between individual SNPs and birth weight centile in predicting ADHD symptom severity. SNPs within neurotrophic (NTRK3) and cytokine genes (CNTFR) were associated with ADHD inattentive symptom severity. There was no main effect of birth weight centile on ADHD symptom severity. SNPs within angiogenic (NRP1 & NRP2), neurotrophic (NTRK1 & NTRK3), cytokine (IL16 & S100B), and kynurenine (CCBL1 & CCBL2) genes moderate the association between birth weight centile and ADHD symptom severity. The SNP main effects and SNP × birth weight centile interactions remained significant after adjusting for multiple testing. Genetic variability in angiogenic, neurotrophic, and inflammatory systems may moderate the association between restricted prenatal growth, a proxy for an adverse prenatal environment, and risk to develop ADHD.

  5. 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.

  6. 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.

  7. 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.

  8. Feature Selection Based on the SVM Weight Vector for Classification of Dementia.

    Science.gov (United States)

    Bron, Esther E; Smits, Marion; Niessen, Wiro J; Klein, Stefan

    2015-09-01

    Computer-aided diagnosis of dementia using a support vector machine (SVM) can be improved with feature selection. The relevance of individual features can be quantified from the SVM weights as a significance map (p-map). Although these p-maps previously showed clusters of relevant voxels in dementia-related brain regions, they have not yet been used for feature selection. Therefore, we introduce two novel feature selection methods based on p-maps using a direct approach (filter) and an iterative approach (wrapper). To evaluate these p-map feature selection methods, we compared them with methods based on the SVM weight vector directly, t-statistics, and expert knowledge. We used MRI data from the Alzheimer's disease neuroimaging initiative classifying Alzheimer's disease (AD) patients, mild cognitive impairment (MCI) patients who converted to AD (MCIc), MCI patients who did not convert to AD (MCInc), and cognitively normal controls (CN). Features for each voxel were derived from gray matter morphometry. Feature selection based on the SVM weights gave better results than t-statistics and expert knowledge. The p-map methods performed slightly better than those using the weight vector. The wrapper method scored better than the filter method. Recursive feature elimination based on the p-map improved most for AD-CN: the area under the receiver-operating-characteristic curve (AUC) significantly increased from 90.3% without feature selection to 92.0% when selecting 1.5%-3% of the features. This feature selection method also improved the other classifications: AD-MCI 0.1% improvement in AUC (not significant), MCI-CN 0.7%, and MCIc-MCInc 0.1% (not significant). Although the performance improvement due to feature selection was limited, the methods based on the p-map generally had the best performance, and were therefore better in estimating the relevance of individual features.

  9. Classification of Irreducible Weight Modules with a Finite-dimensional Weight Space over Twisted Heisenberg-Virasoro Algebra

    Institute of Scientific and Technical Information of China (English)

    Ran SHEN; Yu Cai SU

    2007-01-01

    We show that the support of an irreducible weight module over the twisted Heisenberg-Virasoro algebra, which has an infinite-dimensional weight space, coincides with the weight lattice and that all nontrivial weight spaces of such a module are infinite dimensional. As a corollary, we obtain that every irreducible weight module over the twisted Heisenberg-Virasoro algebra, having a nontrivial finite-dimensional weight space, is a Harish-Chandra module (and hence is either an irreducible highest or lowest weight module or an irreducible module from the intermediate series).

  10. Sex differences in severity of inflammation-induced anorexia and weight loss.

    Science.gov (United States)

    Lennie, Terry A

    2004-04-01

    Food intake and body weight changes in response to induction of acute inflammation were examined in intact cycling females, ovariectomized females, and sham-operated male rats. In intact females, body weight and feeding responses were compared between rats in which inflammation was induced on day of estrus with rats in which inflammation was induced on day of diestrus. Anorexia and weight loss were more severe in the female rats with inflammation induced on estrus day, which coincides with peak serum estrogen levels. In ovariectomized females, inflammation was induced the day after rats received injections of estrogen, progesterone, or sesame oil (vehicle). Males received vehicle injections. Among female rats, the group that received estradiol injections the previous day displayed the most severe anorexia. The least severe anorexia was observed in female rats that received progesterone the previous day. Food intake of female rats that received vehicle injections prior to induction of inflammation was greater than the rats receiving estrogen but less than the rats receiving progesterone. Male rats displayed the most severe anorexia and greatest weight loss. These data suggest that, although females exposed to estradiol prior to induction of acute inflammation display more severe anorexia than those exposed to progesterone, it may be that progesterone attenuates severity of anorexia rather than estrogen solely potentiating severity. Male rats, however, appear to experience the most severe anorexia in response to this form of inflammation.

  11. 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

  12. Systematic Classification of Disease Severity for Evaluation of Expanded Carrier Screening Panels.

    Directory of Open Access Journals (Sweden)

    Gabriel A Lazarin

    Full Text Available Professional guidelines dictate that disease severity is a key criterion for carrier screening. Expanded carrier screening, which tests for hundreds to thousands of mutations simultaneously, requires an objective, systematic means of describing a given disease's severity to build screening panels. We hypothesized that diseases with characteristics deemed to be of highest impact would likewise be rated as most severe, and diseases with characteristics of lower impact would be rated as less severe. We describe a pilot test of this hypothesis in which we surveyed 192 health care professionals to determine the impact of specific disease phenotypic characteristics on perceived severity, and asked the same group to rate the severity of selected inherited diseases. The results support the hypothesis: we identified four "Tiers" of disease characteristics (1-4. Based on these responses, we developed an algorithm that, based on the combination of characteristics normally seen in an affected individual, classifies the disease as Profound, Severe, Moderate, or Mild. This algorithm allows simple classification of disease severity that is replicable and not labor intensive.

  13. 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

  14. Benign-malignant mass classification in mammogram using edge weighted local texture features

    Science.gov (United States)

    Rabidas, Rinku; Midya, Abhishek; Sadhu, Anup; Chakraborty, Jayasree

    2016-03-01

    This paper introduces novel Discriminative Robust Local Binary Pattern (DRLBP) and Discriminative Robust Local Ternary Pattern (DRLTP) for the classification of mammographic masses as benign or malignant. Mass is one of the common, however, challenging evidence of breast cancer in mammography and diagnosis of masses is a difficult task. Since DRLBP and DRLTP overcome the drawbacks of Local Binary Pattern (LBP) and Local Ternary Pattern (LTP) by discriminating a brighter object against the dark background and vice-versa, in addition to the preservation of the edge information along with the texture information, several edge-preserving texture features are extracted, in this study, from DRLBP and DRLTP. Finally, a Fisher Linear Discriminant Analysis method is incorporated with discriminating features, selected by stepwise logistic regression method, for the classification of benign and malignant masses. The performance characteristics of DRLBP and DRLTP features are evaluated using a ten-fold cross-validation technique with 58 masses from the mini-MIAS database, and the best result is observed with DRLBP having an area under the receiver operating characteristic curve of 0.982.

  15. Automated Classification of Severity in Cardiac Dyssynchrony Merging Clinical Data and Mechanical Descriptors

    Science.gov (United States)

    Santos-Díaz, Alejandro; Valdés-Cristerna, Raquel; Vallejo, Enrique; Hernández, Salvador

    2017-01-01

    Cardiac resynchronization therapy (CRT) improves functional classification among patients with left ventricle malfunction and ventricular electric conduction disorders. However, a high percentage of subjects under CRT (20%–30%) do not show any improvement. Nonetheless the presence of mechanical contraction dyssynchrony in ventricles has been proposed as an indicator of CRT response. This work proposes an automated classification model of severity in ventricular contraction dyssynchrony. The model includes clinical data such as left ventricular ejection fraction (LVEF), QRS and P-R intervals, and the 3 most significant factors extracted from the factor analysis of dynamic structures applied to a set of equilibrium radionuclide angiography images representing the mechanical behavior of cardiac contraction. A control group of 33 normal volunteers (28 ± 5 years, LVEF of 59.7% ± 5.8%) and a HF group of 42 subjects (53.12 ± 15.05 years, LVEF < 35%) were studied. The proposed classifiers had hit rates of 90%, 50%, and 80% to distinguish between absent, mild, and moderate-severe interventricular dyssynchrony, respectively. For intraventricular dyssynchrony, hit rates of 100%, 50%, and 90% were observed distinguishing between absent, mild, and moderate-severe, respectively. These results seem promising in using this automated method for clinical follow-up of patients undergoing CRT.

  16. Family factors that characterize adolescents with severe obesity and their role in weight loss surgery outcomes.

    Science.gov (United States)

    Zeller, Meg H; Hunsaker, Sanita; Mikhail, Carmen; Reiter-Purtill, Jennifer; McCullough, Mary Beth; Garland, Beth; Austin, Heather; Washington, Gia; Baughcum, Amy; Rofey, Dana; Smith, Kevin

    2016-12-01

    To comprehensively assess family characteristics of adolescents with severe obesity and whether family factors impact weight loss outcomes following weight loss surgery (WLS). Multisite prospective data from 138 adolescents undergoing WLS and primary caregivers (adolescent: Mage  = 16.9; MBMI = 51.5 kg/m(2) ; caregiver: Mage  = 44.5; 93% female) and 83 nonsurgical comparators (NSComp: adolescent: Mage  = 16.1; MBMI = 46.9 kg/m(2) ; caregiver: Mage  = 43.9; 94% female) were collected using standardized measures at presurgery/baseline and at 1 and 2 years. The majority (77.3%) of caregivers had obesity, with rates of caregiver WLS significantly higher in the WLS (23.8%) versus NSComp group (3.7%, P Family dysfunction was prevalent (≈1 in every two to three families), with rates higher for NSComp than the WLS group. For the WLS group, preoperative family factors (i.e., caregiver BMI or WLS history, dysfunction, social support) were not significant predictors of adolescent weight loss at 1 and 2 years postoperatively, although change in family functioning over time emerged as a significant correlate of percent weight loss. Rates of severe obesity in caregivers as well as family dysfunction were clinically noteworthy, although not related to adolescent weight loss success following WLS. However, change in family communication and emotional climate over time emerged as potential targets to optimize weight loss outcomes. © 2016 The Obesity Society.

  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. A population survey in Italy based on the ICF classification: recognizing persons with severe disability.

    Science.gov (United States)

    Leonardi, Matilde; Martinuzzi, Andrea; Meucci, Paolo; Sala, Marina; Russo, Emanuela; Buffoni, Mara; Raggi, Alberto

    2012-01-01

    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.

  19. 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…

  20. Lifestyle interventions for weight loss in adults with severe obesity: a systematic review.

    Science.gov (United States)

    Hassan, Y; Head, V; Jacob, D; Bachmann, M O; Diu, S; Ford, J

    2016-12-01

    Severe obesity is an increasingly prevalent condition and is often associated with long-term comorbidities, reduced survival and higher healthcare costs. Non-surgical methods avoid the side effects, complications and costs of surgery, but it is unclear which non-surgical method is most effective. The objective of this article was to systematically review the effectiveness of lifestyle interventions compared to standard or minimal care for weight loss in adults with severe obesity. MEDLINE, EMBASE, CENTRAL, databases of on-going studies, reference lists of any relevant systematic reviews and the Cochrane Library database were searched from inception to February 2016 for relevant randomized controlled trials (RCTs). Inclusion criteria were participants with severe obesity (body mass index [BMI] > 40 kg/m(2) or BMI > 35 kg/m(2) with comorbidity) and interventions with a minimal duration of 12 weeks that were multi-component combinations of diet, exercise and behavioural therapy. Risk of bias was evaluated using the Cochrane risk of bias criteria. Meta-analysis was not possible because of methodological heterogeneity. Seventeen RCTs met the inclusion criteria. Weight change in kilograms of participants from baseline to follow-up was reported for 14 studies. Participants receiving the lifestyle intervention had a greater decrease in weight than participants in the control group for all studies (1.0-11.5 kg). Lifestyle interventions varied greatly between the studies. Overall lifestyle interventions with combined diet and exercise components achieved the greatest weight loss. Lifestyle interventions for weight loss in adults with severe obesity were found to result in increased weight loss when compared to minimal or standard care, especially those with combined diet and exercise components. © 2016 World Obesity Federation.

  1. 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...

  2. Complementary markers for the clinical severity classification of hereditary spherocytosis in unsplenectomized patients.

    Science.gov (United States)

    Rocha, Susana; Costa, Elísio; Rocha-Pereira, Petronila; Ferreira, Fátima; Cleto, Esmeralda; Barbot, José; Quintanilha, Alexandre; Belo, Luís; Santos-Silva, Alice

    2011-02-15

    Hereditary spherocytosis (HS) is usually classified as mild, moderate or severe using conventional features, namely, hemoglobin (Hb) concentration, reticulocyte count and bilirubin levels, which do not always contribute to an adequate clinical classification. The aim of our study was to establish the importance of some laboratory routine parameters, as markers of HS clinical outcome, by studying a control group (n=26) and unsplenectomized HS patients (n=82) presenting mild, moderate or severe HS. We performed a basic hematologic study and evaluated the reticulocyte count, bilirubin, erythropoietin (EPO) and soluble transferrin receptor (sTfR) levels; the osmotic fragility (OFT) and criohemolysis tests (CHT); the ratios Hb/MCHC (mean cell hemoglobin concentration), Hb/RDW (red cell distribution width) and MCHC/RDW, were calculated. Hb changed significantly in accordance with HS severity, but not reticulocytes or bilirubin. We found that MCHC, RDW, EPO, sTfR, OFT, CHT and the calculated ratios were significantly changed in patients, and, therefore, were valuable as complementary diagnostic tools for HS. Moreover, RDW, Hb/MCHC, Hb/RDW and MCHC/RDW changed significantly with worsening of HS; thus, they are also good markers for the clinical outcome of HS. In conclusion, we propose the use of these routine parameters as useful to complement the analysis of HS severity.

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

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Song, E-mail: songliu532909756@gmail.com [Department of Radiology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing 210008 (China); Guan, Wenxian, E-mail: wenxianguan123@126.com [Department of Gastrointestinal Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing 210008 (China); Wang, Hao, E-mail: wanghao20140525@126.com [Department of Gastrointestinal Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing 210008 (China); Pan, Liang, E-mail: panliang2014@126.com [Department of Radiology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing 210008 (China); Zhou, Zhuping, E-mail: zhupingzhou@126.com [Department of Radiology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing 210008 (China); Yu, Haiping, E-mail: haipingyu2012@126.com [Department of Radiology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing 210008 (China); Liu, Tian, E-mail: tianliu2014@126.com [Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA 30322 (United States); Yang, Xiaofeng, E-mail: xiaofengyang2014@126.com [Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA 30322 (United States); He, Jian, E-mail: hjxueren@126.com [Department of Radiology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing 210008 (China); Zhou, Zhengyang, E-mail: zyzhou@nju.edu.cn [Department of Radiology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing 210008 (China)

    2014-12-15

    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{sup 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

  4. MRI Based Preterm White Matter Injury Classification: The Importance of Sequential Imaging in Determining Severity of Injury.

    Directory of Open Access Journals (Sweden)

    Miriam Martinez-Biarge

    Full Text Available The evolution of non-hemorrhagic white matter injury (WMI based on sequential magnetic resonance imaging (MRI has not been well studied. Our aim was to describe sequential MRI findings in preterm infants with non-hemorrhagic WMI and to develop an MRI classification system for preterm WMI based on these findings.Eighty-two preterm infants (gestation ≤35 weeks were retrospectively included. WMI was diagnosed and classified based on sequential cranial ultrasound (cUS and confirmed on MRI.138 MRIs were obtained at three time-points: early (<2 weeks; n = 32, mid (2-6 weeks; n = 30 and term equivalent age (TEA; n = 76. 63 infants (77% had 2 MRIs during the neonatal period. WMI was non-cystic in 35 and cystic in 47 infants. In infants with cystic-WMI early MRI showed extensive restricted diffusion abnormalities, cysts were already present in 3 infants; mid MRI showed focal or extensive cysts, without acute diffusion changes. A significant reduction in the size and/or extent of the cysts was observed in 32% of the infants between early/mid and TEA MRI. In 4/9 infants previously seen focal cysts were no longer identified at TEA. All infants with cystic WMI showed ≥2 additional findings at TEA: significant reduction in WM volume, mild-moderate irregular ventriculomegaly, several areas of increased signal intensity on T1-weighted-images, abnormal myelination of the PLIC, small thalami.In infants with extensive WM cysts at 2-6 weeks, cysts may be reduced in number or may even no longer be seen at TEA. A single MRI at TEA, without taking sequential cUS data and pre-TEA MRI findings into account, may underestimate the extent of WMI; based on these results we propose a new MRI classification for preterm non-hemorrhagic WMI.

  5. Weight reduction after severe brain injury: a challenge during the rehabilitation course.

    Science.gov (United States)

    Aadal, Lena; Mortensen, Jesper; Nielsen, Jørgen Feldbæk

    2015-04-01

    There is a paucity of studies, which have described malnutrition in patients with acquired brain injury (ABI) across etiology. This study describes weight change, malnutrition, and potential associations in patients with ABI at a subacute inpatient rehabilitation hospital. This is a descriptive cohort study. Ninety-eight patients were admitted in a 3-month period, of whom n = 76 met inclusion criteria. The Malnutrition Universal Screening Tool was used for categorizing patients according to risk of malnutrition. Patients had experienced weight loss of 5.59% ± 5.89% (p brain injury had experienced a greater weight loss than patients with stroke (p malnutrition, and 52% of these patients received enteral or parenteral nutrition at admission at the rehabilitation hospital. No association was found between risk of malnutrition and severity of injury, complications, functional outcome, or length of stay. RESULTS underline the importance that nurses, especially in acute care, adhere to clinical guidelines to minimize weight loss. Special attention should be on patients with traumatic brain injury. Weight gain in the following course of rehabilitation may facilitate positive rehabilitation outcomes.

  6. [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

  7. 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.

  8. Occurrence Classifications, Severity Weighting, and Normalization for the DOE Packaging and Transportation Safety Metrics Indicator Program

    Energy Technology Data Exchange (ETDEWEB)

    Dickerson, L.S.; Pope, R.B.; Michelhaugh, R.D.; Harrison, I.G.; Hermann, B.; Lester, P.B.

    1999-06-01

    The US Department of Energy (DOE) Occurrence Reporting and Processing System (ORPS) is an interactive computer system designed to support DOE-owned or -operated facilities in reporting and processing information concerning occurrences related to facility operations. The Oak Ridge National Laboratory has been charged by the DOE National Transportation Program Albuquerque (NTPA) with the responsibility of retrieving reports and information pertaining to packaging and transportation (P and T) incidents from the centralized ORPS database. These selected reports are analyzed for trends, impact on P and T operations and safety concerns, and ''lessons learned'' in P and T safety.

  9. The Influence of Body Weight on the Prevalence and Severity of Hidradenitis Suppurativa

    DEFF Research Database (Denmark)

    Kromann, Charles B; Ibler, Kristina S; Kristiansen, Viggo B

    2014-01-01

    The prevalence of hidradenitis suppurativa (HS) has been estimated to be 1% of the population. Obesity is considered a co-morbidity, but the prevalence of HS in obese population is not known. A retrospective questionnaire was distributed to 383 patients over 2 years after bariatric surgery. Data...... on pre- and post-surgery HS symptoms and disease severity were studied. Disease severity was assessed by number of involved sites. General skin problems rated numerically on an anchored 1-10 scale. Valid responses were obtained from 249/383 (65%). A point prevalence of 18.1% (45/249) HS was found....... The number of patients reporting HS symptoms after weight loss decreased by 35% and the mean number of involved sites was reduced from 1.93 to 1.22 following weight loss (p = 0.003). The prevalence of HS appears higher in the obese than in the background population, and a weight loss of more than 15...

  10. Severe weight gain and generalized insulin edema after the starting of an insulin pump.

    Science.gov (United States)

    Greco, Domenico

    2015-02-01

    The possibility of the occurrence of a generalized edema after initiation or intensification of insulin treatment in patients with diabetes, although considered a rare event, has long been described in the literature. In this case, a state of clinically significant edema, with a concurrent severe weight gain, occurred in a patient with type 1 diabetes in whom the implantation of an insulin pump resulted in a dramatic and abrupt improvement in glycemic control. Copyright © 2015 Canadian Diabetes Association. Published by Elsevier Inc. All rights reserved.

  11. Comparison and validation of tissue modelization and statistical classification methods in T1-weighted MR brain images.

    Science.gov (United States)

    Cuadra, Meritxell Bach; Cammoun, Leila; Butz, Torsten; Cuisenaire, Olivier; Thiran, Jean-Philippe

    2005-12-01

    This paper presents a validation study on statistical nonsupervised brain tissue classification techniques in magnetic resonance (MR) images. Several image models assuming different hypotheses regarding the intensity distribution model, the spatial model and the number of classes are assessed. The methods are tested on simulated data for which the classification ground truth is known. Different noise and intensity nonuniformities are added to simulate real imaging conditions. No enhancement of the image quality is considered either before or during the classification process. This way, the accuracy of the methods and their robustness against image artifacts are tested. Classification is also performed on real data where a quantitative validation compares the methods' results with an estimated ground truth from manual segmentations by experts. Validity of the various classification methods in the labeling of the image as well as in the tissue volume is estimated with different local and global measures. Results demonstrate that methods relying on both intensity and spatial information are more robust to noise and field inhomogeneities. We also demonstrate that partial volume is not perfectly modeled, even though methods that account for mixture classes outperform methods that only consider pure Gaussian classes. Finally, we show that simulated data results can also be extended to real data.

  12. Finite Projective Geometries and Classification of the Weight Hierarchies of Codes (I)

    Institute of Scientific and Technical Information of China (English)

    Wen De CHEN; Torleiv KLфVE

    2004-01-01

    The weight hierarchy of a binary linear [n, k] code C is the sequence (d1, d2,……, dk), where dr is the smallest support of an r-dimensional subcode of C. The codes of dimension 4 are collected in classes and the possible weight hierarchies in each class is determined by finite projective geometries.The possible weight hierarchies in class A, B, C, D are determined in Part (Ⅰ). The possible weight hierarchies in class E, F, G, H, I are determined in Part (Ⅱ).

  13. Coagulation abnormalities and severe intraventricular hemorrhage in extremely low birth weight infants.

    Science.gov (United States)

    Piotrowski, Andrzej; Dabrowska-Wojciak, Iwona; Mikinka, Marek; Fendler, Wojciech; Walas, Wojciech; Sobala, Wojciech; Kuczkowski, Krzysztof Marek

    2010-07-01

    The association between intraventricular hemorrhage (IVH) and coagulation in infants has been a subject of controversy. Only few publications assessing risk factors for development of IVH reported results of coagulation studies. To evaluate the levels of coagulation and fibrinolysis systems in ELBW infants and determine their influence on IVH. Following IRB approval coagulation status of 38 ELBW infants was evaluated on first and second day of life. Severity of IVH assessed by cerebral ultrasonography was graded according to Papile classification. Newborns were assigned to either Group A--Grade III or IV, or Group B--Grade I-II, or no IVH. Neonates with Grade III/IV IVH had significantly lower plasma Factor VII (FVII) level on first day of life and FVII differed significantly between Groups A and B with sensitivity of 100%, specificity 41% for a cut-off value of< 7%. In Group A there was no improvement of prothrombin and activated partial thromboplastin times on Day 2. A significant decline of platelet count was also observed. High-grade IVH coincides with severe derangement of coagulation in ELBW infants with FVII level being the most sensitive, it is not clear what the reason for such low FVII concentration is. Further studies are indicated.

  14. Which is the most accurate formula to estimate fetal weight in women with severe preterm preeclampsia?

    Science.gov (United States)

    Geerts, Lut; Widmer, Tania

    2011-02-01

    To identify the most accurate formula to estimate fetal weight (EFW) from ultrasound parameters in severe preterm preeclampsia. In a prospective study, serial ultrasound assessments were performed in 123 women with severe preterm preeclampsia. The EFW, calculated for 111 live born, normal, singleton fetuses within 7 days of delivery using 38 published formulae, was compared to the actual birth weight (ABW). Accuracy was assessed by correlations, mean (absolute and signed) (%) errors, % correct predictions within 5-20% of ABW and limits of agreement. Accuracy was highly variable. Most formulae systematically overestimated ABW. Five Hadlock formulae utilizing three or four variables and Woo 3 formula had the highest accuracy and did not differ significantly (mean absolute % errors 6.8-7.2%, SDs 5.3-5.8%, > 75% of estimations within 10% of ABW and 95% limits of agreement between -18/20% and +14/15%). They were not negatively affected by clinical variables but had some inconsistency in bias over the ABW range. All other formulae, including those targeted for small, preterm or growth restricted fetuses, were inferior and/or affected by multiple clinical variables. In this GA window, Hadlock formulae using three or four variables or Woo 3 formula can be recommended.

  15. Weight-Based Classification of Raters and Rater Cognition in an EFL Speaking Test

    Science.gov (United States)

    Cai, Hongwen

    2015-01-01

    This study is an attempt to classify raters according to their weighting patterns and explore systematic differences between rater types in the rating process. In the context of an EFL speaking test, 126 raters were classified into three types--form-oriented, balanced, and content-oriented--through cluster analyses of their weighting patterns…

  16. Establishing the Injury Severity of Thoracolumbar Trauma : Confirmation of the Hierarchical Structure of the AOSpine Thoracolumbar Spine Injury Classification System

    NARCIS (Netherlands)

    Schroeder, Gregory D.; Vaccaro, Alexander R.; Kepler, Christopher K.; Koerner, John D.; Oner, F. Cumhur; Dvorak, Marcel F.; Vialle, Luiz R.; Aarabi, Bizhan; Bellabarba, Carlo; Fehlings, Michael G.; Schnake, Klaus J.; Kandziora, Frank

    2015-01-01

    Study Design. Survey of spine surgeons. Objective. To develop a validated regional and global injury severity scoring system for thoracolumbar trauma. Summary of Background Data. The AOSpine Thoracolumbar Spine Injury Classification System was recently published and combines elements of both the Mag

  17. Evaluation of the WHO classification of dengue disease severity during an epidemic in 2011 in the state of Ceara, Brazil

    Directory of Open Access Journals (Sweden)

    Luciano Pamplona de Goes Cavalcanti

    2014-02-01

    Full Text Available In 2009, the World Health Organization (WHO issued a new guideline that stratifies dengue-affected patients into severe (SD and non-severe dengue (NSD (with or without warning signs. To evaluate the new recommendations, we completed a retrospective cross-sectional study of the dengue haemorrhagic fever (DHF cases reported during an outbreak in 2011 in northeastern Brazil. We investigated 84 suspected DHF patients, including 45 (53.6% males and 39 (46.4% females. The ages of the patients ranged from five-83 years and the median age was 29. According to the DHF/dengue shock syndrome classification, 53 (63.1% patients were classified as having dengue fever and 31 (36.9% as having DHF. According to the 2009 WHO classification, 32 (38.1% patients were grouped as having NSD [4 (4.8% without warning signs and 28 (33.3% with warning signs] and 52 (61.9% as having SD. A better performance of the revised classification in the detection of severe clinical manifestations allows for an improved detection of patients with SD and may reduce deaths. The revised classification will not only facilitate effective screening and patient management, but will also enable the collection of standardised surveillance data for future epidemiological and clinical studies.

  18. [Utility of diffusion-weighted magnetic resonance imaging in severe focal traumatic brain injuries].

    Science.gov (United States)

    Prieto-Valderrey, F; Muñiz-Montes, J R; López-García, J A; Villegas-Del Ojo, J; Málaga-Gil, J; Galván-García, R

    2013-01-01

    To describe the apparent diffusion coefficient (ADC) in a series of severe traumatic brain injuries, their clinical and outcome features, and possible implications. A descriptive, observational case-series study was carried out. Patients with severe traumatic brain injuries (TBIs) admitted to the ICU were subjected to MRI study using a 1.5 T scanner. Diffusion-weighted images (DWMR) were obtained using the following echo-planar pulse sequence: TR 10000 ms, TE 126.9 ms, with b values 1000 s/mm2 in the three spatial dimensions. Combining the three sets of images, an isotropic image conforming a map of the mean ADCs was obtained. DWMR was performed in 23 patients with severe TBI admitted to the ICU between 2001 and 2004. In the MR images we selected 26 regions of interest (ROIs) where ADC was recorded. We observed a clear increase in diffusion in non-treated space-occupying lesions versus other types of injuries and the normal values. A poorer outcome was recorded in patients with lower ADC values. Mean ADC in the lesions was greater than the normal values and greater in contusions than in other types of injuries, as an expression of extracellular edema. ADCs were decreased in patients with a poor outcome, suggesting an association between ischemia and the patient prognosis. Copyright © 2011 Elsevier España, S.L. and SEMICYUC. All rights reserved.

  19. 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.

  20. Severe chronic diarrhea and weight loss in cholesteryl ester storage disease: A case report

    Institute of Scientific and Technical Information of China (English)

    Uta Drebber; Matthias Andersen; Hans U Kasper; Peter Lohse; Manfred Stolte; Hans P Dienes

    2005-01-01

    AIM: An inherited deficiency of human lysosomal acid lipase (LAL)results in the rare conditions of Wolman disease and cholesteryl ester storage disease (CESD). We want to present the rare case of CESD in an adult.METHODS: We report about an adult female patient with severe chronic diarrhea and weight loss as a consequence of CESD. Clinical examination revealed signs of malabsorption and slightly elevated liver enzymes.RESULTS: Histopathologic changes in the liver tissue and DNA sequence analysis confirmed the diagnosis of CESD due to homozygosity for the most common CESD mutation,a G934A splice site defect encoded by exon 8 of the lysosomal acid lipase (LIPA) gene.CONCLUSION: It is the first case in the literature with diarrhea as a putative symptom of CESD in adult patients.

  1. Can Statistical Machine Learning Algorithms Help for Classification of Obstructive Sleep Apnea Severity to Optimal Utilization of Polysomnography Resources?

    Science.gov (United States)

    Bozkurt, Selen; Bostanci, Asli; Turhan, Murat

    2017-08-11

    The goal of this study is to evaluate the results of machine learning methods for the classification of OSA severity of patients with suspected sleep disorder breathing as normal, mild, moderate and severe based on non-polysomnographic variables: 1) clinical data, 2) symptoms and 3) physical examination. In order to produce classification models for OSA severity, five different machine learning methods (Bayesian network, Decision Tree, Random Forest, Neural Networks and Logistic Regression) were trained while relevant variables and their relationships were derived empirically from observed data. Each model was trained and evaluated using 10-fold cross-validation and to evaluate classification performances of all methods, true positive rate (TPR), false positive rate (FPR), Positive Predictive Value (PPV), F measure and Area Under Receiver Operating Characteristics curve (ROC-AUC) were used. Results of 10-fold cross validated tests with different variable settings promisingly indicated that the OSA severity of suspected OSA patients can be classified, using non-polysomnographic features, with 0.71 true positive rate as the highest and, 0.15 false positive rate as the lowest, respectively. Moreover, the test results of different variables settings revealed that the accuracy of the classification models was significantly improved when physical examination variables were added to the model. Study results showed that machine learning methods can be used to estimate the probabilities of no, mild, moderate, and severe obstructive sleep apnea and such approaches may improve accurate initial OSA screening and help referring only the suspected moderate or severe OSA patients to sleep laboratories for the expensive tests.

  2. Classification

    Data.gov (United States)

    National Aeronautics and Space Administration — A supervised learning task involves constructing a mapping from an input data space (normally described by several features) to an output space. A set of training...

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

    Directory of Open Access Journals (Sweden)

    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.

  4. Adaptive classification of temporal signals in fixed-weights recurrent neural networks: an existence proof

    CERN Document Server

    Tyukin, Ivan; van Leeuwen, Cees

    2007-01-01

    We address the important theoretical question why a recurrent neural network with fixed weights can adaptively classify time-varied signals in the presence of additive noise and parametric perturbations. We provide a mathematical proof assuming that unknown parameters are allowed to enter the signal nonlinearly and the noise amplitude is sufficiently small.

  5. Diffusion-weighted MRI in cyclosporin A neurotoxicity for the classification of cerebral edema

    Energy Technology Data Exchange (ETDEWEB)

    Debaere, C.; Stadnik, T.; Maeseneer, M. de; Osteaux, M. [Dept. of Radiology, Academic Hospital, Vrije Universiteit Brussel (Belgium)

    1999-07-01

    Cyclosporin A, an immunosuppressive agent, is known to have neurotoxic effects, but until now, there has not been agreement on the underlying mechanism. Our report suggests, by using diffusion-weighted MRI, that the brain lesions caused by cyclosporin A, are probably related to vasogenic edema. This may explain the complete recovery of the lesions on imaging when cyclosporine therapy is stopped. (orig.)

  6. Pre- and post- prandial appetite hormone levels in normal weight and severely obese women

    Directory of Open Access Journals (Sweden)

    Wiebke Gail

    2009-08-01

    Full Text Available Abstract Background Appetite is affected by many factors including the hormones leptin, ghrelin and adiponectin. Ghrelin stimulates hunger, leptin promotes satiety, and adiponectin affects insulin response. This study was designed to test whether the pre- and postprandial response of key appetite hormones differs in normal weight (NW and severely obese (SO women. Methods Twenty three women ages 25–50 were recruited for this study including 10 NW (BMI = 23.1 ± 1.3 kg/m2 and 13 SO (BMI = 44.5 ± 7.1 kg/m2. The study was conducted in a hospital-based clinical research centre. Following a 12-hour fast, participants had a baseline blood draw, consumed a moderately high carbohydrate meal (60% carbohydrate, 20% protein, 20% fat based on body weight. Postprandially, participants had six blood samples drawn at 0, 15, 30, 60, 90, and 120 minutes. Primary measures included pre- and post-prandial total ghrelin, leptin, adiponectin and insulin. A repeated measures general linear model was used to evaluate the hormone changes by group and time (significance p ≤ 0.05. Results There were significant differences between the NW and the SO for all hormones in the preprandial fasting state. The postprandial responses between the SO versus NW revealed: higher leptin (p Conclusion This study indicates that significant differences in both pre- and selected post- prandial levels of leptin, ghrelin, adiponectin and insulin exist between NW and SO women. Improving our understanding of the biochemical mechanisms accounting for these differences in appetite hormones among individuals with varying body size and adiposity should aid in the development of future therapies to prevent and treat obesity.

  7. OFW-ITS-LSSVM: Weighted Classification by LS-SVM for Diabetes diagnosis

    Directory of Open Access Journals (Sweden)

    Fawzi Elias Bekri

    2012-03-01

    Full Text Available In accordance to the fast developing technology now a days, every field is gaining it’s benefit through machines other than human involvement. Many changes are being made much advancement is possible by this developing technology. Likewise this technology is too gaining its importance in bioinformatics especially to analyse data. As we all know that diabetes is one of the present day deadly diseases prevailing. So in this paper we introduce LS-SVM classification to understand which datasets of blood may have the chance to get diabetes. Further, considering the patient’s details we can predict where he has a chance to get diabetes, if so measures to cure or stop it. In this method, an optimal Tabu search model will be suggested to reduce the chances of getting it in the future

  8. Personal weight status classification and health literacy among Supplemental Nutrition Assistance Program (SNAP) participants.

    Science.gov (United States)

    Song, Hee-Jung; Grutzmacher, Stephanie K; Kostenko, Jane

    2014-06-01

    The purpose of this study was to examine the conceptual gap between self-perceived weight and body mass index (BMI), and to assess the knowledge gap between perceived importance of following dietary guidelines and health literacy levels. Adults (n = 131) eligible for the Supplemental Nutrition Assistance Program (SNAP) were interviewed at eleven SNAP regional offices in Maryland. Based on BMI calculated from self-reported height and weight, 65.6% of participants were overweight or obese while 40.5% perceived that they were overweight or obese. In sub-group analysis categorized by BMI, only 20.0% in the overweight and 20.0% in the obese group correctly perceived themselves as being overweight or obese. Following dietary guidelines was perceived as important by a majority of participants, but only 43.5% had adequate health literacy. Conceptual and knowledge gaps between self-perception and objective health status existed in the low-income SNAP-eligible sample. Future studies need to address these gaps because misperceived weight status and insufficient health literacy are critical barriers to inducing behavioral change.

  9. Dialectical multispectral classification of diffusion-weighted magnetic resonance images as an alternative to apparent diffusion coefficients maps to perform anatomical analysis.

    Science.gov (United States)

    Santos, W P; Assis, F M; Souza, R E; Santos Filho, P B; Lima Neto, F B

    2009-09-01

    Multispectral image analysis is a relatively promising field of research with applications in several areas, such as medical imaging and satellite monitoring. A considerable number of current methods of analysis are based on parametric statistics. Alternatively, some methods in computational intelligence are inspired by biology and other sciences. Here we claim that philosophy can be also considered as a source of inspiration. This work proposes the objective dialectical method (ODM): a method for classification based on the philosophy of praxis. ODM is instrumental in assembling evolvable mathematical tools to analyze multispectral images. In the case study described in this paper, multispectral images are composed of diffusion-weighted (DW) magnetic resonance (MR) images. The results are compared to ground-truth images produced by polynomial networks using a morphological similarity index. The classification results are used to improve the usual analysis of the apparent diffusion coefficient map. Such results proved that gray and white matter can be distinguished in DW-MR multispectral analysis and, consequently, DW-MR images can also be used to furnish anatomical information.

  10. Bone metabolism in obesity: changes related to severe overweight and dietary weight reduction

    DEFF Research Database (Denmark)

    Hyldstrup, Lars; Andersen, T; McNair, P;

    1993-01-01

    A non-invasive evaluation of bone metabolism was performed in 44 morbidly obese patients before and after a mean weight loss of 22.4 kg (range 7.9-43.4 kg) after 2 months and a further weight loss of 7.3 kg after 8 months (0.8-20.0 kg). This weight reduction was obtained by a nutritionally adequa...

  11. 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).

  12. 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 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.

  13. 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

    2014-01-01

    Objectives 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. Study design Baseline (pre-operative) data from Teen-LABS, a prospective multicenter observational study of 242 adolescents with severe obesity (MdnBMI = 50.5 kg/m2; Mage=17.1; 75.6% female; 71.9% White) undergoing WLS, were utilized 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; IWQOL-Kids). Results 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%). Males had a higher CLoad (p=.01) and BMI (p=.01), yet less impairment in total WRQOL (pstress urinary incontinence) also emerged as contributors to lower WRQOL. Conclusions 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 prior to WLS. Further, they provide a comprehensive empirical base for understanding heterogeneity in adolescent WRQOL outcomes following WLS, as weight and comorbidity profiles change over time. PMID:25556022

  14. 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)

  15. Bone metabolism in obesity: changes related to severe overweight and dietary weight reduction

    DEFF Research Database (Denmark)

    Hyldstrup, Lars; Andersen, T; McNair, P

    1993-01-01

    A non-invasive evaluation of bone metabolism was performed in 44 morbidly obese patients before and after a mean weight loss of 22.4 kg (range 7.9-43.4 kg) after 2 months and a further weight loss of 7.3 kg after 8 months (0.8-20.0 kg). This weight reduction was obtained by a nutritionally adequate...... obese patients (19.2 molar ratio x 10(-3) vs 16.7 molar ratio x 10(-3), NS). After 2 months...

  16. Actual versus ideal body weight for acute kidney injury diagnosis and classification in critically ill patients.

    Science.gov (United States)

    Thongprayoon, Charat; Cheungpasitporn, Wisit; Akhoundi, Abbasali; Ahmed, Adil H; Kashani, Kianoush B

    2014-11-15

    In the current acute kidney injury (AKI) definition, the urine output (UO) criterion does not specify which body weights (BW), i.e. actual (ABW) versus ideal (IBW), should be used to diagnose and stage AKI, leading to heterogeneity across research studies. This is a single center, retrospective, observational study conducted at a tertiary referral hospital. All adult patients who were admitted to intensive care units (ICUs) at our institution for a minimum of 6 continuous hours between January and March 2010 and had a urinary catheter for hourly urine output monitoring were eligible for this study. Patients' AKI stages, based on UO criterion, were assessed by calculating each milliliter of urine per kilogram per hour, using ABW versus IBW. A total of 493 ICU patients were included in the analysis. The median ABW and IBW were 82 (IQR 68-96) and 70 (IQR 60-77) kg, respectively. Using the IBW criterion, 154 patients (31.2%) were diagnosed with AKI, while 204 (41.4%) were diagnosed using the ABW measurement (P-valueABW but not IBW had no significant increase in the risk of 90-day mortality, adjusted OR 0.76; (95% CI 0.25-1.91), compared to patients who had no AKI. Using ABW to diagnose and stage AKI by UO criterion is more sensitive and less specific than IBW. Based on the application of the definition, different BW types could be utilized.

  17. 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.

  18. How should severity be determined for the DSM-5 proposed classification of Hypersexual Disorder?

    Science.gov (United States)

    Reid, Rory C.

    2015-01-01

    Background and Aims The concept of severity among providers working with hypersexual behavior is frequently used despite a lack of consensus about how severity should be operationalized. The paucity of dialogue about severity for hypersexual behavior is disconcerting given its relevance in determining level of care, risk, allocation of resources, and measuring treatment outcomes in clinical practice and research trials. The aim of the current article is to highlight several considerations for assessing severity based on the proposed DSM-5 criteria for hypersexual disorder. Methods A review of current conceptualizations for severity among substance-use disorders and gambling disorder in the DSM-5 were considered and challenged as lacking applicability or clinical utility for hypersexual behavior. Results and conclusions The current research in the field of hypersexual behavior is in its infancy. No concrete approach currently exists to assess severity in hypersexual populations. Several factors in operationalizing severity are discussed and alternative approaches to defining severity are offered for readers to consider. PMID:26690616

  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. Excess weight in preschool children with a history of severe bronchiolitis is associated with asthma.

    Science.gov (United States)

    Törmänen, Sari; Lauhkonen, Eero; Saari, Antti; Koponen, Petri; Korppi, Matti; Nuolivirta, Kirsi

    2015-05-01

    The relationship between excess weight gain and asthma in childhood remains inadequately defined. The aim of this study was to evaluate, as part of a prospective post-bronchiolitis follow-up, whether there is a link between earlier or current overweight or obesity and asthma or asthma symptoms at 5-7 years of age. In all, 151 former bronchiolitis patients were followed-up until the mean age of 6.45 years. At the control visit, the weights and heights were measured, and the asthma symptoms and medications for asthma were recorded. The weight status was expressed as body mass index (BMI) z-scores (zBMI). There were 10 obese and 31 overweight (zBMI over national references) children. In adjusted analyses, presence of current asthma at 6-7 years of age (aOR 3.05, 95% CI 1.02-9.93) differed between overweight and normal weight children. Further, asthma ever, asthma at age 4-5 years, asthma at age 5-6 years, use of bronchodilators ever and use of ICSs during the last 12 months were more common in currently overweight than in normal weight children. Obesity was associated only with current asthma and asthma ever. Instead, there were no significant associations between birth weight, excess weight gain in infancy, or overweight at age 1.5 years, and later asthma, asthma symptoms or use of asthma medication. Asthma was more common in currently overweight than in normal weight former bronchiolitis patients at preschool age and early school age. © 2014 Wiley Periodicals, Inc.

  1. Automatic classification of apnea/hypopnea events through sleep/wake states and severity of SDB from a pulse oximeter.

    Science.gov (United States)

    Park, Jong-Uk; Lee, Hyo-Ki; Lee, Junghun; Urtnasan, Erdenebayar; Kim, Hojoong; Lee, Kyoung-Joung

    2015-09-01

    This study proposes a method of automatically classifying sleep apnea/hypopnea events based on sleep states and the severity of sleep-disordered breathing (SDB) using photoplethysmogram (PPG) and oxygen saturation (SpO2) signals acquired from a pulse oximeter. The PPG was used to classify sleep state, while the severity of SDB was estimated by detecting events of SpO2 oxygen desaturation. Furthermore, we classified sleep apnea/hypopnea events by applying different categorisations according to the severity of SDB based on a support vector machine. The classification results showed sensitivity performances and positivity predictive values of 74.2% and 87.5% for apnea, 87.5% and 63.4% for hypopnea, and 92.4% and 92.8% for apnea + hypopnea, respectively. These results represent better or comparable outcomes compared to those of previous studies. In addition, our classification method reliably detected sleep apnea/hypopnea events in all patient groups without bias in particular patient groups when our algorithm was applied to a variety of patient groups. Therefore, this method has the potential to diagnose SDB more reliably and conveniently using a pulse oximeter.

  2. Prediction of Severe Acute Pancreatitis Using a Decision Tree Model Based on the Revised Atlanta Classification of Acute Pancreatitis.

    Directory of Open Access Journals (Sweden)

    Zhiyong Yang

    Full Text Available To develop a model for the early prediction of severe acute pancreatitis based on the revised Atlanta classification of acute pancreatitis.Clinical data of 1308 patients with acute pancreatitis (AP were included in the retrospective study. A total of 603 patients who were admitted to the hospital within 36 hours of the onset of the disease were included at last according to the inclusion criteria. The clinical data were collected within 12 hours after admission. All the patients were classified as having mild acute pancreatitis (MAP, moderately severe acute pancreatitis (MSAP and severe acute pancreatitis (SAP based on the revised Atlanta classification of acute pancreatitis. All the 603 patients were randomly divided into training group (402 cases and test group (201 cases. Univariate and multiple regression analyses were used to identify the independent risk factors for the development of SAP in the training group. Then the prediction model was constructed using the decision tree method, and this model was applied to the test group to evaluate its validity.The decision tree model was developed using creatinine, lactate dehydrogenase, and oxygenation index to predict SAP. The diagnostic sensitivity and specificity of SAP in the training group were 80.9% and 90.0%, respectively, and the sensitivity and specificity in the test group were 88.6% and 90.4%, respectively.The decision tree model based on creatinine, lactate dehydrogenase, and oxygenation index is more likely to predict the occurrence of SAP.

  3. Relationship between clinical factors and severity of esophageal candidiasis according to Kodsi's classification.

    Science.gov (United States)

    Asayama, N; Nagata, N; Shimbo, T; Nishimura, S; Igari, T; Akiyama, J; Ohmagari, N; Hamada, Y; Nishijima, T; Yazaki, H; Teruya, K; Oka, S; Uemura, N

    2014-04-01

    Severe Candida esophagitis (CE) may lead to development of strictures, hemorrhage, esophagotracheal fistula, and a consequent decrease in quality of life. Although the severity of CE has been classified based on macroscopic findings on endoscopy, the clinical significance remains unknown. The aim of the study was to elucidate the predictive clinical factors for endoscopic severity of CE. Patients who underwent upper endoscopy and answered questionnaires were prospectively enrolled. Smoking, alcohol, human immunodeficiency virus (HIV) infection, diabetes mellitus, chronic renal failure, liver cirrhosis, systemic steroids use, proton pump inhibitor use, H2 blocker use, and gastrointestinal (GI) symptoms were assessed on the same day of endoscopy. GI symptoms including epigastric pain, heartburn, reflux, hunger cramps, nausea, dysphagia, and odynophagia were assessed on a 7-point Likert scale. Endoscopic severity was classified as mild (Kodsi's grade I/II) or severe (grade III/IV). Of 1855 patients, 71 (3.8%) were diagnosed with CE (mild, n = 48; severe, n = 23). In the CE patients, 50.0% (24/48) in the mild group and 23.1% (6/23) in the severe group did not have any GI symptoms. In HIV-infected patients (n = 17), a significant correlation was found between endoscopic severity and declining CD4 cell count (Spearman's rho = -0.90; P < 0.01). Multivariate analysis revealed that GI symptoms (odds ratio [OR], 3.32) and HIV infection (OR, 3.81) were independently associated with severe CE. Patients in the severe group experienced more epigastric pain (P = 0.02), reflux symptoms (P = 0.04), dysphagia (P = 0.05), and odynophagia (P < 0.01) than those in the mild group. Of the GI symptoms, odynophagia was independently associated with severe CE (OR 9.62, P = 0.02). In conclusion, the prevalence of CE in adults who underwent endoscopy was 3.8%. Silent CE was found in both mild and severe cases. Endoscopic severity was associated with

  4. [Low doses of megestrol acetate increase weight and improve nutrition status in patients with severe chronic obstructive pulmonary disease and weight loss].

    Science.gov (United States)

    Herrejón, Alberto; Palop, Julio; Inchaurraga, Ignacio; López, Antonio; Bañuls, Celia; Hernández, Antonio; Blanquer, Rafael; Están, Nuria; Anguera, Anna

    2011-07-23

    Weight loss in patients with severe chronic obstructive pulmonary disease (COPD) is a prognostic bad factor. The objective of this study is to analyze the effectively of megestrol acetate (MA) to increase appetite of these patients. Randomized double blind placebo controlled trial to study the effect of 160 mg/bid of MA, for 8 weeks, on nutritional, functional, analytical and quality of life parameters, in 38 patients with severe COPD and body mass index (BMI) nutritional parameters and the sense of wellbeing, but it does not improve the respiratory muscular function or exercise tolerance. Copyright © 2010 Elsevier España, S.L. All rights reserved.

  5. Bone metabolism in obesity: changes related to severe overweight and dietary weight reduction

    DEFF Research Database (Denmark)

    Hyldstrup, Lars; Andersen, T; McNair, P

    1993-01-01

    A non-invasive evaluation of bone metabolism was performed in 44 morbidly obese patients before and after a mean weight loss of 22.4 kg (range 7.9-43.4 kg) after 2 months and a further weight loss of 7.3 kg after 8 months (0.8-20.0 kg). This weight reduction was obtained by a nutritionally adequate...... After 2 months......, the bone mineral content had declined by 3.3%. Serum alkaline phosphatase remained unchanged (187.8 U/l vs 186.9 U/l, NS) but serum osteocalcin demonstrated a significant rise (3.94 nmol/l vs 10.53 nmol/l, p changes in the hydroxyproline/creatinine ratio (19.2 molar ratio x 10(-3) vs...

  6. The effects of weight loss surgery on blood rheology in severely obese patients.

    Science.gov (United States)

    Wiewiora, Maciej; Piecuch, Jerzy; Glűck, Marek; Slowinska-Lozynska, Ludmila; Sosada, Krystyn

    2015-01-01

    The effects of dieting on blood rheology in obese individuals suggest that improving the rheologic profiles depends on the amount of weight lost and its long-term maintenance. The aim of this study was to evaluate the effects of weight loss after surgery on blood rheology at 12-month follow-up. We studied 38 obese patients who underwent laparoscopic weight loss surgery, 22 of whom had sleeve gastrectomy (SG) and 16 of whom had gastric banding (LAGB). We evaluated rheologic parameters such as blood viscosity, plasma viscosity, and erythrocyte deformability (as measured by elongation index [EI]) preoperatively and 12 months after surgery. Whole blood viscosity at 150 s(-1) shear rate (Prheology in obese patients at 12 months after surgery. The increased red blood cell rigidity after surgery requires further study because the physiologic importance of this change has not yet been established. Copyright © 2015 American Society for Bariatric Surgery. Published by Elsevier Inc. All rights reserved.

  7. Classification of histological severity of Helicobacter pylori-associated gastritis by confocal laser endomicroscopy

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    AIM: To classify the histological severity of Helicobacter pylori (H. pylori) infection-associated gastritis by confocal laser endomicroscopy (CLE). METHODS: Patients with upper gastrointestinal symptoms or individuals who were screened for gastric cancer were enrolled in this study. Histological severity of H. pylori infection-associated gastritis was graded according to the established CLE criteria. Diagnostic value of CLE for histo-logical gastritis was investigated and compared with that of white light ...

  8. Improvement of impaired diastolic left ventricular function after diet-induced weight reduction in severe obesity

    Science.gov (United States)

    Karimian, Sevda; Stein, Juergen; Bauer, Boris; Teupe, Claudius

    2017-01-01

    Background/objectives Obesity is independently associated with left ventricular (LV) diastolic dysfunction and altered cardiac morphology. Morbidity and mortality in patients with diastolic dysfunction are similar to values observed in patients with systolic heart failure. We hypothesized that dysfunctional cardiac responses in people with obesity are reversible after weight loss. Thus, we studied the effect of dietary weight reduction on LV diastolic function as well as on cardiac structure using transthoracic echocardiography and tissue Doppler imaging (TDI). Subjects/methods Thirty-two subjects with obesity underwent a 12-week low-calorie fasting phase of a formula diet. Echocardiographic tissue Doppler indices of diastolic function and measurements of cardiac size were obtained prior to and after the fasting phase. Results A 12-week diet significantly reduced body mass index from 40.3 ± 6.6 kg/m2 to 33.2 ± 6.1 kg/m2 (p < 0.01). Weight loss was associated with a significant reduction in blood pressure and heart rate. Echocardiography revealed diastolic dysfunction in subjects with obesity, which was improved by dieting. After weight loss, trans-mitral Doppler echocardiography showed a significant reduction in A-wave velocity, from 65.8 ± 19.2 cm/s to 57.0 ± 16.8 cm/s, and an increase in E/A ratio from 1.2 ± 0.4 to 1.4 ± 0.5 (p < 0.01). TDI displayed a significantly lower a′-wave velocity (10.3 ± 2.3 cm/s and 8.9 ± 1.7 cm/s; p < 0.01). Left atrial and LV dimensions were normal and remained unchanged after weight loss. Conclusion Obesity is associated with diastolic dysfunction. A 12-week low-calorie diet with successful weight loss can reduce blood pressure and heart rate and partially normalize diastolic dysfunction. PMID:28123309

  9. A classification of substance-dependent men on temperament and severity variables.

    Science.gov (United States)

    Henderson, Melinda J; Galen, Luke W

    2003-06-01

    This study examined the validity of classifying substance abusers based on temperament and dependence severity, and expanded the scope of typology differences to proximal determinants of use (e.g., expectancies, motives). Patients were interviewed about substance use, depression, and family history of alcohol and drug abuse. Self-report instruments measuring temperament, expectancies, and motives were completed. Participants were 147 male veterans admitted to inpatient substance abuse treatment at a U.S. Department of Veterans Affairs medical center. Cluster analysis identified four types of users with two high substance problem severity and two low substance problem severity groups. Two, high problem severity, early onset groups differed only on the cluster variable of negative affectivity (NA), but showed differences on antisocial personality characteristics, hypochondriasis, and coping motives for alcohol. The two low problem severity groups were distinguished by age of onset and positive affectivity (PA). The late onset, low PA group had a higher incidence of depression, a greater tendency to use substances in solitary contexts, and lower enhancement motives for alcohol compared to the early onset, high PA cluster. The four-cluster solution yielded more distinctions on external criteria than the two-cluster solution. Such temperament variation within both high and low severity substance abusers may be important for treatment planning.

  10. Correlation of disease severity with body weight and high fat diet in the FATZO/Pco mouse.

    Science.gov (United States)

    Droz, Brian A; Sneed, Bria L; Jackson, Charles V; Zimmerman, Karen M; Michael, M Dodson; Emmerson, Paul J; Coskun, Tamer; Peterson, Richard G

    2017-01-01

    Obesity in many current pre-clinical animal models of obesity and diabetes is mediated by monogenic mutations; these are rarely associated with the development of human obesity. A new mouse model, the FATZO mouse, has been developed to provide polygenic obesity and a metabolic pattern of hyperglycemia and hyperinsulinemia, that support the presence of insulin resistance similar to metabolic disease in patients with insulin resistance/type 2 diabetes. The FATZO mouse resulted from a cross of C57BL/6J and AKR/J mice followed by selective inbreeding for obesity, increased insulin and hyperglycemia. Since many clinical studies have established a close link between higher body weight and the development of type 2 diabetes, we investigated whether time to progression to type 2 diabetes or disease severity in FATZO mice was dependent on weight gain in young animals. Our results indicate that lighter animals developed metabolic disturbances much slower and to a lesser magnitude than their heavier counterparts. Consumption of a diet containing high fat, accelerated weight gain in parallel with disease progression. A naturally occurring and significant variation in the body weight of FATZO offspring enables these mice to be identified as low, mid and high body weight groups at a young age. These weight groups remain into adulthood and correspond to slow, medium and accelerated development of type 2 diabetes. Thus, body weight inclusion criteria can optimize the FATZO model for studies of prevention, stabilization or treatment of type 2 diabetes.

  11. Influence on and Severity of Weight Concern: Bulimics, Dieters, and Controls.

    Science.gov (United States)

    Jones, Terri L.; Wolchik, Sharlene A.

    Little previous research has compared bulimics to dieters who do not binge eat but who are also concerned with their weight. This study examined differences between college students who were classified as either bulimic (N=21), chronic dieters (N=29), or controls (N=83). The extent to which remarks made by significant others and failure…

  12. Improvement of impaired diastolic left ventricular function after diet-induced weight reduction in severe obesity

    Directory of Open Access Journals (Sweden)

    Karimian S

    2017-01-01

    Full Text Available Sevda Karimian,1 Juergen Stein,2 Boris Bauer,3 Claudius Teupe1 1Department of Medicine – Cardiology, 2Department of Medicine – Gastroenterology, 3Department of Radiology, Krankenhaus Sachsenhausen, Teaching Hospital of Goethe University Frankfurt, Frankfurt, Germany Background/objectives: Obesity is independently associated with left ventricular (LV diastolic dysfunction and altered cardiac morphology. Morbidity and mortality in patients with diastolic dysfunction are similar to values observed in patients with systolic heart failure. We hypothesized that dysfunctional cardiac responses in people with obesity are reversible after weight loss. Thus, we studied the effect of dietary weight reduction on LV diastolic function as well as on cardiac structure using transthoracic echocardiography and tissue Doppler ­imaging (TDI. Subjects/methods: Thirty-two subjects with obesity underwent a 12-week low-calorie fasting phase of a formula diet. Echocardiographic tissue Doppler indices of diastolic function and measurements of cardiac size were obtained prior to and after the fasting phase. Results: A 12-week diet significantly reduced body mass index from 40.3 ± 6.6 kg/m2 to 33.2 ± 6.1 kg/m2 (p < 0.01. Weight loss was associated with a significant reduction in blood pressure and heart rate. Echocardiography revealed diastolic dysfunction in subjects with obesity, which was improved by dieting. After weight loss, trans-mitral Doppler echocardiography showed a significant reduction in A-wave velocity, from 65.8 ± 19.2 cm/s to 57.0 ± 16.8 cm/s, and an increase in E/A ratio from 1.2 ± 0.4 to 1.4 ± 0.5 (p < 0.01. TDI displayed a significantly lower a′-wave velocity (10.3 ± 2.3 cm/s and 8.9 ± 1.7 cm/s; p < 0.01. Left atrial and LV dimensions were normal and remained unchanged after weight loss. Conclusion: Obesity is associated with diastolic dysfunction. A 12-week low-calorie diet with successful weight loss can reduce blood pressure

  13. Classification and mass production technique for three-quarter shoe insoles using non-weight-bearing plantar shapes.

    Science.gov (United States)

    Sun, Shuh-Ping; Chou, Yi-Jiun; Sue, Chun-Chia

    2009-07-01

    We have developed a technique for the mass production and classification of three-quarter shoe insoles via a 3D anthropometric measurement of full-size non-weight-bearing plantar shapes. The plantar shapes of fifty 40-60-year-old adults from Taiwan were categorized and, in conjunction with commercially available flat or leisure shoe models, three-quarter shoe-insole models were generated using a CAD system. Applying a rapid prototype system, these models were then used to provide the parameters for manufacturing the shoe insoles. The insoles developed in this study have been classified into S, M and L types that offer user-friendly options for foot-care providers. We concluded that these insoles can mate tightly with the foot arch and disperse the pressure in the heel and forefoot over the foot arch. Thus, practically, the pressure difference over the plantar region can be minimised, and the user can experience comfort when wearing flat or leisure shoes.

  14. 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.

    2011-01-01

    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 fi

  15. Cellulite: poor correlation between instrumental methods and photograph evaluation for severity classification.

    Science.gov (United States)

    Soares, J L M; Miot, H A; Sanudo, A; Bagatin, E

    2015-02-01

    Cellulite refers to skin relief alterations in women's thighs and buttocks, causing dissatisfaction and search for treatment. Its physiopathology is complex and not completely understood. Many therapeutic options have been reported with no scientific evidence about benefits. The majority of the studies are not controlled nor randomized; most efficacy endpoints are subjective, like not well-standardized photographs and investigator opinion. Objective measures could improve severity assessment. Our purpose was to correlate non-invasive instrumental measures and standardized clinical evaluation. Twenty six women presenting cellulite on buttocks, aged from 25 to 41, were evaluated by: body mass index; standardized photography analysis (10-point severity and 5-point photonumeric scales) by five dermatologists; cutometry and high-frequency ultrasonography (dermal density and dermis/hypodermis interface length). Quality of life impact was assessed. Correlations between clinical and instrumental parameters were performed. Good agreement among dermatologists and main investigator perceptions was detected. Positive correlations: body mass index and clinical scores; ultrasonographic measures. Negative correlation: cutometry and clinical scores. Quality of life score was correlated to dermal collagen density. Cellulite caused impact in quality of life. Poor correlation between objective measures and clinical evaluation was detected. Cellulite severity assessment is a challenge, and objective parameters should be optimized for clinical trials. © 2014 Society of Cosmetic Scientists and the Société Française de Cosmétologie.

  16. 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

  17. Classification of histological severity of Helicobacter pylori-associated gastritis by confocal laser endomicroscopy

    Science.gov (United States)

    Wang, Peng; Ji, Rui; Yu, Tao; Zuo, Xiu-Li; Zhou, Cheng-Jun; Li, Chang-Qing; Li, Zhen; Li, Yan-Qing

    2010-01-01

    AIM: To classify the histological severity of Helicobacter pylori (H. pylori) infection-associated gastritis by confocal laser endomicroscopy (CLE). METHODS: Patients with upper gastrointestinal symptoms or individuals who were screened for gastric cancer were enrolled in this study. Histological severity of H. pylori infection-associated gastritis was graded according to the established CLE criteria. Diagnostic value of CLE for histological gastritis was investigated and compared with that of white light endoscopy (WLE). Targeted biopsies from the sites observed by CLE were performed. RESULTS: A total of 118 consecutive patients with H. pylori infection-associated gastritis were enrolled in this study. Receiver operating characteristic curve analysis showed that the sensitivity and specificity of CLE were 82.9% and 90.9% for the diagnosis of H. pylori infection, 94.6% and 97.4% for predicting gastric normal mucosa, 98.5% and 94.6% for predicting histological active inflammation, 92.9% and 95.2% for predicting glandular atrophy, 98.6% and 100% for diagnosing intestinal metaplasia, respectively. Post-CLE image analysis showed that goblet cells and absorptive cells were the two most common parameters on the CLE-diagnosed intestinal metaplasia (IM) images (P gastritis. Mapping IM by CLE has a rather good diagnostic accuracy. PMID:21049554

  18. 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.

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

    Science.gov (United States)

    Valerio, Giuliana; Maffeis, Claudio; Balsamo, Antonio; Del Giudice, Emanuele Miraglia; Brufani, Claudia; Grugni, Graziano; Licenziati, Maria Rosaria; Brambilla, Paolo; Manco, Melania

    2013-01-01

    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 pobese 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.

  20. Complications of fat grafts growth after weight gain: report of a severe diplopia.

    Science.gov (United States)

    Duhoux, Alexandre; Chennoufi, Mehdi; Lantieri, Laurent; Hivelin, Mikael

    2013-07-01

    A 47 years old woman underwent autologous fat grafting to treat a 5×4 cm depression of the lower lid and the upper cheek secondary resection of squamous cell carcinoma and subsequent coverage by full thickness skin graft. 20 mL of autologous fat were harvested from lower abdomen, centrifuged and injected subcutaneously. The patient then gained a total of 15 kg over a period of 24 months. Eye dystopia developed while the grafted area became convex. MRI confirmed subcutaneous fat mass going to the orbital floor through the inferior septal defect. The fat excess was removed through a trans-conjonctival approach allowing for a progressive regression of diplopia after 2 months while the oedema reduced. The overall follow up from the resection-coverage and last examination was 5 years. In this case with a context of noticeable weight gain, the growth of a fat graft trapped between a sclerous plane and the eye, that penetrated the orbital cavity through a septal defect led have led to exophthalmos, ocular dystopia and diplopia. Systematic overcorrection in autologous fat grafting should be prevented, especially in functional areas and on low body mass index patient that might gain weight.

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

    Directory of Open Access Journals (Sweden)

    Giuliana Valerio

    Full Text Available OBJECTIVES: 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. RESEARCH DESIGN AND METHODS: 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. RESULTS: 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. CONCLUSIONS: 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

  2. Severe Obesity and Cardiometabolic Risk in Children: Comparison from Two International Classification Systems

    Science.gov (United States)

    Valerio, Giuliana; Maffeis, Claudio; Balsamo, Antonio; Del Giudice, Emanuele Miraglia; Brufani, Claudia; Grugni, Graziano; Licenziati, Maria Rosaria; Brambilla, Paolo; Manco, Melania

    2013-01-01

    Objectives 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. Research Design and Methods Cross-sectional, multicenter study involving 3,340 overweight/obese young subjects. Sev-OB was defined as BMI ≥99th percentile or ≥1.2 times the 95th 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. Results The estimated prevalence of Sev-OB varied widely between the two reference systems. Either using the cut-point ≥99th percentile or ≥1.2 times the 95th 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 99th 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 95th 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 95th percentile, in particular in children ≤10 years. Conclusions 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 95th percentile of BMI of either CDC or WHO standard has a discriminatory advantage over the 99th percentile for identifying severely obese children at increased cardiometabolic risk, particularly under 10 years of age. PMID:24386280

  3. 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.

  4. 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.)

  5. A 15-year-old boy with severe combined immunodeficiency, fungal infection, and weight gain.

    Science.gov (United States)

    Abul, Mehtap Haktanir; Tuano, Karen; Healy, C Mary; Vece, Timothy J; Quintanilla, Norma M; Davis, Carla M; Seeborg, Filiz O; Hanson, Imelda Celine

    2015-01-01

    Hematopoietic stem cell transplantation (HSCT) outcomes in X-linked severe combined immune deficiency are most effective when performed with patients <3 months of age and without coexisting morbidity, and with donor cells from a matched sibling. Even under such favorable circumstances, outcomes can be suboptimal, and full cellular engraftment may not be complete, which results in poor B or natural killer cell function. Protein losing enteropathies can accompany persistent immune deficiency disorders with resultant low serum globulins (immunoglobulin A [IgA], IgG, IgM) and lymphopenia. Patients with immune disorders acquire infections that can be predicted by their immune dysfunction. Fungal infections are typically noted in neutropenic (congenital or acquired) and T-cell deficient individuals. Coexisting fungal infections are rare, even in hosts who are immunocompromised, and they require careful evaluation. Antifungal treatment may result in drug-drug interactions with significant complications.

  6. Impact of Orlistat-Induced Weight Loss on Diastolic Function and Heart Rate Variability in Severely Obese Subjects with Diabetes

    Directory of Open Access Journals (Sweden)

    Julie Martin

    2011-01-01

    Full Text Available Objective. Determine the impact of Orlistat-induced weight loss on metabolic profile and cardiovascular function in severely obese patients with type 2 diabetes. Methods. Twenty-nine patients were randomized either to a nonplacebo control group or to a treatment group with Orlistat thrice a day. Metabolic profile, anthropometric parameters, heart rate variability indices, and echocardiographic variables were measured before and after a 12-week treatment period. Results. Treatment with Orlistat induced a modest but significant weight loss compared to controls (3.7 ± 3.0 versus 0.5 ± 2.2 kg, resp.; P=.003. There was significant decrease in fasting glycemia (7.9 ± 3.0 versus 6.7 ± 2.2 mmol/L; P=.03 and significant improvements in left ventricular diastolic function (P=.03 and in the sympathovagal balance (LF/HF ratio (P=.04 in the Orlistat group. Conclusion. These results suggest that a modest weight loss improves fasting glycemia, left ventricular diastolic function, and sympathovagal balance in severely obese patients with type 2 diabetes.

  7. 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

  8. Household tobacco smoke and admission weight predict severe bronchiolitis in infants independent of deprivation: prospective cohort study.

    Directory of Open Access Journals (Sweden)

    Malcolm G Semple

    Full Text Available OBJECTIVES: To examine demographic, environmental and clinical factors associated with severe bronchiolitis in infants admitted to hospital and quantify the independent effects of these factors. DESIGN: Prospective cohort study. SETTING: Alder Hey Children's Hospital, Liverpool, United Kingdom. PARTICIPANTS: 378 infants admitted to hospital with a diagnosis of bronchiolitis, of whom 299 (79% were antigen positive to respiratory syncytial virus (RSV. OUTCOME: Severity of disease during admission, defined as "no need for supplemental oxygen" (reference group, "any need for supplemental oxygen" and "any need for mechanical ventilation". RESULTS: Univariate analysis found male sex (p = 0.035 and tobacco smoking by a household member (p<0.001 were associated with need for both supplemental oxygen and mechanical ventilation. Premature birth, low gestation, low birth weight, low admission weight and low corrected age on admission were also associated with need for mechanical ventilation (all p≤0.002. Deprivation scores (IMD 2004 were significantly higher in households where a member smoked compared to non-smoking households (p<0.001. The odds of smoking predicted by deprivation were 7 times higher (95%CI (3.59, 14.03, when comparing the least and most deprived quintiles of the study population. Family history of atopic disease and deprivation score were not associated with severe disease. Multivariate multinomial logistic regression which initially included all covariates, found household tobacco smoking (adjusted OR = 2.45, 95%CI (1.60, 3.74 predicted need for oxygen supplementation. Household tobacco smoking (adjusted OR = 5.49, (2.78, 10.83 and weight (kg on admission (adjusted OR = 0.51, (0.40, 0.65 were both significant predictors in the final model for mechanical ventilation. The same associations and similar size of effects were found when only children with proven RSV infection were included in analysis. CONCLUSIONS: Low

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

    DEFF Research Database (Denmark)

    Lange, 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...

  10. 33 ku protein associated several polypeptides with nearly the same molecular weight but not the same isoelectric point

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    The 33 ku protein,prepared from NaCl-treated PSⅡ particles,has shown an single band by SDS-PAGE.After being dialyzed against the low-osmotic medium at 4℃,it has been found that the 33 ku protein degraded into several small fragments.This result suggests that the preparations of 33 ku protein probably contain some latent proteinases.It has also been found,by the 2-D electrophoresis and IEF,that the preparations of 33 ku protein not dialyzed against the low-osmotic medium contain several polypeptides with nearly the same molecular weight but not the same isoelectric point as the 33 ku protein.

  11. 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.

  12. Evaluation of the World Health Organization 2009 classification of dengue severity in autopsied individuals, during the epidemics of 2011 and 2012 in Brazil

    Directory of Open Access Journals (Sweden)

    Luciano Pamplona de Góes Cavalcanti

    2015-12-01

    Full Text Available Abstract: INTRODUCTION: The dengue classification proposed by the World Health Organization (WHO in 2009 is considered more sensitive than the classification proposed by the WHO in 1997. However, no study has assessed the ability of the WHO 2009 classification to identify dengue deaths among autopsied individuals suspected of having dengue. In the present study, we evaluated the ability of the WHO 2009 classification to identify dengue deaths among autopsied individuals suspected of having dengue in Northeast Brazil, where the disease is endemic. METHODS: This retrospective study included 121 autopsied individuals suspected of having dengue in Northeast Brazil during the epidemics of 2011 and 2012. All the autopsied individuals included in this study were confirmed to have dengue based on the findings of laboratory examinations. RESULTS: The median age of the autopsied individuals was 34 years (range, 1 month to 93 years, and 54.5% of the individuals were males. According to the WHO 1997 classification, 9.1% (11/121 of the cases were classified as dengue hemorrhagic fever (DHF and 3.3% (4/121 as dengue shock syndrome. The remaining 87.6% (106/121 of the cases were classified as dengue with complications. According to the 2009 classification, 100% (121/121 of the cases were classified as severe dengue. The absence of plasma leakage (58.5% and platelet counts <100,000/mm3 (47.2% were the most frequent reasons for the inability to classify cases as DHF. CONCLUSIONS: The WHO 2009 classification is more sensitive than the WHO 1997 classification for identifying dengue deaths among autopsied individuals suspected of having dengue.

  13. Automated development of linguistic-fuzzy classifier membership functions and weights for use in disparate sensor integration visible and infrared imaging sensor classification

    Science.gov (United States)

    Nelson, Bruce N.; Birenzvige, Amnon

    2004-04-01

    In support of the Disparate Sensor Integration (DSI) Program a number of imaging sensors were fielded to determine the feasibility of using information from these systems to discriminate between chemical and conventional munitions. The camera systems recorded video from 160 training and 100 blind munitions detonation events. Two types of munitions were used; 155 mm conventional rounds and 155 mm chemical simulant rounds. In addition two different modes of detonation were used with these two classes of munitions; detonation on impact (point detonation) and detonation in the air (airblasts). The cameras fielded included two visible wavelength cameras, a near infrared camera (peak responsivity of approximately 1μm), a mid wavelength infrared camera system (3 μm to 5 μm) and a long wavelength infrared camera system (7.5 μm to 13 μm). Our recent work has involved developing Linguistic-Fuzzy Classifiers for performing munitions detonation classification with the DSI visible and infrared imaging sensors data sets. In this initial work, the classifiers were heuristically developed based on analyses of the training data features distributions. In these initial classification systems both the membership functions and the feature weights were hand developed and tuned. We have recently developed new methodologies to automatically generate membership functions and weights in Linguistic-Fuzzy Classifiers. This paper will describe this new methodology and provide an example of its efficacy for separating munitions detonation events into either air or point detonation. This is a critical initial step in achieving the overall goal of DSI; the classification of detonation events as either chemical or conventional. Further, the detonation mode is important as it significantly effects the dispersion of agents. The results presented in this paper clearly demonstrate that the automatically developed classifiers perform as well in this classification task as the previously developed

  14. Effect of Body Weight and Esophageal Damage on the Severity of Gastroesophageal Reflux Symptoms. Mexican GERD Working Group

    Science.gov (United States)

    Lopez-Alvarenga, Juan Carlos; Vargas, José Antonio; Lopez, Luis Humberto; Fass, Ronnie; Sobrino-Cossio, Sergio; Higgins, Paul; Comuzzie, Anthony

    2010-01-01

    Background and Aims Several studies have demonstrated overweight and obesity are strong independent risk factor of GERD symptoms and esophageal erosions. Our aim was to analyze the joint effect of BMI with the grade of esophageal damage over symptoms’ intensity of GERD. Methods We used a questionnaire with a Likert scale for severity of symptoms related to GERD. The distal portion of the esophagus was evaluated to determine the presence of mucosal injury, classified by Los Angeles criteria (LA). Results We included 917 subjects (53.76% females) with average age 36.8 ± 7 years. Males had higher BMI than females (26.8 ± 3.5 vs. 25.2 ± 4.5, p 30 had high score for heartburn and retching, but low score for nausea, compared with lower weight. The model with interaction showed a non-linear association between BMI and LA. Overweight (but not obese) patients with damage scored C–D had the highest score for intensity of heartburn and retching. Conclusions BMI and LA do not have additive effects on the severity of symptoms of GERD. Those with BMI between 25 and 30 had severe symptoms score, but those with BMI >30 showed lower scores. These findings could explain controversial results found in other studies. PMID:20082872

  15. 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…

  16. 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…

  17. Prevalence of male secondary hypogonadism in moderate to severe obesity and its relationship with insulin resistance and excess body weight.

    Science.gov (United States)

    Calderón, Berniza; Gómez-Martín, Jesús M; Vega-Piñero, Belén; Martín-Hidalgo, Antonia; Galindo, Julio; Luque-Ramírez, Manuel; Escobar-Morreale, Héctor F; Botella-Carretero, José I

    2016-01-01

    To study the prevalence of male obesity-secondary hypogonadism (MOSH) in patients with moderate to severe obesity, we performed a prospective prevalence study including 100 male patients with moderate to severe obesity at a university tertiary hospital. Total testosterone (TT) and sex hormone-binding globulin (SHBG) concentrations among others were assayed in all patients. Serum-free testosterone (FT) concentration was calculated from TT and SHBG levels. Semen analysis was conducted in 31 patients. We found a prevalence of 45% (95% CI: 35-55%) when considering decreased TT and/or FT concentrations. Serum concentrations of TT were correlated negatively with glucose (r = -0.328, p insulin resistance (r = -0.261, p = 0.011). The same occurred with FT and glucose (r = -0.340, p insulin resistance (r = -0.246, p = 0.016). Sixty-two percent (95% CI: 39-85%) of the patients with seminogram also presented abnormal results in semen analysis. The frequencies of low TT or low FT values were similar in patients with abnormal or normal semen analysis (p = 0.646 and p = 0.346, respectively). Ejaculate volume inversely correlated with BMI (ρ = -0.400, p = 0.029) and with excess body weight (ρ = -0.464, p = 0.010). Our data show the prevalence of MOSH in patients with moderate to severe obesity is high. Low circulating testosterone is associated with insulin resistance and low ejaculate volume with higher BMI and excess body weight. Semen analysis must be performed in these patients when considering fertility whether or not presenting low circulating testosterone. © 2015 American Society of Andrology and European Academy of Andrology.

  18. Predicting quality of life in adults with severe mental illness: Extending the International Classification of Functioning, Disability, and Health.

    Science.gov (United States)

    Sánchez, Jennifer; Rosenthal, David A; Tansey, Timothy N; Frain, Michael P; Bezyak, Jill L

    2016-02-01

    The International Classification of Functioning, Disability and Health (ICF) framework was used to investigate person-environment contextual factors, mental functioning, activity limitations, and participation as predictors of quality of life (QoL) in adults with severe mental illness (SMI). A quantitative descriptive design using multiple regression and correlational analyses was used. One hundred ninety-four individuals with SMI from 4 community-based mental health agencies in 2 states from Southern and Midwestern regions of the United States participated in the study. The criterion variable was QoL. Predictor variables comprised the ICF constructs: (a) demographics, (b) personal factors, (c) environmental factors, (d) mental functioning, (e) activity limitations, and (f) participation. A majority of participants were White (60.3%) and not employed (59.8%). Half of them received Social Security Disability Income and/or Supplemental Security Income (50.0%). Correlations between QoL and the predictor variables ranged from small to large (r = .01 to .63, respectively). The final regression model accounted for 58% of the variance in QoL. After controlling for other factors, social competency, social support, societal stigma, psychological distress, cognitive dysfunction, activity limitations, and participation were found to be significant predictors of QoL in adults with SMI. The study supports the use of the ICF to predict QoL for adults with SMI. Evidence-based treatments focused on increasing social competence, social support, and participation should be developed to promote rehabilitation outcomes and overall QoL. (c) 2016 APA, all rights reserved).

  19. Assessing Field Triage Decisions and the International Classification Injury Severity Score (ICISS) at Predicting Outcomes of Trauma Patients.

    Science.gov (United States)

    Allen, Casey J; Baldor, Daniel J; Schulman, Carl I; Pizano, Louis R; Livingstone, Alan S; Namias, Nicholas

    2017-06-01

    Florida considers the International Classification Injury Severity Score (ICISS) from hospital discharges within a geographic region in the apportionment of trauma centers (TCs). Patients with an ICISS <0.85 are considered to require triage to a TC, yet many are triaged to an emergency department (ED). We assess outcomes of those with an ICISS <0.85 by the actual triage decision of emergency medical services (EMS). From October 2011 to October 2013, 39,021 consecutive admissions with injury ICD-9 codes were analyzed. ICISS was calculated from the product of the survival risk ratios for a patient's three worst injuries. Outcomes were compared between patients with ICISS <0.85 either triaged to the ED or its separate, neighboring, free-standing TC at a large urban hospital. A total of 32,191 (83%) patients were triaged to the ED by EMS and 6,827 (17%) were triaged to the TC. Of these, 2544 had an ICISS <0.85, with 2145 (84%) being triaged to the TC and 399 (16%) to the ED. In these patients, those taken to the TC more often required admission, and those taken to the ED had better outcomes. When the confounders influencing triage to an ED or a TC are eliminated, those triaged by EMS to the ED rather than the TC had better overall outcomes. EMS providers better identified patients at risk for mortality than did the retrospective application of ICISS. ICISS <0.85 does not identify the absolute need for TC as EMS providers were able to appropriately triage a large portion of this population to the ED.

  20. Spatial Analysis of Severe Fever with Thrombocytopenia Syndrome Virus in China Using a Geographically Weighted Logistic Regression Model

    Directory of Open Access Journals (Sweden)

    Liang Wu

    2016-11-01

    Full Text Available Severe fever with thrombocytopenia syndrome (SFTS is caused by severe fever with thrombocytopenia syndrome virus (SFTSV, which has had a serious impact on public health in parts of Asia. There is no specific antiviral drug or vaccine for SFTSV and, therefore, it is important to determine the factors that influence the occurrence of SFTSV infections. This study aimed to explore the spatial associations between SFTSV infections and several potential determinants, and to predict the high-risk areas in mainland China. The analysis was carried out at the level of provinces in mainland China. The potential explanatory variables that were investigated consisted of meteorological factors (average temperature, average monthly precipitation and average relative humidity, the average proportion of rural population and the average proportion of primary industries over three years (2010–2012. We constructed a geographically weighted logistic regression (GWLR model in order to explore the associations between the selected variables and confirmed cases of SFTSV. The study showed that: (1 meteorological factors have a strong influence on the SFTSV cover; (2 a GWLR model is suitable for exploring SFTSV cover in mainland China; (3 our findings can be used for predicting high-risk areas and highlighting when meteorological factors pose a risk in order to aid in the implementation of public health strategies.

  1. 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.)

  2. Evaluation of the WHO classification of dengue disease severity during an epidemic in 2011 in the state of Ceará, Brazil

    Science.gov (United States)

    Cavalcanti, Luciano Pamplona de Góes; Mota, Lia Alves Martins; Lustosa, Gustavo Porto; Fortes, Mayara Carvalho; Mota, Davi Alves Martins; Lima, Antônio Afonso Bezerra; Coelho, Ivo Castelo Branco; Mourão, Maria Paula Gomes

    2013-01-01

    In 2009, the World Health Organization (WHO) issued a new guideline that stratifies dengue-affected patients into severe (SD) and non-severe dengue (NSD) (with or without warning signs). To evaluate the new recommendations, we completed a retrospective cross-sectional study of the dengue haemorrhagic fever (DHF) cases reported during an outbreak in 2011 in northeastern Brazil. We investigated 84 suspected DHF patients, including 45 (53.6%) males and 39 (46.4%) females. The ages of the patients ranged from five-83 years and the median age was 29. According to the DHF/dengue shock syndrome classification, 53 (63.1%) patients were classified as having dengue fever and 31 (36.9%) as having DHF. According to the 2009 WHO classification, 32 (38.1%) patients were grouped as having NSD [4 (4.8%) without warning signs and 28 (33.3%) with warning signs] and 52 (61.9%) as having SD. A better performance of the revised classification in the detection of severe clinical manifestations allows for an improved detection of patients with SD and may reduce deaths. The revised classification will not only facilitate effective screening and patient management, but will also enable the collection of standardised surveillance data for future epidemiological and clinical studies. PMID:24626308

  3. Duplication Cyst in the Third Part of the Duodenum Presenting with Gastric Outlet Obstruction and Severe Weight Loss

    Science.gov (United States)

    Shaheen, Osama; Sara, Samer; Safadi, Mhd Firas; Alsaid, Bayan

    2015-01-01

    Duodenal duplication is a rare developmental abnormality which is usually diagnosed in infancy and childhood, but less frequently in adulthood. We report a case of a 16-year-old female with a duplication cyst in the third part of the duodenum. The patient presented with symptoms of gastric outlet obstruction, including severe anorexia and weight loss. The diagnosis was made preoperatively by CT scan and upper endoscopy. The cyst was successfully treated by marsupialization on the duodenum using a GIA stapler. Duodenal duplication presents with a wide variety of symptoms. Although illusive, many cases can be properly diagnosed preoperatively by using the appropriate imaging modalities. Treatment choices are tailored according to the size and location of the cyst, in addition to its relation to adjacent structures. The outcomes are favorable in the majority of patients. PMID:26649220

  4. 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.

  5. 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 teenagers, associated with an increase in ghrelin (apparent from month 6; P 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.

  6. Physical fitness of secondary school adolescents in relation to the body weight and the body composition: classification according to World Health Organization. Part I.

    Science.gov (United States)

    Chwałczyńska, Agnieszka; Jędrzejewski, Grzegorz; Socha, Małgorzata; Jonak, Wiesława; Sobiech, Krzysztof A

    2017-03-01

    Underweight and obesity are important factors affecting the level of physical fitness. The aim of this study was to assess physical fitness of lower secondary school adolescents in relation to BMI. Two-hundred students, aged 14-16, were examined. Respondents were divided into 4 groups according to BMI classification. The body height and weight were determined. Physical fitness was assessed on the basis Zuchora's ISF tests. The body weight deficiency occurred in 3% of girls and 5% of boys, overweight was noted in 14% of both groups, and obesity in 6% and 12% accordingly. Statistically significant differences were determined in the components of physical fitness. They were noted in both genders between the group of children with standard body weight and overweight as well as obese children. Significant negative correlations were determined between and the components of physical fitness. More significant correlations giving evidence to the decrease of Zuchora's ISF score along with the increase of BMI were more significant in girls. Statistically significant differences between the boys and girls were determined in all five Zuchora's tests. The highest scores in physical fitness were achieved by the boys and girls with weight deficiency.

  7. Physical fitness of secondary school adolescents in relation to the body weight and the body composition: classification according to Bioelectrical Impedance Analysis. Part II.

    Science.gov (United States)

    Chwałczyńska, Agnieszka; Jędrzejewski, Grzegorz; Lewandowski, Zdzisław; Jonak, Wiesława; Sobiech, Krzysztof A

    2017-03-01

    Underweight and obesity are important factors affecting the level of physical fitness. The aim of this study was to assess physical fitness of lower secondary school adolescents in relation to BMI. Two-hundred students, aged 14-16, were examined. Respondents were divided into 4 groups according to BMI classification. The body height and weight were determined. Physical fitness was assessed on the basis Zuchora's ISF tests. The body weight deficiency occurred in 3% of girls and 5% of boys, overweight was noted in 14% of both groups, and obesity in 6% and 12% accordingly. Statistically significant differences were determined in the components of physical fitness. They were noted in both genders between the group of children with standard body weight and overweight as well as obese children. Significant negative correlations were determined between and the components of physical fitness. More significant correlations giving evidence to the decrease of Zuchora's ISF score along with the increase of BMI were more significant in girls. Statistically significant differences between the boys and girls were determined in all five Zuchora's tests. The highest scores in physical fitness were achieved by the boys and girls with weight deficiency.

  8. Severity of depressive symptoms and accuracy of dietary reporting among obese women with major depressive disorder seeking weight loss treatment.

    Science.gov (United States)

    Whited, Matthew C; Schneider, Kristin L; Appelhans, Bradley M; Ma, Yunsheng; Waring, Molly E; DeBiasse, Michele A; Busch, Andrew M; Oleski, Jessica L; Merriam, Philip A; Olendzki, Barbara C; Crawford, Sybil L; Ockene, Ira S; Lemon, Stephenie C; Pagoto, Sherry L

    2014-01-01

    An elevation in symptoms of depression has previously been associated with greater accuracy of reported dietary intake, however this association has not been investigated among individuals with a diagnosis of major depressive disorder. The purpose of this study was to investigate reporting accuracy of dietary intake among a group of women with major depressive disorder in order to determine if reporting accuracy is similarly associated with depressive symptoms among depressed women. Reporting accuracy of dietary intake was calculated based on three 24-hour phone-delivered dietary recalls from the baseline phase of a randomized trial of weight loss treatment for 161 obese women with major depressive disorder. Regression models indicated that higher severity of depressive symptoms was associated with greater reporting accuracy, even when controlling for other factors traditionally associated with reporting accuracy (coefficient  =  0.01 95% CI = 0.01 - 0.02). Seventeen percent of the sample was classified as low energy reporters. Reporting accuracy of dietary intake increases along with depressive symptoms, even among individuals with major depressive disorder. These results suggest that any study investigating associations between diet quality and depression should also include an index of reporting accuracy of dietary intake as accuracy varies with the severity of depressive symptoms.

  9. 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 r

  10. A metric measure for weight matrices of variable lengths—with applications to clustering and classification of hidden Markov models

    Science.gov (United States)

    Yu, Yi-Kuo

    2007-02-01

    We construct a metric measure among weight matrices that are commonly used in non-interacting statistical physics systems, computational biology problems, as well as in general applications such as hidden Markov models. The metric distance between two weight matrices is obtained via aligning the matrices and thus can be evaluated by dynamic programming. Capable of allowing reverse complements in distance evaluation, this metric accommodates both gapless and gapped alignments between two weight matrices. The distance statistics among random motifs is also studied. We find that the average square distance and its standard error grow with different powers of motif length, and the normalized square distance follows a Gaussian distribution for large motif lengths.

  11. Pegylated human recombinant leptin (PEG-OB) causes additional weight loss in severely energy-restricted, overweight men.

    Science.gov (United States)

    Hukshorn, Chris J; Westerterp-Plantenga, Margriet S; Saris, Wim H M

    2003-04-01

    Increasing evidence suggests that falling leptin concentrations observed during fasting act as a peripheral signal of starvation, which serves to conserve energy in the face of limited reserves. An extension of this hypothesis is that exogenous leptin should affect energy regulation during severe energy restriction. To explore this hypothesis, we assessed whether elevated leptin concentrations achieved with the use of long-acting pegylated human recombinant leptin [polyethylene glycol-OB protein (PEG-OB)] affected weight loss and changes in body composition, energy expenditure, appetite, and metabolic variables during semistarvation in healthy overweight men. A randomized, double-blind, placebo-controlled study was executed in overweight men with a mean (+/- SEM) age of 34.8 +/- 1.3 y and body mass index (in kg/m2) of 28.8 +/- 0.5. All subjects received weekly treatment with 80 mg PEG-OB (n = 12) or matching placebo (n = 10) for 46 d while their energy intake was reduced to 2.1 MJ/d by means of a very-low-energy diet. Body composition (hydrodensitometry and deuterium dilution), energy expenditure (ventilated hood), and appetite (visual analogue scales) were evaluated at the start and the end of the study. Metabolic variables were measured throughout the study period. Compared with placebo treatment, treatment with PEG-OB led to significant (P < 0.03) additional weight loss (14.6 +/- 0.8 compared with 11.8 +/- 0.9 kg) and a reduction in appetite (P < 0.05) after 46 d, but the 2 treatment groups did not differ significantly in changes in body composition, energy expenditure, and metabolic variables. Our observations support the hypothesis that the decrease in leptin concentrations during starvation increases appetite in humans.

  12. 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.

  13. 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 ...

  14. Kappa Coefficients for Circular Classifications

    NARCIS (Netherlands)

    Warrens, Matthijs J.; Pratiwi, Bunga C.

    2016-01-01

    Circular classifications are classification scales with categories that exhibit a certain periodicity. Since linear scales have endpoints, the standard weighted kappas used for linear scales are not appropriate for analyzing agreement between two circular classifications. A family of kappa coefficie

  15. The relationship between mean birth weight and poverty using the Townsend deprivation score and the Super Profile classification system.

    Science.gov (United States)

    Aveyard, P; Manaseki, S; Chambers, J

    2002-11-01

    Super Profiles have been used as alternative methods of characterising the deprivation of an area. Some reports suggest that Super Profiles are as accurate as established indices such as the Townsend score (TS). This was a test of this assertion.A total of 138 696 live born singleton births to Birmingham residents born between 1986 and 1996 (inclusive) were allocated to enumeration districts (EDs) by linkage from the postcode. We allocated the TS of the individual's ED. We allocated a Lifestyle and Target Market (TM) from Super Profiles by linkage to the ED. We examined the gradient between mean birth weight and the 10 Super Profile Lifestyles and compared this to the gradient between 10 Townsend groups and mean birth weight. We repeated this approach using the 40 TMs and 40 Townsend groups. We used both the median income and a census-derived deprivation measure to rank Lifestyles and TMs. The gradient between mean birth weight and area deprivation was linear for Townsend groups but not linear using either Lifestyles or TMs whichever method of ranking Lifestyles or TMs was used. Where Lifestyles or TMs were out of line with their neighbours, the TS of that group mostly explained this. As Super Profiles are generated using nationally representative data, applying the affluence ranking to small areas can lead to inaccuracies, as shown in this data. We conclude that Super Profiles are probably unsuitable as measures of deprivation of small areas.

  16. Diffusion weighted MR and apparent diffusion coefficient measurement in classification and characterization of noncystic focal liver lesions: does a clinical role exist?

    Science.gov (United States)

    Mungai, Francesco; Morone, Mario; Villanacci, Alberta; Bondioni, Maria Pia; Mazzoni, Lorenzo Nicola; Grazioli, Luigi; Colagrande, Stefano

    2014-07-01

    The objective of this study was to assess the clinical role of apparent diffusion coefficient (ADC) analysis in noncystic focal liver lesion (FLL) classification/characterization.Six hundred liver magnetic resonances with multi-b (b = 50, 400, 800 s/mm) diffusion-weighted imaging (DwI) were retrospectively reviewed. Mean ADC was measured in 388 lesions (195 benign and 193 malignant) excluding internal necrotic areas. Cystic benign lesions were excluded from analysis. Sensitivity and specificity in distinguishing benign from malignant lesions were calculated. Analysis of variance was performed to detect differences among subgroups of solid lesions.Mean ADC of malignant lesions was 0.980 × 10 mm/s, significantly (P 1/3 (39.5%) presented values lower than 1 × 10 mm/s, with 90.0% chance of malignancy. Above 1.5 × 10 mm/s (about 20% of all lesions) chance of malignancy was 9.5%.DwI cannot assist in noncystic FLL characterization, but can help in FLL classification in about half the cases.

  17. 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.

  18. 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

  19. 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 the reprodu...

  20. 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…

  1. 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…

  2. High molecular weight organic compounds (HMW-OCs) in severe winter haze: Direct observation and insights on the formation mechanism.

    Science.gov (United States)

    Duan, F K; He, K B; Ma, Y L; Ihozaki, T; Kawasaki, H; Arakawa, R; Kitayama, S; Tujimoto, K; Huang, T; Kimoto, T; Furutani, H; Toyoda, M

    2016-11-01

    High molecular weight organic compounds (HMW-OCs), formed as secondary organic aerosols (SOA), have been reported in many laboratory studies. However, little evidence of HMW-OCs formation, in particular during winter season in the real atmosphere, has been reported. In January 2013, Beijing faced historically severe haze pollution, in which the hourly PM2.5 concentration reached as high as 974 μg m(-3). Four typical haze events (HE1 to HE4) were identified, and HE2 (Jan. 9-16) was the most serious of these. Based on the hourly observed chemical composition of PM2.5 and the daily organic composition analyzed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS), we found that abundant ion peaks in m/z 200-850 appeared on heavy haze days, whereas these were negligible on a clear day, indicating the existence of HMW-OCs in the wintertime haze. A negative nonlinear correlation between HMW-OCs and O3 suggested that gas oxidation was not likely to be the dominant mechanism for HMW-OCs formation. During the heavy haze events, the relative humidity and mass ratio of H2O/PM2.5 reached as high as 80% and 0.2, respectively. The high water content and its good positive correlation with HMW-OCs indicated that an aqueous-phase process may be a significant pathway in wintertime. The evidence that acidity was much higher during HE2 (0.37 μg m(-3)) than on other days, as well as its strong correlation with HMW-OCs, indicated that acid-catalyzed reactions likely resulted in HMW-OCs formation during the heavy winter haze in Beijing.

  3. Deep white matter hyperintensity in the occipital lobe on T sub 2 -weighted MRI in children, 2; Classification based on the signal intensity

    Energy Technology Data Exchange (ETDEWEB)

    Miyazaki, Masahito; Hashimoto, Toshiaki (Tokushima Univ. (Japan). School of Medicine)

    1992-01-01

    Twenty-seven children, who had deep white matter hyperintensity in the occipital lobe (DWMH) on T{sub 2}-weighted MRI, were classified into two groups, mild and severe, based on the signal intensity. The frequency of mild DWMH, which was iso- or hyperintense relative to the gray matter but hypointense relative to cerebrospinal fluid (CSF), decreased with aging; mild DWMH might result from a delayed myelination in the central nervous system. However, the frequency of severe DWMH, which was iso- or hyperintense relative to CSF, was not related to aging and was significantly high in severely retarded children. Therefore, severe DWMH might be a new indicator of mental retardation in children. (author).

  4. 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.

  5. Classification of traumatic brain injury severity using informed data reduction in a series of binary classifier algorithms.

    Science.gov (United States)

    Prichep, Leslie S; Jacquin, Arnaud; Filipenko, Julie; Dastidar, Samanwoy Ghosh; Zabele, Stephen; Vodencarević, Asmir; Rothman, Neil S

    2012-11-01

    Assessment of medical disorders is often aided by objective diagnostic tests which can lead to early intervention and appropriate treatment. In the case of brain dysfunction caused by head injury, there is an urgent need for quantitative evaluation methods to aid in acute triage of those subjects who have sustained traumatic brain injury (TBI). Current clinical tools to detect mild TBI (mTBI/concussion) are limited to subjective reports of symptoms and short neurocognitive batteries, offering little objective evidence for clinical decisions; or computed tomography (CT) scans, with radiation-risk, that are most often negative in mTBI. This paper describes a novel methodology for the development of algorithms to provide multi-class classification in a substantial population of brain injured subjects, across a broad age range and representative subpopulations. The method is based on age-regressed quantitative features (linear and nonlinear) extracted from brain electrical activity recorded from a limited montage of scalp electrodes. These features are used as input to a unique "informed data reduction" method, maximizing confidence of prospective validation and minimizing over-fitting. A training set for supervised learning was used, including: "normal control," "concussed," and "structural injury/CT positive (CT+)." The classifier function separating CT+ from the other groups demonstrated a sensitivity of 96% and specificity of 78%; the classifier separating "normal controls" from the other groups demonstrated a sensitivity of 81% and specificity of 74%, suggesting high utility of such classifiers in acute clinical settings. The use of a sequence of classifiers where the desired risk can be stratified further supports clinical utility.

  6. Relationship Between Severity Classification of Acute Exacerbation of Chronic Obstructive Pulmonary Disease and Clinical Outcomes in Hospitalized Patients

    Science.gov (United States)

    Sanjuán, Pilar; Huerta, Arturo; Nieto-Codesido, Irene; Ferreira-Gonzalez, Lucía; Sibila, Oriol; Restrepo, Marcos I

    2017-01-01

    Background Limited data are available regarding the impact of the potential validation of the Canadian Thoracic Society (CTS) guidelines recommendations in classifying patients with an acute exacerbation of chronic obstructive pulmonary disease (AECOPD) in simple and complex. The aim of the present study was to assess the CTS recommendations regarding risk stratification on clinical outcomes among patients hospitalized with an AECOPD. Methods We developed a retrospective cohort study of patients admitted to one tertiary hospital with a diagnosis of AECOPD. The main clinical outcome was the percentage of treatment failure. Secondary outcomes were 30-day, 90-day, and 1-year readmission and mortality rate, length of stay in hospital, intensive care unit (ICU) admission rate, time to readmission, and time to death. Multivariate analyses were performed using 1-year mortality rate as the dependent measures. Results One hundred forty-three patients composed the final study population, most of them (106 [74.1%)] classified as complex acute exacerbation (C-AE) of COPD. C-AE patients had similar rate of treatment failure compared with simple acute exacerbation (S-AE) of COPD (31.1% vs. 27%; p = 0.63). There were no differences regarding the length of stay in hospital, ICU admission rate, and 30-day, 90-day, and 1-year readmission rate. C-AE patients had faster declined measures on time to death (691.6 ± 430 days vs. 998.1 ± 355 days; p = 0.02). In the multivariate analysis, after adjusting for comorbidity, lung function and previous treatment, C-AE patients had a significant higher mortality at one year (Odds Ratio [OR] = 4.9 (Confidence Interval [CI] 95%: 1.16-21); p = 0.031). Conclusions In hospitalized patients with an AECOPD, CTS classification, according to the presence of risk factors, was not associated with worse short-term clinical outcomes although it is related with long-term mortality. 

  7. Pilot evaluation of a multidisciplinary, medically supervised, nonsurgical weight loss program on the severity of low back pain in obese adults.

    Science.gov (United States)

    Roffey, Darren M; Ashdown, Lynn C; Dornan, Holly D; Creech, Michael J; Dagenais, Simon; Dent, Robert M; Wai, Eugene K

    2011-03-01

    Low back pain (LBP) is a prevalent and costly condition. Although its etiology is largely unknown, a link to obesity is suspected, and weight loss programs are often recommended to obese patients with LBP. To assess the efficacy of a pilot, multidisciplinary, medically supervised, nonsurgical weight loss program involving meal replacement, caloric restriction, education, exercise, and group therapy at reducing the severity of LBP in obese adults. Pilot prospective cohort study. A total of 46 obese adults (mean body mass index [BMI] 44.7±7.6 kg/m2) referred to an academic hospital for a multidisciplinary, medically supervised, nonsurgical weight loss program who reported LBP were enrolled. The severity of LBP was measured using the Numerical Pain Scale (NPS) and modified Oswestry Disability Index (ODI) at baseline (Week 1), Week 14, and Week 53; weight, BMI, dietary adherence, and physical activity levels were also measured. The 52-week weight loss program was administered by a team of physicians, dietitians, exercise specialists, and nurses and included liquid meal replacements for 12 weeks, followed by supervised caloric restriction diets for 13 weeks. Participants also attended weekly group therapy and educational meetings for the first 26 weeks, after which they were instructed to continue caloric restriction diets, engage in 60 to 90 minutes of daily physical activity, and attend monthly group meetings for an additional 26 weeks. At baseline, NPS was mild in 61% (n=28), moderate in 30% (n=14), and severe in 9% (n=4), whereas ODI was moderate in 48% (n=22), severe in 17% (n=8), and crippling in 4% (n=2). At Week 14 (n=42; 92% follow-up), there were significant improvements in NPS (p=.001) and ODI (p=.0005), and significant weight loss (pobese patients with LBP improved both pain and function. Copyright © 2011 Elsevier Inc. All rights reserved.

  8. Classification of the severity of diabetic neuropathy: a new approach taking uncertainties into account using fuzzy logic

    Directory of Open Access Journals (Sweden)

    Andreja P. Picon

    2012-01-01

    Full Text Available OBJECTIVE: This study proposes a new approach that considers uncertainty in predicting and quantifying the presence and severity of diabetic peripheral neuropathy. METHODS: A rule-based fuzzy expert system was designed by four experts in diabetic neuropathy. The model variables were used to classify neuropathy in diabetic patients, defining it as mild, moderate, or severe. System performance was evaluated by means of the Kappa agreement measure, comparing the results of the model with those generated by the experts in an assessment of 50 patients. Accuracy was evaluated by an ROC curve analysis obtained based on 50 other cases; the results of those clinical assessments were considered to be the gold standard. RESULTS: According to the Kappa analysis, the model was in moderate agreement with expert opinions. The ROC analysis (evaluation of accuracy determined an area under the curve equal to 0.91, demonstrating very good consistency in classifying patients with diabetic neuropathy. CONCLUSION: The model efficiently classified diabetic patients with different degrees of neuropathy severity. In addition, the model provides a way to quantify diabetic neuropathy severity and allows a more accurate patient condition assessment.

  9. Classification of the severity of diabetic neuropathy: a new approach taking uncertainties into account using fuzzy logic

    Science.gov (United States)

    Picon, Andreja P; Ortega, Neli R S; Watari, Ricky; Sartor, Cristina; Sacco, Isabel C N

    2012-01-01

    OBJECTIVE: This study proposes a new approach that considers uncertainty in predicting and quantifying the presence and severity of diabetic peripheral neuropathy. METHODS: A rule-based fuzzy expert system was designed by four experts in diabetic neuropathy. The model variables were used to classify neuropathy in diabetic patients, defining it as mild, moderate, or severe. System performance was evaluated by means of the Kappa agreement measure, comparing the results of the model with those generated by the experts in an assessment of 50 patients. Accuracy was evaluated by an ROC curve analysis obtained based on 50 other cases; the results of those clinical assessments were considered to be the gold standard. RESULTS: According to the Kappa analysis, the model was in moderate agreement with expert opinions. The ROC analysis (evaluation of accuracy) determined an area under the curve equal to 0.91, demonstrating very good consistency in classifying patients with diabetic neuropathy. CONCLUSION: The model efficiently classified diabetic patients with different degrees of neuropathy severity. In addition, the model provides a way to quantify diabetic neuropathy severity and allows a more accurate patient condition assessment. PMID:22358240

  10. 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 of the r...

  11. The correct prednisone starting dose in polymyalgia rheumatica is related to body weight but not to disease severity

    Directory of Open Access Journals (Sweden)

    Montecucco Carlomaurizio

    2011-05-01

    Full Text Available Abstract Background the mainstay of treatment of polymyalgia rheumatica (PMR is oral glucocorticoids, but randomized controlled trials of treatment are lacking. As a result, there is no evidence from controlled studies on the efficacy of different initial doses or glucocorticoid tapering. The aim of this study is to test if 12.5 mg prednisone/day is an adequate starting dose in PMR and to evaluate clinical predictors of drug response. Methods 60 consecutive PMR patients were treated with a starting dose of 12,5 mg/day prednisone. Clinical, laboratory, and, in a subset of 25 patients, ultrasonographic features were recorded as possible predictors of response to prednisone. Remission was defined as disappearance of at least 75% of the signs and symptoms of PMR and normalization of ESR and CRP within the first month, a scenario allowing steroid tapering. Results 47/60 (78.3% patients responded to 12.5 mg of prednisone after a mean interval of 6.6 ± 5.2 days. In univariate analysis, body weight and gender discriminated the two groups. In multivariate analysis, the only factor predicting a good response was low weight (p = 0.004; the higher response rate observed in women was explained by their lower weight. The mean prednisone dose per kg in the responders was 0.19 ± 0.03 mg in comparison with 0.16 ± 0.03 mg for non responders (p = 0.007. Conclusions 12.5 mg prednisone is a sufficient starting dose in ¾ of PMR patients. The main factor driving response to prednisone in PMR was weight, a finding that could help in the clinical care of PMR patients and in designing prospective studies of treatment. Trial Registration ClinicalTrials.gov: NCT01169597

  12. 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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Ipach, Ingmar; Mittag, F.; Sachsenmaier, S.; Kluba, T. [Tuebingen Univ. (Germany). Dept. of Orthopaedic Surgery; Heinrich, P. [Klinikum rechts der Isar der Technischen Univ. Muenchen (Germany). Inst. fuer Medizinische Statistik und Epidemiologie

    2011-04-15

    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.)

  14. Weighted Clustering

    CERN Document Server

    Ackerman, Margareta; Branzei, Simina; Loker, David

    2011-01-01

    In this paper we investigate clustering in the weighted setting, in which every data point is assigned a real valued weight. We conduct a theoretical analysis on the influence of weighted data on standard clustering algorithms in each of the partitional and hierarchical settings, characterising the precise conditions under which such algorithms react to weights, and classifying clustering methods into three broad categories: weight-responsive, weight-considering, and weight-robust. Our analysis raises several interesting questions and can be directly mapped to the classical unweighted setting.

  15. Metabolic and Nutritional Needs to Normalize Body Mass Index by Doubling the Admission Body Weight in Severe Anorexia Nervosa

    Science.gov (United States)

    Gentile, Maria Gabriella; Lessa, Chiara; Cattaneo, Marina

    2013-01-01

    Anorexia nervosa exhibits one of the highest death rates among psychiatric patients and a relevant fraction of it is derived from undernutrition. Nutritional and medical treatment of extreme undernutrition present two very complex and conflicting tasks: (1) to avoid “refeeding syndrome” caused by a too fast correction of malnutrition; and (2) to avoid “underfeeding” caused by a too cautious refeeding. To obtain optimal treatment results, the caloric intake should be planned starting with indirect calorimetry measurements and electrolyte abnormalities accurately controlled and treated. This article reports the case of an anorexia nervosa young female affected by extreme undernutrition (BMI 9.6 kg/m2) who doubled her admission body weight (from 22.5 kg to 44 kg) in a reasonable time with the use of enteral tube feeding for gradual correction of undernutrition. Refeeding syndrome was avoided through a specialized and flexible program according to clinical, laboratory, and physiological findings. PMID:23645991

  16. 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.

  17. 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.

  18. EFFECT OF SEVERAL STRUCTURES OF CONTEMPORARY GROUPS ON ESTIMATES OF (COVARIANCE AND GENETIC PARAMETERS FOR WEANING WEIGHT IN NELLORE CATTLE

    Directory of Open Access Journals (Sweden)

    Lillian Pascoa

    2013-06-01

    Full Text Available We used actual and adjusted weights to 120 d and 210 d of age of 72,731 male and female Nellore calves born in 40 PMGRN - Nellore Brazil herds from 1985 to 2005 aiming to compare the effect of different definitions of contemporary groups on estimates of (covariance and genetic parameters. Four models, each one with a different structure of contemporary group (CG, were compared using the Akaike Information Criterion (AIC, the Bayesian Information Criterion (BIC, and the Consistent Akaike Information Criterion (CAIC. (Covariance estimates were obtained using a derivative-free restricted maximum likelihood procedure. Estimates of (covariances and genetic parameters were similar for the four models considered. However, the BIC and CAIC indicated that the most appropriate model for this Nellore population was the one that considered CG to be random, and sex of calf to be fixed and separate from CG, in which CG was defined as the group of calves born in the same herd, year, season of birth (trimester, and undergone the same management.

  19. 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.

  20. Moderate Weight Reduction in an Outpatient Obesity Intervention Program Significantly Reduces Insulin Resistance and Risk Factors for Cardiovascular Disease in Severely Obese Adolescents

    Directory of Open Access Journals (Sweden)

    J. Grulich-Henn

    2011-01-01

    Full Text Available Background. Metabolic risk factors like insulin resistance and dyslipidemia are frequently observed in severly obese children. We investigated the hypothesis that moderate weight reduction by a low-threshold intervention is already able to reduce insulin resistance and cardiovascular risk factors in severely obese children. Methods. A group of 58 severely obese children and adolescents between 8 and 17 years participating in a six-month-long outpatient program was studied before and after treatment. The program included behavioral treatment, dietary education and specific physical training. Metabolic parameters were measured in the fasting state, insulin resistance was evaluated in an oral glucose tolerance test. Results. Mean standard deviation score of the body mass index (SDS-BMI in the study group dropped significantly from +2.5 ± 0.5 to 2.3 ± 0.6 (P<0.0001 after participation in the program. A significant decrease was observed in HOMA (6.3 ± 4.2 versus 4.9 ± 2.4, P<0.03, and in peak insulin levels (232.7 ± 132.4 versus 179.2 ± 73.3 μU/mL, P<0.006. Significant reductions were also observed in mean levels of hemoglobin A1c, total cholesterol and LDL cholesterol. Conclusions. These data demonstrate that already moderate weight reduction is able to decrease insulin resistance and dyslipidemia in severely obese children and adolescents.

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

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    Włodzimierz Łuczyński

    2014-01-01

    Full Text Available 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 children with T1DM included female gender (P=0.0003, poor metabolic control (P=0.0001, and carriage of the A allele of the FTO rs9939609 gene (P=0.02. Conclusion. Our research indicates, when assessing, the risk of overweight and obesity carriage of the A allele in the rs9939609 site of the FTO gene adds to that of female gender and poor metabolic control. This trial is registered with ClinicalTrials.gov (NCT01279161.

  2. 几种不同减肥方法及其效果评价%Evaluation of several ways for weight loss

    Institute of Scientific and Technical Information of China (English)

    彭莉

    2001-01-01

    The main way of weight loss is diet control, exercise, drug administration and behavior modification. And each way has its different content and effect. This paper summarized different content and effect of these several ways of weight loss.%有氧运动、饮食节制、药物疗法、行为矫正法是目前常用的几种减肥方法,其减肥作用各有优劣。文章综述了以上几种不同减肥方法的内容与效果,认为行为矫正疗法才是长期有效的综合性减肥方法。

  3. Effects of Age, Sex, Body Weight, and Quantity of Alcohol Consumption on Occurrence and Severity of Alcoholic Hepatitis.

    Science.gov (United States)

    Liangpunsakul, Suthat; Puri, Puneet; Shah, Vijay H; Kamath, Patrick; Sanyal, Arun; Urban, Thomas; Ren, Xiaowei; Katz, Barry; Radaeva, Svetlana; Chalasani, Naga; Crabb, David W

    2016-12-01

    Only a minority of heavy drinking individuals develop alcoholic hepatitis (AH), for unclear reasons. We analyzed data from the Translational Research and Evolving Alcoholic Hepatitis Treatment cohort, consisting of subjects who drink heavily with normal results from liver tests (controls) and patients with AH. We examined risk factors for the development of AH including body mass index (BMI), drinking pattern and quantity, and sex. We compared data from 145 patients with AH and 124 controls based on BMI when they joined the cohort; groups were matched for sex and race. Drinking patterns were assessed using the timeline followback method, the Alcohol Use Disorders Identification Test, and the National Institute of Alcohol Abuse and Alcoholism 6-question survey. We performed univariable and multivariable analyses to assess the effects of these factors and their interaction in increasing the risk for AH. We also explored the association between PNPLA3 variants and AH. Cases with AH were older (47 vs 44 y; P = .03). For nearly all measures of quantity of alcohol consumed or frequency of binge drinking, controls drank more heavily than cases with AH. We did not find an association between BMI, sex, drinking patterns, and the presence of AH. Age and BMI were independent predictors for the severity of AH. When we analyzed cases and controls of European ancestry, the PNPLA3 single-nucleotide polymorphism rs738409 was associated with risk for AH (odds ratio, 1.89; P = .007). Compared with heavy drinkers without liver disease, subjects with AH consumed lower levels of alcohol and had less binge drinking, suggesting an increased sensitivity to the toxic effects of alcohol. The risk for AH may be associated with the PNPLA3 rs738409 polymorphism. Copyright © 2016 AGA Institute. Published by Elsevier Inc. All rights reserved.

  4. 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.

  5. Cocaine use disorder prevalence: From current DSM-IV to proposed DSM-5 diagnostic criteria with both a two and three severity level classification system.

    Science.gov (United States)

    Proctor, Steven L; Kopak, Albert M; Hoffmann, Norman G

    2014-06-01

    This article presents a secondary analysis from a study investigating the compatibility of the current DSM-IV and previously proposed DSM-5 cocaine use disorder (CUD) criteria (S. L. Proctor, A. M. Kopak, & N. G. Hoffmann, 2012, Compatibility of current DSM-IV and proposed DSM-5 diagnostic criteria for cocaine use disorders. Addictive Behaviors, 37, 722-728). The current analyses examined the compatibility of the current DSM-IV and two sets of proposed DSM-5 diagnostic criteria for CUDs among adult male inmates (N = 6,871) recently admitted to the Minnesota Department of Corrections state prison system from 2000-2003. Initially proposed DSM-5 criteria (DSM-5.0) featured only two diagnostic designations (i.e., moderate and severe). A subsequent revision (DSM-5.1) included the addition of a mild designation and required a greater number of positive findings for the severe designation. A computer-prompted structured diagnostic interview was administered to all inmates as part of routine clinical assessments. The past 12-month prevalence of DSM-IV CUDs was 12.70% (Abuse, 3.78%, Dependence, 8.92%), while 10.98% met past 12-month DSM-5.1 criteria for a CUD (Mild [MiCUD], 1.72%; Moderate [MCUD], 1.12%; and Severe [SCUD], 8.14%). The vast majority of those with no diagnosis (99.6%) continued to have no diagnosis, and most of those with a dependence diagnosis (91.2%) met SCUD criteria of the proposed DSM-5.1. Most of the variation in DSM-5.1 diagnostic classifications was accounted for by those with a current abuse diagnosis. DSM-5.0 MCUD cases were most affected when DSM-5.1 criteria were applied. The proposed diagnostic changes might translate to reduced access to treatment for those individuals evincing symptoms consistent with DSM-IV cocaine abuse.

  6. 粗糙集理论在采空区分级指标权重确定中的应用%Application of Rough Set Theory (RST) in Weight Determination for the Classification Index of Underground Goaf

    Institute of Scientific and Technical Information of China (English)

    杨金林; 李夕兵; 周子龙; 陈红江

    2011-01-01

    为了准确计算采空区各个分级指标的权重,应用粗糙集理论对原始数据挖掘,将权重确定问题转化为粗糙集中属性重要性问题,通过计算分级指标与评判结果的粗糙依赖度来确定分级指标的权重.该方法克服了传统权重确定方法的主观性,从而提高了采空区分级的精度.通过广东大宝山采空区实例说明该方法合理、有效,为优化与改进采空区分级指标体系提供了合理的依据.%In order to compute the weight factors of classification index for underground goaf accurately, rough sets theory is used to analyze the raw data, the significance of attributes among rough sets is estimated instead of weight determination. Weight factor is determined by calculating rough dependability between indexes and appraisement results. The approach overcomes the subjectivity in traditional weight determination method and improves the precision of underground goal classification. It is reasonable for optimizing algorithm of underground goaf classification index system. Taking underground goaf in Dabaoshan Mine as an example, this new method proves to be effective and rational.

  7. 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

  8. Derivation of a T2-weighted MRI total colonic inflammation score (TCIS) for assessment of patients with severe acute inflammatory colitis - a preliminary study

    Energy Technology Data Exchange (ETDEWEB)

    Hafeez, Rehana; Boulos, Paul [University College London Hospitals NHS Trust, Department of Surgery, London (United Kingdom); Punwani, Shonit; Halligan, Steve [University College London, Centre for Medical Imaging, London (United Kingdom); University College London Hospitals NHS Trust, Department of Specialist X-ray, Level 2 podium, London (United Kingdom); Pendse, Doug [University College London, Centre for Medical Imaging, London (United Kingdom); Bloom, Stuart [University College London Hospitals NHS Trust, Department of Gastroenterology, London (United Kingdom); Taylor, Stuart A. [University College London, Centre for Medical Imaging, London (United Kingdom); University College London Hospitals NHS Trust, Department of Specialist X-ray, Level 2 podium, London (United Kingdom)

    2011-02-15

    To derive an MRI score for assessing severity, therapeutic response and prognosis in acute severe inflammatory colitis. Twenty-one patients with acute severe colitis underwent colonic MRI after admission and again (n = 16) after median 5 days of treatment. Using T2-weighted images, two radiologists in consensus graded segmental haustral loss, mesenteric and mural oedema, mural thickness, and small bowel and colonic dilatation producing a total colonic inflammatory score (TCIS, range 6-95). Pre- and post-treatment TCIS were compared, and correlated with CRP, stool frequency, and number of inpatient days (therapeutic response marker). Questionnaire assessment of patient worry, satisfaction and discomfort graded 1 (bad) to 7 (good) was administered Admission TCIS correlated significantly with CRP (Kendall's tau=0.45, 95% confidence interval [CI] 0.11-0.79, p = 0.006), and stool frequency (Kendall's tau 0.39, 95% CI 0.14-0.64, p = 0.02). TCIS fell after treatment (median [22 range 15-31]) to median 20 [range 8-25], p = 0.01. Admission TCIS but not CRP or stool frequency was correlated with length of inpatient stay (Kendall's tau 0.40, 95% CI 0.11-0.69, p = 0.02). Patients reported some discomfort (median score 4) during MRI. MRI TCIS falls after therapy, correlates with existing markers of disease severity, and in comparison may better predict therapeutic response. (orig.)

  9. 基于加权聚类质心的 SVM 不平衡分类方法%Support vector machine imbalanced data classification based on weighted clustering centroid

    Institute of Scientific and Technical Information of China (English)

    2013-01-01

    Classification of imbalanced data has become a research hot topic in machine learning .Traditional classi-fication algorithms assume that different classes have balanced distribution or equal misclassification cost , thus, making it hard to get ideal result of classifications .A support vector machine (SVM) classification method based on weighted clustering centroid was proposed in this paper .First, unsupervised clustering was applied to the positive and negative samples respectively to extract the clustering centroid of each clustering , which was represented the most in compactness of the clustering sample .Next, all clustering centroids formed a new set of balance training .In order to minimize the information loss during clustering , each clustering centroid was associated with a weight factor that was defined proportional to the number of samples of the class .Finally, all clustering centroids and weight fac-tors participated in the training of the improved SVM model .Experimental results show that the proposed method can make the sample selected from model train sets more typical and improve the classification performance better than other sampling techniques for dealing with imbalanced data .%  不平衡数据分类是机器学习研究的热点问题,传统分类算法假定不同类别具有平衡分布或误分代价相同,难以得到理想的分类结果。提出一种基于加权聚类质心的SVM分类方法,在正负类样本上分别进行聚类,对每个聚类,用聚类质心和权重因子代表聚类内样本分布和数量,相等类别数量的质心和权重因子参与SVM模型训练。实验结果表明,该方法使模型的训练样本具有较高的代表性,分类性能与其他采样方法相比得到了提升。

  10. 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

  11. 一种基于改进的权值调整技术数据源分类算法研究%Classification of Deep Web data sources based on weight adjustment technique

    Institute of Scientific and Technical Information of China (English)

    周晓庆; 肖顺文; 肖建琼; 罗兴贤

    2012-01-01

    针对传统的搜索引擎无法正确搜索到Deep Web中隐藏的海量信息,对Web数据库的分类是通向Web数据库分类集成和检索的关键步骤.提出了一种基于权值调整技术的Deep Web数据库分类方法,首先从网页表单中提取特征;然后对这些特征使用一种新的权重计算方法进行估值;最后利用朴素贝叶斯分类器对Web数据库进行分类.实验表明,这种分类方法经过少量样本训练后,就能达到很好的分类效果,并且随着训练样本的增加,该分类器的性能保持稳定,准确率、召回率都在很小的范围内波动.%The traditional search engine is unable to correct search for the magnanimous information in Deep Web hides. The Web database' s classification is the key step which integrates with the Web database classification and retrieves. This paper proposed a kind of classification of Deep Web data sources based on weight adjustment technique, which, used a new weight adjustment method to valuate the weight of feature extracted from the homepage form, and finally used the simple Bayes sorter to classify the Web database. The experiment indicates that after this taxonomic approach undergoes few sample training, it can achieve the very good classified effect, and along with training sample' s increase, this classifier' s performance maintains stable and the rate of accuracy and the recalling rate fluctuate in the very small scope.

  12. A systematic review of quality of life and weight gain-related issues in patients treated for severe and persistent mental disorders: focus on aripiprazole

    Directory of Open Access Journals (Sweden)

    Salvatore Gentile

    2009-02-01

    Full Text Available Salvatore GentileDepartment of Mental Health, ASL Salerno 1, ItalyAbstract: Aripiprazole is a relatively novel second-generation antipsychotic belonging to the chemical class of benzisoxazole derivatives and is characterized by a unique pharmacological profile which suggests that the drug acts as a dopamine-serotonin system stabilizer. Whereas all previously available antipsychotics are antagonists at D2 receptors, aripiprazole is the only available partial agonist at these receptors. Thus, it has been suggested that aripiprazole could be associated with a relatively neutral impact on bodyweight, possibly reducing risks of a detrimental impact on the quality of life that often complicates management for a large number of patients diagnosed with severe and persistent mental disorders (SPMDs treated chronically with antipsychotic medications. However, data from short- and long-term reviewed studies indicate that the prevalence rate of clinically relevant weight gain during therapy with this drug is similar to that occurring during treatments with other antipsychotic agents, either typical or atypical. Moreover, information on the impact of aripiprazole therapy on the quality of life of patients diagnosed with SPMDs is scarce and characterized by conflicting results. Given these results, further, large, well-designed studies are needed before confirming potential advantages of aripiprazole over first-generation antipsychotics and other SGAs.Keywords: aripiprazole, effectiveness, quality of life, safety, weight gain

  13. Locomotor training using body-weight support on a treadmill in conjunction with ongoing physical therapy in a child with severe cerebellar ataxia.

    Science.gov (United States)

    Cernak, Kristin; Stevens, Vicki; Price, Robert; Shumway-Cook, Anne

    2008-01-01

    This case report describes the effects of locomotor training using body-weight support (BWS) on a treadmill and during overground walking on mobility in a child with severe cerebellar ataxia who was nonambulatory. To date, no studies have examined the efficacy of this intervention in people with cerebellar ataxia. The patient was a 13-year-old girl who had a cerebellar/brainstem infarct 16 months before the intervention. Her long-term goal was to walk independently in her home with a walker. Locomotor training using a BWS system both on the treadmill and during overground walking was implemented 5 days a week for 4 weeks in a clinic. Locomotor training using BWS on a treadmill was continued 5 days a week for 4 months at home. Prior to training, she was able to take steps on her own with the help of another person, but did not take full weight on her feet or walk on a regular basis. At 6 months, she walked for household distances. Prior to training, her Pediatric Functional Independence Measure scores were 3 (moderate assistance) for all transfers, 2 (maximal assistance) for walking, and 1 (total assistance) for stairs. At 6 months, her scores were 6 (modified independence) for transfers, 5 (supervision) for walking, and 4 (minimal assistance) for stairs. Prior to training, she was unable to take independent steps during treadmill walking; at 6 months, all of her steps were unassisted. Locomotor training using BWS on a treadmill in conjunction with overground gait training may be an effective way to improve ambulatory function in individuals with severe cerebellar ataxia, but the intensity and duration of training required for functionally significant improvements may be prolonged.

  14. Comparison of the Child-Turcotte-Pugh classification and the model for end-stage liver disease score as predictors of the severity of the systemic inflammatory response in patients undergoing living-donor liver transplantation.

    Science.gov (United States)

    Hong, Sang-Hyun; Kim, Jeong-Eun; Cho, Mi-La; Heo, Yu-Jung; Choi, Jong-Ho; Choi, Jung-Hyun; Lee, Jaemin

    2011-10-01

    The aim of this study was to evaluate and compare the Child-Turcotte-Pugh (CTP) classification system and the model for end-stage liver disease (MELD) score in predicting the severity of the systemic inflammatory response in living-donor liver transplantation patients. Recipients of liver graft were allocated to a recipient group (n = 39) and healthy donors to a donor group (n = 42). The association between the CTP classification, the MELD scores and perioperative cytokine concentrations in the recipient group was evaluated. The pro-inflammatory cytokines measured included interleukin (IL)-1β, IL-6, and tumor necrosis factor (TNF)-α; the anti-inflammatory cytokines measured included IL-10 and IL-4. Cytokine concentrations were quantified using sandwich enzyme-linked immunoassays. The IL-6, TNF-α, and IL-10 concentrations in the recipient group were significantly higher than those in healthy donor group patients. All preoperative cytokine levels, except IL-6, increased in relation to the severity of liver disease, as measured by the CTP classification. Additionally, all cytokine levels, except IL-6, were significantly correlated preoperatively with MELD scores. However, the correlations diminished during the intraoperative period. The CTP classification and the MELD score are equally reliable in predicting the severity of the systemic inflammatory response, but only during the preoperative period.

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

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Ah Yeong; Kim, Young Kon; Lee, Min Woo; Park, Min Jung; Hwang, Jiyoung; Lee, Mi Hee; Lee, Jae Won [Dept. of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan Univ. School of Medicine, Seoul (Korea, Republic of)], e-mail: jmyr@dreamwiz.com

    2012-10-15

    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. 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

  17. 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.

  18. 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

  19. 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.

  20. [Direct medical costs of (severe) obesity: a bottom-up assessment of over- vs. normal-weight adults in the KORA-study region (Augsburg, Germany)].

    Science.gov (United States)

    von Lengerke, T; Reitmeir, P; John, J

    2006-02-01

    To estimate and compare direct medical costs of illness of German adults in different BMI-groups and different degrees of obesity. In a sub-sample (n = 947) of the KORA-Survey S4 1999/2001, a cross-sectional health survey of the adult population in the Augsburg region (Germany; age: 25-74), visits to physicians, receipt and purchase of drugs, and inpatient days in hospital were assessed over half a year. Body mass index (BMI in kg/m(2)) was assessed anthropometrically. Respondents in normal weight (18.5 or = 35) range were compared in their costs of illness via analyses of covariance and regression analyses based on generalized linear models. Physician visits and inpatient days were evaluated as recommended by the Working Group "Methods in Health Economic Evaluation", and drugs by actual costs. Sex, age, socio-economic status (Helmert-Index), sickness fund (statutory vs. private), and place of residence (Augsburg City vs. District of Augsburg or Aichach-Friedberg) were adjusted for. While respondents with moderate obesity statistically did not differ significantly in their direct medical costs from those in normal weight or pre-obese range (1,080.14 euro vs. 847.60 euro and 830.59 euro; for users of care: 1,215.55 euro vs. 993.18 euro and 1,003.23 euro [all estimates adjusted and per annum]), those with severe obesity had significantly higher costs (2,572.19 euro; for users of care: 2,964.87 euro). Sub-analyses for individual parameters of health care use revealed that this pattern is largely due to inpatient days in hospital and receipt/purchase of drugs only available on prescription. On average, results indicate excess direct medical costs primarily in people with severe, and less with moderate obesity. In particular, they underline the need to distinguish moderate vs. severe obesity (classes 1 vs. 2-3) in health economics and health services research.

  1. Sample cutting and weighting method in text classification based on posi-tion%基于位置的文本分类样本剪裁及加权方法

    Institute of Scientific and Technical Information of China (English)

    刘海峰; 刘守生; 苏展

    2015-01-01

    k近邻方法是文本分类中广泛应用的方法,对其性能的优化具有现实需求。使用一种改进的聚类算法进行样本剪裁以提高训练样本的类别表示能力;根据样本的空间位置先后实现了基于类内和类间分布的样本加权;改善了k近邻算法中的大类别、高密度训练样本占优现象。实验结果表明,提出的改进文本加权方法提高了分类器的分类效率。%K nearest neighbor method is widely used in text classification method. There is the real need of improving the algorithm performance. It uses an improved clustering algorithm for sample cut to improve training sample category repre-sentation capability. According to the spatial location of the sample, it realizes the sample weighting based on class inner and class between. It improves the phenomenon that categories, high density of training samples have the advantage in k nearest neighbor algorithm. The experimental result shows that the improved text weighted method improves the classifi-cation efficiency.

  2. 基于组合赋权的难采储量模糊分类%Fuzzy Classification of Difficult Recoverable Reserves Based on Combination weighting approach

    Institute of Scientific and Technical Information of China (English)

    李志; 翁克瑞; 杨娟

    2013-01-01

    选取两个效果指标,结合模糊C均值算法和组合赋权法实现难采储量的分类.首先基于效果指标运用模糊C均值算法自动搜索储量的最佳类别,再利用主客观赋权偏差最小的思想,构建组合赋权模型,确定属性指标的权重,并计算储量效益指标值,结合模糊C均值结果判别难采储量类别.最后以大庆某油田为实例,对其难采储量进行了分类,有效指导难采储量滚动开发决策.%This paper selected two effectiveness indicators,combined with Fuzzy C-Means clustering algorithm (FCM) and combination weighting approach to classify difficult recoverable reserves.First use FCM to automatically search for the optimal category number of reserves based on effectiveness indicators.And then establish a combination weighting model based on the minimal deviation between subjective weighting method and objective weighting method,which was used for computing the attributes' weighting.Multiply the weighting by the corresponding attributes'value to judge the categories that blocks belonged to,according to the result of FCM.Finally take the case of an oil field in the 10th Oil Production Plant of PetroChina Daqing Oilfield LLC,and evaluate the recoverable reserves,which conducts the rolling development of recoverable reserves.

  3. Food Consumption Patterns in Mediterranean Adolescents: Are There Differences between Overweight and Normal-Weight Adolescents?

    Science.gov (United States)

    Yannakoulia, Mary; Brussee, Sandra E.; Drichoutis, Andreas C.; Kalea, Anastasia Z.; Yiannakouris, Nikolaos; Matalas, Antonia-Leda; Klimis-Zacas, Dorothy

    2012-01-01

    Objective: To quantify food consumption (based on food group classification) during several time periods in a sample of adolescents and to identify potential differences in food patterns between normal-weight and overweight participants. Design: Cross-sectional study. Participants were classified as normal weight and overweight/obese. Dietary…

  4. Food Consumption Patterns in Mediterranean Adolescents: Are There Differences between Overweight and Normal-Weight Adolescents?

    Science.gov (United States)

    Yannakoulia, Mary; Brussee, Sandra E.; Drichoutis, Andreas C.; Kalea, Anastasia Z.; Yiannakouris, Nikolaos; Matalas, Antonia-Leda; Klimis-Zacas, Dorothy

    2012-01-01

    Objective: To quantify food consumption (based on food group classification) during several time periods in a sample of adolescents and to identify potential differences in food patterns between normal-weight and overweight participants. Design: Cross-sectional study. Participants were classified as normal weight and overweight/obese. Dietary…

  5. SVM加权学习下的机载LiDAR数据多元分类研究%Aerial LiDAR Data Classification Using Weighted Support Vector Machines

    Institute of Scientific and Technical Information of China (English)

    吴军; 刘荣; 郭宁; 刘丽娟

    2013-01-01

    This paper presents our research on classifying scattered 3D aerial LiDAR height data into ground, vegetable (trees) and man-made object (buildings) using improved Support Vector Machine algorithm. To this end, the most basic theory of SVM is first outlined and with the fact that features are differed in their contribution to identify certain class or classes simultaneously, Weighted Support Vector Machine (W-SVM) technique is developed for maximizing the "recognition" capacity of SVM features in classifying scattered 3D LiDAR height data. Second, we give a proof that the implement of W-SVM is equal to the features normalization multiplied by one weight that indicates feature's contribution to certain class or multi-class as a whole. The weight calculation for each feature is discussed as well. Third, Based on W-SVM technique, one 1AAA1 solution to multi-class classification is proposed by integration "one against one" and "one against all" solution together. Finally, the experiment of classifying LiDAR data with presented technique is presented and shows encouraging improvement classification accuracy, compared to tradition SVM technique. Valuable conclusions are given as well.%基于支持向量机统计学习分类过程中不同特征对分类结果贡献存在差异的问题,提出了支持向量机加权学习下的训练、分类新方法,以实现对城区机载LiDAR数据多元分类(地面、树木、建筑),并对特征矢量加权归一化、特征权重计算以及该方式下多元分类策略的建立进行了讨论,实验证明了该方法的有效性.

  6. Mode of delivery and antenatal steroids and their association with survival and severe intraventricular hemorrhage in very low birth weight infants.

    Science.gov (United States)

    Hübner, M E; Ramirez, R; Burgos, J; Dominguez, A; Tapia, J L

    2016-10-01

    To determine whether CS delivery and receipt of antenatal steroids (ANS) in vertex-presenting singletons with a gestational age (GA) between 24 and 30 weeks is associated with improved survival and improved severe intraventricular hemorrhage (sIVH)-free survival. Multicenter cohort, retrospective analysis of prospectively collected data. Vertex-presenting singletons newborns with GA 24 to 30 weeks, birth weight between 500 and 1500 g, without major congenital malformations, born between 2001 and 2011 at Neocosur centers were included. Four thousand three hundred and eighty-six infants fulfilled inclusion criteria: 45.8% were delivered vaginally and 54.2% by cesarean section (CS). Newborns delivered vaginally received less ANS, had lower GA, Apgar scores and a lower incidence of survival and sIVH-free survival (P<0.001). Newborns with better survival were those with ANS, independent of mode of delivery. At 24 to 25 weeks GA, increased survival and sIVH-free survival were associated with ANS and CS delivery, compared with those who received ANS and delivered vaginally. Among vertex-presenting singletons with GA 24 to 30 weeks, better survival and IVH-free survival were associated with ANS, independent of mode of delivery. In infants at 24 to 25 weeks gestation the combination of ANS/CS was associated with improvement in both outcomes.

  7. A Method of Text Sentiment Classification Based on Weighted Rough Membership%基于赋权粗糙隶属度的文本情感分类方法

    Institute of Scientific and Technical Information of China (English)

    王素格; 李德玉; 魏英杰

    2011-01-01

    Facing with promptly increasing reviews on the Web, it has been great challenge for information science and technology that how people effectively organize and process document data hiding large amounts of information to meet with particular needs. Text sentiment classification aims at developing some new theories and methods to automatically explore the sentiment orientation of a text by mining and analyzing subjective information in texts such as standpoint, view, attitude,mood, and so on. A method of text sentiment classification based on weighted rough membership is proposed in this paper. In the method, the model of text expression is established based on two-tuples attribute (feature, feature orientation intensity), by introducing feature orientation intensity into the method of vector space representation. An attribute discretization method is proposed based on the sentiment orientation sequence for feature selection unifying the discretization processing to depress data dimension. To utilize the feature orientation intensity, a weighted rough membership is defined for classifying new sentiment text. Compared with SVM classifier, on the reality car review corpus,the proposed method based on rough membership for text sentiment classification has the best performance after data being compressed in a certainty extent for text sentiment classification.%提出了基于赋权粗糙隶属度的文本情感分类方法.该方法将特征倾向强度引入到文本的向量空间表示法中,建立了基于二元组属性(特征,特征倾向强度)的文本表示模型.提出了基于情感倾向强度序的属性离散化方法,将特征选择寓于离散化过程,达到数据降维的目的.利用特征倾向强度,定义了赋权粗糙隶属度,用于新文本的情感分类.在真实汽车评论语料上,与支持向量机分类模型进行比较实验表明,基于赋权粗糙隶属度的文本情感分类方法在对数据进行一定程度的压缩后仍表现出较好的分类性能.

  8. Maternal weight change between 1 and 2 years postpartum: the importance of 1 year weight retention.

    Science.gov (United States)

    Lipsky, Leah M; Strawderman, Myla S; Olson, Christine M

    2012-07-01

    Pregnancy weight gain may lead to long-term increases in maternal BMI for some women. The objective of this study was to examine maternal body weight change 1y-2y postpartum, and to compare classifications of 2y weight retention with and without accounting for 1y-2y weight gain. Early pregnancy body weight (EPW, first trimester) was measured or imputed, and follow-up measures obtained before delivery, 1 year postpartum (1y) and 2 years postpartum (2y) in an observational cohort study of women seeking prenatal care in several counties in upstate New York (n = 413). Baseline height was measured; demographic and behavioral data were obtained from questionnaires and medical records. Associations of 1y-2y weight change (kg) and 1y-2y weight gain (≥2.25 kg) with anthropometric, socioeconomic, and behavioral variables were evaluated using linear and logistic regressions. While mean ± SE 1y-2y weight change was 0.009 ± 4.6 kg, 1y-2y weight gain (≥2.25 kg) was common (n = 108, 26%). Odds of weight gain 1y-2y were higher for overweight (OR(adj) = 2.63, CI(95%) = 1.43-4.82) and obese (OR(adj) = 2.93, CI(95%) = 1.62-5.27) women than for women with BMI change (β(adj) ± SE = -0.28 ± 0.04, P change were attenuated for women with higher early pregnancy BMI. Weight change 1y-2y was predicted primarily by an inverse relation with 1y weight retention. The high frequency of weight gain has important implications for classification of postpartum weight retention.

  9. Is the shock index based classification of hypovolemic shock applicable in multiple injured patients with severe traumatic brain injury?-an analysis of the TraumaRegister DGU(®).

    Science.gov (United States)

    Fröhlich, Matthias; Driessen, Arne; Böhmer, Andreas; Nienaber, Ulrike; Igressa, Alhadi; Probst, Christian; Bouillon, Bertil; Maegele, Marc; Mutschler, Manuel

    2016-12-12

    A new classification of hypovolemic shock based on the shock index (SI) was proposed in 2013. This classification contains four classes of shock and shows good correlation with acidosis, blood product need and mortality. Since their applicability was questioned, the aim of this study was to verify the validity of the new classification in multiple injured patients with traumatic brain injury. Between 2002 and 2013, data from 40 888 patients from the TraumaRegister DGU(®) were analysed. Patients were classified according to their initial SI at hospital admission (Class I: SI shock based on universally available parameters. Although the pathophysiology in TBI and Non TBI patients and early treatment methods such as the use of vasopressors differ, both groups showed an identical probability of recieving blood products within the respective SI class. Regardless of the presence of TBI, the classification of hypovolemic shock based on the SI enables a fast and reliable assessment of hypovolemic shock in the emergency department. Therefore, the presented study supports the SI as a feasible tool to assess patients at risk for blood product transfusions, even in the presence of severe TBI.

  10. Classification of Hard-to-Recover Reserves Based on FCM and Combination weighting approach%基于 FCM-组合赋权的难采储量分类

    Institute of Scientific and Technical Information of China (English)

    杨娟; 龚承柱; 诸克军

    2014-01-01

    Currently, the classification criterion of reserves are determined by the scope of the values of criteria such as geological attributes , reservoir phydical parameters and etc ., which require all attribute values of one block should be just right in the existing range of criteria , otherwise it would be difficult to divide the hard-to-re-cover reserves into different categories .To solve this problem , this paper combines with Fuzzy c-Means clustering algorithm(FCM)and combination weighting approach to classify hard-to-recover reserves.First, FCM is used to automatically search for the optimal category number of reserves based on effect indexes .Then , a combination weighting model is established based on the minimal error-sum of deviation of subjective weights and deviation of objective weights , which is used to compute the weights of attributes and the values of effect indexes .Finally, the categories that blocks belonge to is judged according to the result of FCM .To verify the validity of model , this paper applies it to the classification problem of hard-to-recover reserves from an oil field in the 10th Oil Pro-duction Plant of PetroChina Daqing Oilfield LLC , which would conduct the rolling development of hard-to-recover reserves .%目前储量的分类标准是通过划分指标值的范围来确定的,这就要求所有指标值恰好符合既定的指标范围,否则难以划分储量类别。为克服这一问题,本文结合模糊c-均值算法和组合赋权法实现难采储量的分类。首先基于效益指标运用模糊c-均值算法自动搜索储量的最佳类别,再利用主客观赋权偏差最小的思想,构建组合赋权模型,确定属性指标的权重,并计算储量效益指标值,结合模糊c-均值结果判别难采储量类别。最后以大庆某油田为实例,对其难采储量进行了分类,有效指导难采储量滚动开发决策。

  11. Impact of Severe Obesity and Weight Loss on Systolic Left Ventricular Function and Morphology: Assessment by 2-Dimensional Speckle-Tracking Echocardiography

    Directory of Open Access Journals (Sweden)

    Sevda Karimian

    2016-01-01

    Full Text Available Obesity is associated with an increased risk of heart failure. Little is known about the impact of dietary changes on the cardiac sequelae in obese patients. Twenty-one obese subjects underwent a 12-week low calorie fasting phase of a formula diet. Transthoracic two-dimensional speckle-tracking echocardiography was performed to obtain systolic left ventricular strain before and after weight loss. Body mass index decreased significantly from 38.6±6.2 to 31.5±5.3 kg/m2, and the total percentage fat loss was 19%. Weight reduction was associated with a reduction in blood pressure and heart rate. Left ventricular longitudinal global peak systolic strain was in the lower normal range (−18.7±3.2% before weight loss and was unchanged (−18.8±2.4% after 12 weeks on diet with substantial weight loss. Also, no significant change in global radial strain after weight loss was noted (41.1±22.0 versus 43.9±23.3, p=0.09. Left atrial and ventricular dimensions were in normal range before fasting and remained unchanged after weight loss. In our study obesity was associated with normal systolic left ventricular function. A 12-week low calorie diet with successful weight loss can reduce blood pressure and heart rate. Systolic left ventricular function and morphology were not affected by rapid weight reduction.

  12. Oral Administration of Faecalibacterium prausnitzii Decreased the Incidence of Severe Diarrhea and Related Mortality Rate and Increased Weight Gain in Preweaned Dairy Heifers.

    Directory of Open Access Journals (Sweden)

    Carla Foditsch

    Full Text Available Probiotics are a promising alternative to improve food animal productivity and health. However, scientific evidence that specific microbes can be used to benefit animal health and performance is limited. The objective of this study was to evaluate the effects of administering a live culture of Faecalibacterium prausnitzii to newborn dairy calves on subsequent growth, health, and fecal microbiome. Initially, a safety trial was conducted using 30 newborn bull calves to assess potential adverse effects of the oral and rectal administration of F. prausnitzii to neonatal calves. No adverse reactions, such as increased body temperature or heart and respiratory rates, were observed after the administration of the treatments. All calves survived the experimental period, and there was no difference in fecal consistency score, attitude, appetite or dehydration between the treatment groups. The rectal route was not an efficient practice while the oral route ensures that the full dose is administered to the treated calves. Subsequently, a randomized field trial was completed in a commercial farm with preweaned calves. A total of 554 Holstein heifers were assigned to one of two treatment groups: treated calves (FPTRT and non-treated calves (control. Treated calves received two oral doses of F. prausnitzii, one at treatment assignment (1st week and another one week later. The FPTRT group presented significantly lower incidence of severe diarrhea (3.1% compared with the control group (6.8%. Treated calves also had lower mortality rate associated with severe diarrhea (1.5% compared to control calves (4.4%. Furthermore, FPTRT calves gained significantly more weight, 4.4 kg over the preweaning period, than controls calves. The relative abundance of F. prausnitzii in the fecal microbiota was significantly higher in the 3rd and 5th weeks of life of FPTRT calves than of the control calves, as revealed by sequencing of the 16S rRNA gene. Our findings showed that oral

  13. Optimal Combination of Classification Algorithms and Feature Ranking Methods for Object-Based Classification of Submeter Resolution Z/I-Imaging DMC Imagery

    OpenAIRE

    Fulgencio Cánovas-García; Francisco Alonso-Sarría

    2015-01-01

    Object-based image analysis allows several different features to be calculated for the resulting objects. However, a large number of features means longer computing times and might even result in a loss of classification accuracy. In this study, we use four feature ranking methods (maximum correlation, average correlation, Jeffries–Matusita distance and mean decrease in the Gini index) and five classification algorithms (linear discriminant analysis, naive Bayes, weighted k-nearest neighbors,...

  14. 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....

  15. Weighted Combination of Conflicting Evidence Based on Evidence Classification%基于证据分类的加权冲突证据组合

    Institute of Scientific and Technical Information of China (English)

    王进花; 吴迪; 曹洁; 李军

    2013-01-01

    In order to combine highly conflicting evidence efficiently,a new evidence combination rule making use of evidence classfication was proposed based on triangular norm and discount factor analyse. First, utilizing average evidence distance and discount factor based on triangular norm, the evidence was classified into three categories: reliability, no conflict and conflict. The discounting factors of the former two categories of evidences were set to one, which keeps the evidence hold of the right hypothesis to a great extant and makes the fusion results focus onto the right hypothesis more strongly. Then the was improved evidence weight was obtained based on evidence distance, and the modified evidence was obtained by verifying the conflicting evidence according to the weighting rule in order to eliminate the conflict. Finally, according to the Dempster's rule, the modified evidence was combined. Numerical examples show the efficiency and rationality of the proposed approach.%为了有效融合高度冲突的证据,在三角模算子和折扣因子分析的基础上,提出了一种基于证据分类的冲突证据融合规则.采用基于3角模算子定义的平均证据距离与冲突因子将证据分成可信任证据、不冲突证据和冲突证据三类,并赋予可信任证据和不冲突证据折扣因子1,极大程度上保留了证据对正确假设的支持;然后基于证据距离定义了改进的证据权重,基于加权原则对冲突证据进行合成得到修正的证据体,从而消除证据间的冲突;最后利用Dempster规则完成证据组合.算法分析表明所提方法是合理有效的.

  16. 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.

  17. 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.

  18. Weight Management

    Science.gov (United States)

    ... Anger Weight Management Weight Management Smoking and Weight Healthy Weight Loss Being Comfortable in Your Own Skin Your Weight Loss Expectations & Goals Healthier Lifestyle Healthier Lifestyle Physical Fitness Food & Nutrition Sleep, Stress & Relaxation Emotions & Relationships HealthyYouTXT ...

  19. Using Simultaneous Prompting to Teach Restaurant Words and Classifications as Non-Target Information to Secondary Students with Moderate to Severe Disabilities

    Science.gov (United States)

    Smith, Bethany R.; Schuster, John W.; Collins, Belva; Kleinert, Harold

    2011-01-01

    This paper reviews selected literature pertaining to simultaneous prompting and the acquisition of non-target information for individuals with moderate to severe disabilities. The purpose of this review was to discuss the definition of non-target information (NTI) and the various places it can be embedded within an instructional trial. The…

  20. 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.

  1. [Classification of cardiomyopathy].

    Science.gov (United States)

    Asakura, Masanori; Kitakaze, Masafumi

    2014-01-01

    Cardiomyopathy is a group of cardiovascular diseases with poor prognosis. Some patients with dilated cardiomyopathy need heart transplantations due to severe heart failure. Some patients with hypertrophic cardiomyopathy die unexpectedly due to malignant ventricular arrhythmias. Various phenotypes of cardiomyopathies are due to the heterogeneous group of diseases. The classification of cardiomyopathies is important and indispensable in the clinical situation. However, their classification has not been established, because the causes of cardiomyopathies have not been fully elucidated. We usually use definition and classification offered by WHO/ISFC task force in 1995. Recently, several new definitions and classifications of the cardiomyopathies have been published by American Heart Association, European Society of Cardiology and Japanese Circulation Society.

  2. Current terminology and diagnostic classification schemes.

    Science.gov (United States)

    Okeson, J P

    1997-01-01

    This article reviews the current terminology and classification schemes available for temporomandibular disorders. The origin of each term is presented, and the classification schemes that have been offered for temporomandibular disorders are briefly reviewed. Several important classifications are presented in more detail, with mention of advantages and disadvantages. Final recommendations are provided for future direction in the area of classification schemes.

  3. Development of a combined system for identification and classification of adverse drug reactions: Alerts Based on ADR Causality and Severity (ABACUS).

    Science.gov (United States)

    Koh, Yvonne; Yap, Chun Wei; Li, Shu-Chuen

    2010-01-01

    Currently, adverse drug reaction (ADR) causality and severity are assessed using different systems but there is no standard method to combine the results. In this work, a combined ADR causality and severity assessment system, including an online version, was developed. Logical rules were defined to translate the score obtained from the system into three alert zones: green, amber, and red. The alert zones are useful for triaging ADR cases as they help define the seriousness of the ADR and the urgency of the responses required. This new scoring system may be useful for clinicians, investigators, and regulators seeking information on the likelihood of a drug causing an adverse reaction, and whether an adverse reaction is sufficiently dangerous for the drug to be withheld or undergo further investigation.

  4. Hierarchical discriminant manifold learning for dimensionality reduction and image classification

    Science.gov (United States)

    Chen, Weihai; Zhao, Changchen; Ding, Kai; Wu, Xingming; Chen, Peter C. Y.

    2015-09-01

    In the field of image classification, it has been a trend that in order to deliver a reliable classification performance, the feature extraction model becomes increasingly more complicated, leading to a high dimensionality of image representations. This, in turn, demands greater computation resources for image classification. Thus, it is desirable to apply dimensionality reduction (DR) methods for image classification. It is necessary to apply DR methods to relieve the computational burden as well as to improve the classification accuracy. However, traditional DR methods are not compatible with modern feature extraction methods. A framework that combines manifold learning based DR and feature extraction in a deeper way for image classification is proposed. A multiscale cell representation is extracted from the spatial pyramid to satisfy the locality constraints for a manifold learning method. A spectral weighted mean filtering is proposed to eliminate noise in the feature space. A hierarchical discriminant manifold learning is proposed which incorporates both category label and image scale information to guide the DR process. Finally, the image representation is generated by concatenating dimensionality reduced cell representations from the same image. Extensive experiments are conducted to test the proposed algorithm on both scene and object recognition datasets in comparison with several well-established and state-of-the-art methods with respect to classification precision and computational time. The results verify the effectiveness of incorporating manifold learning in the feature extraction procedure and imply that the multiscale cell representations may be distributed on a manifold.

  5. Predictors of mortality in pediatric trauma: experiences of a level 1 trauma center and an assessment of the International Classification Injury Severity Score (ICISS).

    Science.gov (United States)

    Allen, Casey J; Wagenaar, Amy E; Horkan, Davis B; Baldor, Daniel J; Hannay, William M; Tashiro, Jun; Namias, Nicholas; Sola, Juan E

    2016-07-01

    Injury severity scoring tools allow systematic comparison of outcomes in trauma research and quality improvement by indexing an expected mortality risk for certain injuries. This study investigated the predictive value of the empirically derived ICD9-derived Injury Severity Score (ICISS) compared to expert consensus-derived scoring systems for trauma mortality in a pediatric population. 1935 consecutive trauma patients aged <18 years from 1/2000 to 12/2012 were reviewed. Mechanism of injury (MOI), Injury Severity Score (ISS), Revised Trauma Score (RTS), Trauma Score ISS (TRISS), and ICISS were compared using univariate and multivariate logistic regression analysis and receiver operator characteristic analysis. The population was a median age of 11 ± 6 year, 70 % male, and 76 % blunt injury. Median ISS 13 ± 12 and overall mortality 3.5 %. Independent predictors of mortality were initial hematocrit [odds ratio (OR) 0.83 (0.73-0.95)], HCO3 [OR 0.82 (0.67-0.98)], Glasgow Coma Scale score [OR 0.75 (0.62-0.90)], and ISS [OR 1.10 (1.04-1.15)]. TRISS was superior to ICISS in predicting survival [area under receiver operator curve: 0.992 (0.982-1.000) vs 0.888 (0.838-0.938)]. ICISS was inferior to existing injury scoring tools at predicting mortality in pediatric trauma patients.

  6. Weight-loss medications

    Science.gov (United States)

    ... this page: //medlineplus.gov/ency/patientinstructions/000346.htm Weight-loss medicines To use the sharing features on this page, please enable JavaScript. Several weight-loss medicines are available. Ask your health care provider ...

  7. Bosniak Classification system

    DEFF Research Database (Denmark)

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

    2014-01-01

    . 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...

  8. Several clinical problems of light weight at birth%极低出生体重儿临床应注意的几个问题

    Institute of Scientific and Technical Information of China (English)

    樊绍曾

    2001-01-01

    @@极低出生体重儿(very low birth weight infant,VLBWI)是指出生体重不足1500g者。20世纪90年代又将出生体重不足1000g者命名为超低出生体重儿(extremely low birth weight infant,ELBWI)。虽然他们在出生的新生儿中所占比例不高,如上海国际和平妇幼保健院近9年中共有33449名新生儿在该院出生,极低出生体重儿共104名(0.32%),但其疾病发生率高,并因其生理、解剖特点,在医疗护理上存在众多的问题。本文所谈的VLBWI含ELB-WI。

  9. Classification of sepsis, severe sepsis and septic shock: the impact of minor variations in data capture and definition of SIRS criteria.

    Science.gov (United States)

    Klein Klouwenberg, Peter M C; Ong, David S Y; Bonten, Marc J M; Cremer, Olaf L

    2012-05-01

    To quantify the effects of minor variations in the definition and measurement of systemic inflammatory response syndrome (SIRS) criteria and organ failure on the observed incidences of sepsis, severe sepsis and septic shock. We conducted a prospective, observational study in a tertiary intensive care unit in The Netherlands between January 2009 and October 2010. A total of 1,072 consecutive adults were included. We determined the upper and lower limits of the measured incidence of sepsis by evaluating the influence of the use of an automated versus a manual method of data collection, and variations in the number of SIRS criteria, concurrency of SIRS criteria, and duration of abnormal values required to make a particular diagnosis. The measured incidence of SIRS varied from 49% (most restrictive setting) to 99% (most liberal setting). Subsequently, the incidences of sepsis, severe sepsis and septic shock ranged from 22 to 31%, from 6 to 27% and from 4 to 9% for the most restrictive versus the most liberal measurement settings, respectively. In non-infected patients, 39-98% of patients had SIRS, whereas still 17-6% of patients without SIRS had an infection. The apparent incidence of sepsis heavily depends on minor variations in the definition of SIRS and mode of data recording. As a consequence, the current consensus criteria do not ensure uniform recruitment of patients into sepsis trials.

  10. 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)....

  11. The association of self-regulation with weight loss maintenance after an intensive combined lifestyle intervention for children and adolescents with severe obesity

    NARCIS (Netherlands)

    Halberstadt, Jutka; de Vet, Emely; Nederkoorn, Chantal; Jansen, Anita; van Weelden, Ottelien H; Eekhout, Iris; Heymans, Martijn W.; Seidell, Jacob C.

    2017-01-01

    BACKGROUND: Knowledge is limited on the role the ability to self-regulate plays in the long-term outcome of obesity treatment in children and adolescents with severe obesity. The purpose of this study was to determine whether the ability to self-regulate after an one year intensive, partly

  12. 42 CFR 412.513 - Patient classification system.

    Science.gov (United States)

    2010-10-01

    ... 42 Public Health 2 2010-10-01 2010-10-01 false Patient classification system. 412.513 Section 412... Long-Term Care Hospitals § 412.513 Patient classification system. (a) Classification methodology. CMS... LTC-DRG classification system provides a LTC-DRG, and an appropriate weighting factor, for those...

  13. 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.

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

    Science.gov (United States)

    O'Connor, A; Phelan, N; Tun, T Kyaw; Boran, G; Gibney, J; Roche, H M

    2010-03-01

    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. Our objective was to determine which variables in plasma and adipose tissue influence HMW adiponectin in a well characterized cohort of women with PCOS. This was a cross-sectional study. 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). 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). 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. 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. 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.

  15. 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.

    Science.gov (United States)

    Van de Voorde, Patrick; Sabbe, Marc; Tsonaka, Roula; Rizopoulos, Dimitris; Calle, Paul; De Jaeger, Annick; Lesaffre, Emmanuel; Matthys, Dirk

    2011-01-01

    Important 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 >48 h) by means of a questionnaire based on this ICF construct (IROS). Questionnaires were sent to children; one year after this trauma and to 'control' children without any previous 'severe' trauma. We created propensity score-matched pairs (n = 133) and evaluated differences in health perception. IROS characteristics were investigated by means of Item Response Theory models. We then estimated the health state of each individual based on his/her response pattern (factor score z01) and investigated the effect of selected covariates with simple linear regression. Significant odds ratios for differences between matched groups (p trauma group showed, e.g. significant more physician (estimated relative risk R' 1.7) and psychologist (R' 3.5) visits. IROS primarily provides information from medium to high health burden levels and factor scores ranged from 0.41 (lowest) to 0.967 (highest burden). A significant impact on health burden could only be proven for the 'state at discharge' (p = 0.015), although there was a tendency towards worse factor scores for children that were older, had a higher Injury Severity Score or after traffic injury. In conclusion, we showed that the burden of health problems for children and families after severe trauma is still high and physical, as well as psychosocial in nature. The health state at discharge seems to predict long-term outcome, which might be of importance in view of, e.g. trajectory assistance. IROS may provide an improved scoring system to evaluate outcome after (paediatric) injury or critical illness.

  16. Short Text Classification: A Survey

    Directory of Open Access Journals (Sweden)

    Ge Song

    2014-05-01

    Full Text Available With the recent explosive growth of e-commerce and online communication, a new genre of text, short text, has been extensively applied in many areas. So many researches focus on short text mining. It is a challenge to classify the short text owing to its natural characters, such as sparseness, large-scale, immediacy, non-standardization. It is difficult for traditional methods to deal with short text classification mainly because too limited words in short text cannot represent the feature space and the relationship between words and documents. Several researches and reviews on text classification are shown in recent times. However, only a few of researches focus on short text classification. This paper discusses the characters of short text and the difficulty of short text classification. Then we introduce the existing popular works on short text classifiers and models, including short text classification using sematic analysis, semi-supervised short text classification, ensemble short text classification, and real-time classification. The evaluations of short text classification are analyzed in our paper. Finally we summarize the existing classification technology and prospect for development trend of short text classification

  17. PENGARUH PEMULIHAN GIZI BURUK RAWAT JALAN SECARA KOMPREHENSIF TERHADAP KENAIKAN BERAT BADAN, PANJANG BADAN, DAN STATUS GIZI ANAK BATITA (EFECTS OF COMPREHENSIVE OUTPATIENT CARE ON WEIGHT AND HEIGHT INCREAMENT, AND NUTRITIONAL STATUS AMONG SEVERELY MALNO

    Directory of Open Access Journals (Sweden)

    Arnelia Arnelia

    2013-07-01

    Full Text Available ABSTRACT Background: Outpatient care is a new approach for severely acute malnourished children while the other is inpatient care. To increase and optimalize outpatient care at Nutrition Clinic in Center for R&D in Nutrition and Food (CRDNF Bogor, the comprehensively treatment was performed including health, nutrition and caring practices. Objectives: To analyse weight and height increament and the nutritional status of under-three years children during outpatient care of severely malnourished children. Methods: An intervention study was implemented to severely malnourished children who participating in a 6 months outpatient care at Nutrition Clinic in CRDNF, Bogor. The comprehensive treatments were: curing the illness, nutrition and health counseling, gradually dietary treatment, caring guidance. The control groups were treated as the regular treatment of the clinic, including curing the illness, nutrition and health counseling and skim milk ration. Results: The average weight increament among comprehensive group significantly higher than those of reguler group, that was 1.39 ± 0.66 kg and 0.80 ± 0.40 after 3 months  (p=0.001 and at the end of out patient care was increased 2.02 ± 0.85 kg and 1.39 ± 0.52 consecutively (p=0.008. No different was found on the increament of childs length/height after 6 months out patient care, that was 4.0 ± 2.0 cm dan 4.1 ± 1.3 cm (p=0.806. After 3 months, 58.3% of comprehensive group and 22.7% of reguler group increased their weight by >15%, and to 73.9% and 50% after 4 months intervention. Based on W/H category, 79.2% of the comprehensive groups were severe wasting while in reguler group 59.1% and the rest were wasting at the beginning of the study. After 3 months intervention, 50% of the comprehensive group and 27.3% of the reguler group were normal and by the end increased to 73.9% and 33.3%. Conclusion: The increament of weight and the nutritional status improvement was much better among comprehensive

  18. Association of multimodal treatment-induced improvements in stress, exercise volume, nutrition, and weight with improved blood pressure in severely obese women.

    Science.gov (United States)

    Annesi, James J

    2013-09-01

    Research suggests that obesity, physical inactivity, anxiety (psychological tension), and a poor diet are associated with high blood pressure (BP). Although medication is the treatment of choice, behavioral methods might also improve BP in individuals with both prehypertension and hypertension. Severely obese women from the southeast USA (N = 155; M(age) = 45 years; M(body mass index) (BMI) = 41 kg/m(2)) that fulfilled criteria for either prehypertension (n = 96) or hypertension (n = 59) volunteered for a Young Men's Christian Association-based exercise and nutrition support treatment that also included instruction in stress-management methods. Significant (p values of ≤0.001) within-group improvements over 26 weeks in tension, overall mood, exercise volume, fruit and vegetable consumption, BMI, and systolic and diastolic BP were found. There were significant (p values of exercise, fruit and vegetable intake, BMI, and systolic and diastolic BP improvements. Multiple regression analyses, separately entering changes in tension and overall mood along with changes in volume of exercise, fruit and vegetable intake, and BMI, explained 19 and 20 % of the variances in systolic BP, respectively, (p values of <0.001) and 8 % of the variances, each (p values of ≤0.02), in diastolic BP. In each multiple regression equation, improvements in the psychological factors of tension and overall mood demonstrated the greatest independent contribution to the variances accounted for in BP improvements. The ability of nonpharmaceutical, behavioral methods to improve BP in women with prehypertension and hypertension was suggested, with changes in the psychological factors of tension and overall mood appearing to be especially salient. Practical applications of findings were suggested.

  19. Is the shock index based classification of hypovolemic shock applicable in multiple injured patients with severe traumatic brain injury?—an analysis of the TraumaRegister DGU®

    OpenAIRE

    Fröhlich, Matthias; Driessen, Arne; Böhmer, Andreas; Nienaber, Ulrike; Igressa, Alhadi; Probst, Christian; Bouillon, Bertil; Maegele, Marc; Mutschler, Manuel; ,

    2016-01-01

    Background A new classification of hypovolemic shock based on the shock index (SI) was proposed in 2013. This classification contains four classes of shock and shows good correlation with acidosis, blood product need and mortality. Since their applicability was questioned, the aim of this study was to verify the validity of the new classification in multiple injured patients with traumatic brain injury. Methods Between 2002 and 2013, data from 40 888 patients from the TraumaRegister DGU® were...

  20. Research on Improved Fuzzy Rule Weights in Imbalanced Cost Data Classification & Applications in Engineering Cost%基于改进模糊规则权重算法的不平衡造价数据分类及其应用研究

    Institute of Scientific and Technical Information of China (English)

    钟炜; 马啸雨; 姜腾腾; 邢忠桂

    2015-01-01

    针对传统不平衡造价数据分类算法准确率较低的问题,将专家经验分析这一维度引入到造价数据分类工作中,在对国内外相关学者在造价数据分类领域的研究成果进行归纳总结的基础上,将造价行业专家先验知识引入到不平衡造价数据分类领域,构建了基于改进模糊规则权重算法的不平衡造价数据分类模型;并将该模型应用到某单位工程项目的造价数据分类实例中,验证了该模型的可操作性,为其他单位进行类似工作提供了一个新的思考角度。%For the low classification accuracy problem of traditional unbalanced engineering cost data classification algorithm,this paper introduces the dimension of expertise,and an improved fuzzy rules weight algorithm is proposed for unbalanced data classification model. Firstly,we analyze relevant researches home and overboard, and summarize solutions against construction cost data classification proposed by experts in the same field. Secondly,we bring in the experts' prior knowledge in construction cost industry to the field of unbalanced construction cost data classification,thus build an unbalanced construction cost data classification model based on improving fuzzy rule and weight arithmetic. At last,we apply this model to the construction cost data classification example of a certain company's engineering project and get a relatively optimized method in solving the unbalanced construction cost data classification,which provides a new thinking perspective for other similar jobs.

  1. 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...... of descriptors, number of classes, and class intervals occurred between national schemes. However, a proposal “acoustic classification scheme for dwellings” has been developed recently in the European COST Action TU0901 with 32 member countries. This proposal has been accepted as an ISO work item. This paper...

  2. 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...

  3. Acoustic classification of dwellings

    DEFF Research Database (Denmark)

    Berardi, Umberto; Rasmussen, Birgit

    2014-01-01

    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 soun...... 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...... 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...

  4. International Paralympic Committee position stand--background and scientific principles of classification in Paralympic sport.

    Science.gov (United States)

    Tweedy, S M; Vanlandewijck, Y C

    2011-04-01

    The Classification Code of the International Paralympic Committee (IPC), inter alia, mandates the development of evidence-based systems of classification. This paper provides a scientific background for classification in Paralympic sport, defines evidence-based classification and provides guidelines for how evidence-based classification may be achieved. Classification is a process in which a single group of entities (or units) are ordered into a number of smaller groups (or classes) based on observable properties that they have in common, and taxonomy is the science of how to classify. Paralympic classification is interrelated with systems of classification used in two fields: Health and functioning. The International Classification of Functioning, Disability and Health is the most widely used classification in the field of functioning and health. To enhance communication, Paralympic systems of classification should use language and concepts that are consistent with the International Classification of Functioning, Disability and Health. Sport. Classification in sport reduces the likelihood of one-sided competition and in this way promotes participation. Two types of classification are used in sport-performance classification and selective classification. Paralympic sports require selective classification systems so that athletes who enhance their competitive performance through effective training will not be moved to a class with athletes who have less activity limitation, as they would in a performance classification system. Classification has a significant impact on which athletes are successful in Paralympic sport, but unfortunately issues relating to the weighting and aggregation of measures used in classification pose significant threats to the validity of current systems of classification. To improve the validity of Paralympic classification, the IPC Classification Code mandates the development of evidence-based systems of classification, an evidence

  5. On the Implementation of a Land Cover Classification System for SAR Images Using Khoros

    Science.gov (United States)

    Medina Revera, Edwin J.; Espinosa, Ramon Vasquez

    1997-01-01

    The Synthetic Aperture Radar (SAR) sensor is widely used to record data about the ground under all atmospheric conditions. The SAR acquired images have very good resolution which necessitates the development of a classification system that process the SAR images to extract useful information for different applications. In this work, a complete system for the land cover classification was designed and programmed using the Khoros, a data flow visual language environment, taking full advantages of the polymorphic data services that it provides. Image analysis was applied to SAR images to improve and automate the processes of recognition and classification of the different regions like mountains and lakes. Both unsupervised and supervised classification utilities were used. The unsupervised classification routines included the use of several Classification/Clustering algorithms like the K-means, ISO2, Weighted Minimum Distance, and the Localized Receptive Field (LRF) training/classifier. Different texture analysis approaches such as Invariant Moments, Fractal Dimension and Second Order statistics were implemented for supervised classification of the images. The results and conclusions for SAR image classification using the various unsupervised and supervised procedures are presented based on their accuracy and performance.

  6. 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)...

  7. Xenolog classification.

    Science.gov (United States)

    Darby, Charlotte A; Stolzer, Maureen; Ropp, Patrick J; Barker, Daniel; Durand, Dannie

    2017-03-01

    Orthology analysis is a fundamental tool in comparative genomics. Sophisticated methods have been developed to distinguish between orthologs and paralogs and to classify paralogs into subtypes depending on the duplication mechanism and timing, relative to speciation. However, no comparable framework exists for xenologs: gene pairs whose history, since their divergence, includes a horizontal transfer. Further, the diversity of gene pairs that meet this broad definition calls for classification of xenologs with similar properties into subtypes. We present a xenolog classification that uses phylogenetic reconciliation to assign each pair of genes to a class based on the event responsible for their divergence and the historical association between genes and species. Our classes distinguish between genes related through transfer alone and genes related through duplication and transfer. Further, they separate closely-related genes in distantly-related species from distantly-related genes in closely-related species. We present formal rules that assign gene pairs to specific xenolog classes, given a reconciled gene tree with an arbitrary number of duplications and transfers. These xenology classification rules have been implemented in software and tested on a collection of ∼13 000 prokaryotic gene families. In addition, we present a case study demonstrating the connection between xenolog classification and gene function prediction. The xenolog classification rules have been implemented in N otung 2.9, a freely available phylogenetic reconciliation software package. http://www.cs.cmu.edu/~durand/Notung . Gene trees are available at http://dx.doi.org/10.7488/ds/1503 . durand@cmu.edu. Supplementary data are available at Bioinformatics online.

  8. 76 FR 47614 - Mail Classification Change

    Science.gov (United States)

    2011-08-05

    ... Mail Classification Change AGENCY: Postal Regulatory Commission. ACTION: Notice. SUMMARY: The Commission is noticing a recently-filed Postal Service request for a change in classification to the ``Reply Rides Free'' program. The change increases the qualifying First-Class mail letter weight. This...

  9. Classifications for cesarean section: a systematic review.

    Directory of Open Access Journals (Sweden)

    Maria Regina Torloni

    Full Text Available BACKGROUND: Rising cesarean section (CS rates are a major public health concern and cause worldwide debates. To propose and implement effective measures to reduce or increase CS rates where necessary requires an appropriate classification. Despite several existing CS classifications, there has not yet been a systematic review of these. This study aimed to 1 identify the main CS classifications used worldwide, 2 analyze advantages and deficiencies of each system. METHODS AND FINDINGS: Three electronic databases were searched for classifications published 1968-2008. Two reviewers independently assessed classifications using a form created based on items rated as important by international experts. Seven domains (ease, clarity, mutually exclusive categories, totally inclusive classification, prospective identification of categories, reproducibility, implementability were assessed and graded. Classifications were tested in 12 hypothetical clinical case-scenarios. From a total of 2948 citations, 60 were selected for full-text evaluation and 27 classifications identified. Indications classifications present important limitations and their overall score ranged from 2-9 (maximum grade =14. Degree of urgency classifications also had several drawbacks (overall scores 6-9. Woman-based classifications performed best (scores 5-14. Other types of classifications require data not routinely collected and may not be relevant in all settings (scores 3-8. CONCLUSIONS: This review and critical appraisal of CS classifications is a methodologically sound contribution to establish the basis for the appropriate monitoring and rational use of CS. Results suggest that women-based classifications in general, and Robson's classification, in particular, would be in the best position to fulfill current international and local needs and that efforts to develop an internationally applicable CS classification would be most appropriately placed in building upon this

  10. Weight Control

    Science.gov (United States)

    ... obese. Achieving a healthy weight can help you control your cholesterol, blood pressure and blood sugar. It ... use more calories than you eat. A weight-control strategy might include Choosing low-fat, low-calorie ...

  11. Increasing fidelity in parsimony analysis of dorid nudibranchs by differential weighting, or a tale of two genes.

    Science.gov (United States)

    Thollesson, M

    2000-08-01

    Phylogenetic analyses of 22 dorid nudibranch species and 2 outgroup (dendronotacean and notaspidean) species were performed using sequences from two different mitochondrial genes (16S rRNA and COI). Several methods of differential weighting (positional, transformational, and combined) were explored using character congruence between the linked data sets as an optimality criterion. Most weighting schemes gave an increase in congruence as well as phylogenetic signal. The optimal weighting scheme according to the criterion was successive weighting of each character (positional weighting) with 1/(number of steps) in combination with LN weighting of character changes (transformational weighting). The cladogram from the optimal weighting scheme was, in general, congruent with existing classifications. One exception is the genus Goniodoris, which was paraphyletic if Okenia aspersa was not also included. Copyright 2000 Academic Press.

  12. 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...

  13. Compact Weighted Class Association Rule Mining using Information Gain

    CERN Document Server

    Ibrahim, S P Syed

    2011-01-01

    Weighted association rule mining reflects semantic significance of item by considering its weight. Classification constructs the classifier and predicts the new data instance. This paper proposes compact weighted class association rule mining method, which applies weighted association rule mining in the classification and constructs an efficient weighted associative classifier. This proposed associative classification algorithm chooses one non class informative attribute from dataset and all the weighted class association rules are generated based on that attribute. The weight of the item is considered as one of the parameter in generating the weighted class association rules. This proposed algorithm calculates the weight using the HITS model. Experimental results show that the proposed system generates less number of high quality rules which improves the classification accuracy.

  14. MRI Inter-Reader 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.

    Science.gov (United States)

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

    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.

  15. 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

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Guen Young; Lee, Joon Woo; Choi, Seung Woo; Lim, Hyun Jin; Sun, Hye Young; Kang, Yu Suhn; Kang, Heung Sik [Dept. of Radiology, Seoul National University Bundang Hospital, Seongnam (Korea, Republic of); Chai, Jee Won; Kim, Su Jin [Dept. of Radiology, SMG-SNU Boramae Medical Center, Seoul (Korea, Republic of)

    2015-08-15

    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.

  16. Birth Weight

    Science.gov (United States)

    ... baby, taken just after he or she is born. A low birth weight is less than 5.5 pounds. A high ... weight is more than 8.8 pounds. A low birth weight baby can be born too small, too early (premature), or both. This ...

  17. 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.

  18. Classification of nanopolymers

    Energy Technology Data Exchange (ETDEWEB)

    Larena, A; Tur, A [Department of Chemical Industrial Engineering and Environment, Universidad Politecnica de Madrid, E.T.S. Ingenieros Industriales, C/ Jose Gutierrez Abascal, Madrid (Spain); Baranauskas, V [Faculdade de Engenharia Eletrica e Computacao, Departamento de Semicondutores, Instrumentos e Fotonica, Universidade Estadual de Campinas, UNICAMP, Av. Albert Einstein N.400, 13 083-852 Campinas SP Brasil (Brazil)], E-mail: alarena@etsii.upm.es

    2008-03-15

    Nanopolymers with different structures, shapes, and functional forms have recently been prepared using several techniques. Nanopolymers are the most promising basic building blocks for mounting complex and simple hierarchical nanosystems. The applications of nanopolymers are extremely broad and polymer-based nanotechnologies are fast emerging. We propose a nanopolymer classification scheme based on self-assembled structures, non self-assembled structures, and on the number of dimensions in the nanometer range (nD)

  19. Classification of patch type in severe saline-alkaline grassland community in north of Shanxi Province%晋北重度盐碱化草地群落斑块的类型划分

    Institute of Scientific and Technical Information of China (English)

    王永新; 赵祥; 徐静; 董宽虎; 高文俊; 朱慧森; 陈文斌

    2012-01-01

    通过研究围栏封育3年的晋北重度盐碱草地的群落斑块类型,为采取合理的措施和选择适宜的植物改良盐碱草地提供理论依据。试验根据斑块内的指示性植物或高度聚集的植物种群且轮廓明显选取15个斑块进行初步分类,另随机选择斑块特征和界限不明显的20个斑块采用聚类分析法划分斑块群落类型,调查每个斑块的群落特征和基本形状,计算斑块形状指数和分维指数确定斑块类型。结果表明:晋北重度盐碱草地群落斑块可划分为光碱斑、碱蒿(Artemisia anethifolia)斑块、芦苇(Phrag-mites australis)斑块、碱茅(Puccinellia tenuiflora)斑块、虎尾草(Chioris virgata)斑块和赖草(Leymussecalinus)斑块等6种类型。斑块形状指数和分维指数从小到大的顺序依次是光碱斑、碱蒿斑块、芦苇斑块、碱茅斑块、虎尾草斑块和赖草斑块,反映了各斑块受盐碱干扰程度依次降低。%The patch types in severe saline-alkaline grassland community fenced for 3 years in north of Shanxi Province were studied in order to provide basic data for improving saline-alkaline grassland with reasonable methods and proper plants.Fifteen patches with indicative or highly collective and distinctive aspects were used for classification and another randomly selected 20 patches without indicative or highly collective and distinctive aspects were used for classification and cluster analysis.The results showed that patch community included bare saline-alkaline patch,Artemisia anethifolia patch,Phragmites australis patch,Puccinellia distans patch,Chloria virgata patch and Leymus secalinus patch.The order of patches shape indices and fractal dimensions from small to big was bare saline-alkaline patch,A.anethifolia patch,P.australis patch,P.distans patch,C.virgata patch and L.secalinus patch,which indicated the disturbance degree of salinization.

  20. 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.

  1. Recurrent neural collective classification.

    Science.gov (United States)

    Monner, Derek D; Reggia, James A

    2013-12-01

    With the recent surge in availability of data sets containing not only individual attributes but also relationships, classification techniques that take advantage of predictive relationship information have gained in popularity. The most popular existing collective classification techniques have a number of limitations-some of them generate arbitrary and potentially lossy summaries of the relationship data, whereas others ignore directionality and strength of relationships. Popular existing techniques make use of only direct neighbor relationships when classifying a given entity, ignoring potentially useful information contained in expanded neighborhoods of radius greater than one. We present a new technique that we call recurrent neural collective classification (RNCC), which avoids arbitrary summarization, uses information about relationship directionality and strength, and through recursive encoding, learns to leverage larger relational neighborhoods around each entity. Experiments with synthetic data sets show that RNCC can make effective use of relationship data for both direct and expanded neighborhoods. Further experiments demonstrate that our technique outperforms previously published results of several collective classification methods on a number of real-world data sets.

  2. Pattern Classification using Simplified Neural Networks

    CERN Document Server

    Kamruzzaman, S M

    2010-01-01

    In recent years, many neural network models have been proposed for pattern classification, function approximation and regression problems. This paper presents an approach for classifying patterns from simplified NNs. Although the predictive accuracy of ANNs is often higher than that of other methods or human experts, it is often said that ANNs are practically "black boxes", due to the complexity of the networks. In this paper, we have an attempted to open up these black boxes by reducing the complexity of the network. The factor makes this possible is the pruning algorithm. By eliminating redundant weights, redundant input and hidden units are identified and removed from the network. Using the pruning algorithm, we have been able to prune networks such that only a few input units, hidden units and connections left yield a simplified network. Experimental results on several benchmarks problems in neural networks show the effectiveness of the proposed approach with good generalization ability.

  3. 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.

  4. 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.

  5. Weighted statistical parameters for irregularly sampled time series

    CERN Document Server

    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, corrupt measurements, for example, or be inherent to the scanning law of satellites like Hipparcos and the forthcoming Gaia. This paper aims at improving the accuracy of common statistical parameters for the characterization of irregularly sampled signals. The uneven representation of time series, often including clumps of measurements and gaps with no data, can severely disrupt the values of estimators. A weighting scheme adapting to the sampling density and noise level of the signal is formulated. Its application to 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 sugg...

  6. Hand eczema classification

    DEFF Research Database (Denmark)

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

    2008-01-01

    Summary Background Hand eczema is a long-lasting disease with a high prevalence in the background population. The disease has severe, negative effects on quality of life and sometimes on social status. Epidemiological studies have identified risk factors for onset and prognosis, but treatment...... 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...... for hand eczema is needed. Objectives The present study attempts to characterize subdiagnoses of hand eczema with respect to basic demographics, medical history and morphology. Methods Clinical data from 416 patients with hand eczema from 10 European patch test clinics were assessed. Results...

  7. 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....

  8. Classification in Australia.

    Science.gov (United States)

    McKinlay, John

    Despite some inroads by the Library of Congress Classification and short-lived experimentation with Universal Decimal Classification and Bliss Classification, Dewey Decimal Classification, with its ability in recent editions to be hospitable to local needs, remains the most widely used classification system in Australia. Although supplemented at…

  9. 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

    2017-06-02

    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.

  10. Highest weight categories and recollements

    OpenAIRE

    Krause, Henning

    2015-01-01

    We provide several equivalent descriptions of a highest weight category using recollements of abelian categories. Also, we explain the connection between sequences of standard and exceptional objects.

  11. 轻钢门式刚架结构设计中几个关键问题%Several critical issues in the structural design of light-weight steel portal frame

    Institute of Scientific and Technical Information of China (English)

    何增军

    2012-01-01

    According to actual condition,based on many years' design experience,in light of several critical issues in the structural design of light-weight steel portal frame including load value,setting of bracing and rigid-tied arches,setting of knee-bracing,wind-resistant column,foundation and column foot,and antisepsis and fire prevention and so on,the essay proposes suggestions,with a view to provide certain reference for similar engineering design.%根据实际情况,总结多年设计经验,针对轻钢门式刚架结构设计中荷载取值、支撑和刚性系杆的布置、隅撑的设置、抗风柱、基础与柱脚、防腐与防火几个关键问题提出了建议,以期对此类工程设计提供一定的参考。

  12. Evaluating the Initialization Methods of Wavelet Networks for Hyperspectral Image Classification

    Science.gov (United States)

    Hsu, Pai-Hui

    2016-06-01

    The idea of using artificial neural network has been proven useful for hyperspectral image classification. However, the high dimensionality of hyperspectral images usually leads to the failure of constructing an effective neural network classifier. To improve the performance of neural network classifier, wavelet-based feature extraction algorithms can be applied to extract useful features for hyperspectral image classification. However, the extracted features with fixed position and dilation parameters of the wavelets provide insufficient characteristics of spectrum. In this study, wavelet networks which integrates the advantages of wavelet-based feature extraction and neural networks classification is proposed for hyperspectral image classification. Wavelet networks is a kind of feed-forward neural networks using wavelets as activation function. Both the position and the dilation parameters of the wavelets are optimized as well as the weights of the network during the training phase. The value of wavelet networks lies in their capabilities of optimizing network weights and extracting essential features simultaneously for hyperspectral images classification. In this study, the influence of the learning rate and momentum term during the network training phase is presented, and several initialization modes of wavelet networks were used to test the performance of wavelet networks.

  13. 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.

  14. 重度子痫前期病史妇女产后血压体质量的影响因素研究%Factors influencing postpartum blood pressure and body weight among women with severe preeclampsia

    Institute of Scientific and Technical Information of China (English)

    卢(契); 赵扬玉; 郑修霞

    2011-01-01

    目的 了解社会因素对重度子痫前期病史妇女产后血压和体质量的影响,为制定针对性的防护措施提供依据.方法 选取62例有重度子痫前期病史、产后1~3年的妇女,测定其血压和体质量,问卷调查其经济收入、学历、是否产后复查及有无定期体检,有无高血压等疾病家族史.结果 低学历者产后复查率显著低于高学历者,低收入者产后定期体检率显著低于高收入者(均P<0.05);产后复查者体重指数显著低于产后未复查者(P<0.05);低学历、产后未复查及未定期体检者高血压患病率显著增高(均P<0.05);产后复查是产后血压的独立影响因素(OR=0.19,95%CI为0.05~0.66).结论 学历、经济收入影响重度子痫前期妇女防护行为,继而影响其高血压患病率.应采取综合性措施提高该类妇女尤其是低学历及低收入者的防护意识,以降低产后高血压患病率.%Objective To investigate effects of social factors on postpartum blood pressure and body weight among women with severe preeclampsia,and to provide reference for taking preventive interventions.Methods Sixty-two women with history of severe preeclampsia were recruited 1 to 3 years after delivery.Their blood pressure and body weight were measured, and their economic status, educational background, postpartum counseling, regular physical examination, and family history of hypertension were investigated by using questionnaires.Results The rate of postpartum counseling was significantly lower in women with poor educational background, and the rate of regular physical examination was lower in women with low income(P<0.05 for both).The value of BMI of women receiving postpartum counseling was smaller than those receiving no postpartum counseling (P<0.05), and the rates of hypertension were statistically higher in women with poor educational background, receiving no postpartum counseling and regular physical examination(P<0.05 for all

  15. Efficacy Observation of Low Molecular Weight Heparin in Severe and Above AECOPD%低分子肝素钠在重度及极重度AECOPD疗效观察

    Institute of Scientific and Technical Information of China (English)

    周曦; 张柏膺; 严峻海

    2012-01-01

    目的 探讨重度及以上AECOPD应用抗凝治疗的临床意义.方法 选取60例入住病房的重度及以上AECOPD患者,随机分为实验组(抗凝)30例,对照组30例,均给予常规氧疗、抗感染、解痉平喘、化痰等治疗,实验组同时给予低分子肝素治疗1周.治疗前后分别检查动脉血气分析中PaO2、PaCO2,同时取静脉血测C-反应蛋白浓度(C-RP).结果抗凝治疗结束后,实验组中动脉血气分析中PaO2、PaCO2较对照组有明显改善,实验组的CRP浓度较对照组下降.两组比较差异均有统计学意义.结论 抗凝治疗可以改善重度及以上AECOPD患者的动脉血气分析中PaCO2、PaCO2,同时减轻患者体内炎症反应.%Objective To investigate the clinical significance of anticoagulant therapy on severe chronic obstructive pulmonary disease ( CORD ) with acute exacerbation. Methods 60 cases of severe level or above CORD patients with acute exacerbations were randomly divided into experimental groups ( anticoagulant ) having 30 cases, 30 cases in the control group undergone conventional oxygen therapy, antibiotics, antispasmodic asthma, phlegm and other treatment, and the experimental group at the same time were given low molecular weight heparin for 1 week. Blood oxygen pressure ( PaO2 ) in arterial blood, carbon dioxide partial pressure ( PaCO2 ) and C-reac-tive protein concentration ( CRP ) before and after treatment were measured. Results After the end of the anticoagulant therapy, PaO2 , PaGO-, in the experimental group had a more significant improvement than those in the control group; CRP in the experimental group decreased more significantly than that in the control group; and there were significant differences in PaO-, , PaGO-, and CRP between two groups. Conclusions The anticoagulant therapy can improve PaO-, , PaGO-, in severe and above AECOPD, and reduce the inflammatory response.

  16. 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.

  17. Classification of antimicrobial peptides with imbalanced datasets

    Science.gov (United States)

    Camacho, Francy L.; Torres, Rodrigo; Ramos Pollán, Raúl

    2015-12-01

    In the last years, pattern recognition has been applied to several fields for solving multiple problems in science and technology as for example in protein prediction. This methodology can be useful for prediction of activity of biological molecules, e.g. for determination of antimicrobial activity of synthetic and natural peptides. In this work, we evaluate the performance of different physico-chemical properties of peptides (descriptors groups) in the presence of imbalanced data sets, when facing the task of detecting whether a peptide has antimicrobial activity. We evaluate undersampling and class weighting techniques to deal with the class imbalance with different classification methods and descriptor groups. Our classification model showed an estimated precision of 96% showing that descriptors used to codify the amino acid sequences contain enough information to correlate the peptides sequences with their antimicrobial activity by means of learning machines. Moreover, we show how certain descriptor groups (pseudoaminoacid composition type I) work better with imbalanced datasets while others (dipeptide composition) work better with balanced ones.

  18. 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.

  19. 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.

  20. Extreme Learning Machine for land cover classification

    OpenAIRE

    Pal, Mahesh

    2008-01-01

    This paper explores the potential of extreme learning machine based supervised classification algorithm for land cover classification. In comparison to a backpropagation neural network, which requires setting of several user-defined parameters and may produce local minima, extreme learning machine require setting of one parameter and produce a unique solution. ETM+ multispectral data set (England) was used to judge the suitability of extreme learning machine for remote sensing classifications...

  1. Support for linguistic macrofamilies from weighted sequence alignment.

    Science.gov (United States)

    Jäger, Gerhard

    2015-10-13

    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.

  2. 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

  3. Marijuana and body weight.

    Science.gov (United States)

    Sansone, Randy A; Sansone, Lori A

    2014-07-01

    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 patients in which weight gain did occur, it was less than the comparator drug (megestrol). However, data generally suggest that acute marijuana use stimulates appetite, and that marijuana use may stimulate appetite in low-weight individuals. As for large epidemiological studies in the general population, findings consistently indicate that users of marijuana tend to have lower body mass indices than nonusers. While paradoxical and somewhat perplexing, these findings may be explained by various study confounds, such as potential differences between acute versus chronic marijuana use; the tendency for marijuana use to be associated with other types of drug use; and/or the possible competition between food and drugs for the same reward sites in the brain. Likewise, perhaps the effects of marijuana are a function of initial weight status-i.e., maybe marijuana is a metabolic regulatory substance that increases body weight in low-weight individuals but not in normal-weight or overweight individuals. Only further research will clarify the complex relationships between marijuana and body weight.

  4. Relationship Between Birth Weight and Maternal Age in Women With Severe Trauma%重大创伤家庭再生育母亲分娩年龄与新生儿出生体质量的关系

    Institute of Scientific and Technical Information of China (English)

    杨娟; 杨钊; 谭思; 王晓东

    2014-01-01

    Objective To analyze the relationship between birth weight and maternal age in women with severe trauma.Methods From January 2009 to December 2012,a total of 222 newborns whose mother suffered the May 1 2 Wenchuan Earthquake in Sichuan Province were enrolled in the study as research group. They were further divided into ≤29 years old subgroup (14 cases),>29-34 years old subgroup (41 cases),>34-39 years old subgroup (130 cases)and ≥40 years old subgroup (14 cases).Meanwhile 594 newborns who were the first children in their family were selected randomly as control group.Results ①There were no significant differences in birth weight and maternal age between two groups(P34-39 years old subgroup(P=0.001).No significant differences were found in birth weight of newborns with same gender among four subgroups (P>0.05 ).Conclusion With social care and psychological intervention during pregnancy,maternal age doesn′t have a significant effect on birth weight in women with severe trauma.%目的分析重大创伤家庭(子女遇难)再生育母亲的分娩年龄对新生儿出生体质量的影响。方法选择2009年1月至2011年12月“5.12汶川大地震”后重大创伤家庭再生育母亲于四川省都江堰市人民医院分娩的222例新生儿为研究对象并纳入研究组,按照母亲分娩年龄的不同再将其分为4个亚组,其中,14例新生儿为≤29岁亚组,41例为>29~34岁亚组,130例为>34~39岁亚组,37例为≥40岁亚组。随机选取同期在本院初次生育母亲分娩的594例新生儿作为对照组。本研究遵循的程序符合四川省都江堰市人民医院人体试验委员会所制定的伦理学标准,得到该委员会批准,分组征得受试对象监护人的知情同意,并与之签署临床研究知情同意书。结果①两组母亲的平均分娩年龄比较,差异有统计学意义(P0.05);②除>34~39岁亚组母亲分娩的男性和女性新生儿出生体质量比较,差异有统计学意义(P=0.001)

  5. MEDLINE Abstracts Classification Based on Noun Phrases Extraction

    Science.gov (United States)

    Ruiz-Rico, Fernando; Vicedo, José-Luis; Rubio-Sánchez, María-Consuelo

    Many algorithms have come up in the last years to tackle automated text categorization. They have been exhaustively studied, leading to several variants and combinations not only in the particular procedures but also in the treatment of the input data. A widely used approach is representing documents as Bag-Of-Words (BOW) and weighting tokens with the TFIDF schema. Many researchers have thrown into precision and recall improvements and classification time reduction enriching BOW with stemming, n-grams, feature selection, noun phrases, metadata, weight normalization, etc. We contribute to this field with a novel combination of these techniques. For evaluation purposes, we provide comparisons to previous works with SVM against the simple BOW. The well known OHSUMED corpus is exploited and different sets of categories are selected, as previously done in the literature. The conclusion is that the proposed method can be successfully applied to existing binary classifiers such as SVM outperforming the mixture of BOW and TFIDF approaches.

  6. 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...

  7. [Criticism of the gonioscopic classifications of the glaucoma: with particular reference to the classification issued by the European Glaucoma Society in 2008].

    Science.gov (United States)

    Bordeianu, Constantin Dan

    2014-01-01

    To critically analyze the gonioscopic classifications of glaucoma, especially of the classification issued by the European Glaucoma Society in 2008, in order to reveal its advantages and shortcomings. The paper tries to determine the extent to which this classification is clear (being based on a coherent and consistently followed set of criteria), is comprehensive (framing all forms of glaucoma), helps to understand the sickness (using a logical framing system), and facilitates therapeutic decision making (offering direct therapeutic suggestions). The paper shows that, compared with all the previous classifications, the 2008 European Glaucoma Society classification is one step ahead (in the way of classifying the group of secondary angle-closure glaucomas), two steps behind (in rejecting two useful categories of congenital glaucoma), and similar in several respects: that it is based on criticizable fundamental and secondary criteria that cannot cover all forms of sickness gathered at a particular crossing; that it uses several equally weighted criteria for one single crossing (division); that it frames one clinical entity in several clinical categories; that it does not reflect reality in some aspects; and that it does not offer direct therapeutic suggestions: after framing a case in a scheme built on the basis of gonioscopic observation, it requires a second stage of pathogenic analysis, so that the ophthalmologist is able to decide the correct treatment only in the third stage. This tortuous thinking pathway, with successive stages - that are not followed by all doctors, explains many of the erroneous therapeutic decisions. All these considerations justify the efforts to find a new classification, able to correct the abovementioned shortcomings.

  8. AN EMPIRICAL COMPARISON OF WEIGHTING FUNCTIONS FOR MULTI-LABEL DISTANCEWEIGHTED K-NEAREST NEIGHBOUR METHOD

    OpenAIRE

    Jianhua Xu

    2011-01-01

    Multi-label classification is an extension of classical multi-class one, where any instance can be associated with several classes simultaneously and thus the classes are no longer mutually exclusive. It was experimentally shown that the distance-weighted k-nearest neighbour (DWkNN) algorithm is superior to the original kNN rule for multi-class learning. But, it has not been investigated whether the distance-weighted strategy is valid for multi-label learning and which weightin...

  9. 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.

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

    Science.gov (United States)

    Schouten, Tijn M; Koini, Marisa; de Vos, Frank; Seiler, Stephan; van der Grond, Jeroen; Lechner, Anita; Hafkemeijer, Anne; Möller, Christiane; Schmidt, Reinhold; de Rooij, Mark; Rombouts, Serge A R B

    2016-01-01

    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.

  11. Optimal Combination of Classification Algorithms and Feature Ranking Methods for Object-Based Classification of Submeter Resolution Z/I-Imaging DMC Imagery

    Directory of Open Access Journals (Sweden)

    Fulgencio Cánovas-García

    2015-04-01

    Full Text Available Object-based image analysis allows several different features to be calculated for the resulting objects. However, a large number of features means longer computing times and might even result in a loss of classification accuracy. In this study, we use four feature ranking methods (maximum correlation, average correlation, Jeffries–Matusita distance and mean decrease in the Gini index and five classification algorithms (linear discriminant analysis, naive Bayes, weighted k-nearest neighbors, support vector machines and random forest. The objective is to discover the optimal algorithm and feature subset to maximize accuracy when classifying a set of 1,076,937 objects, produced by the prior segmentation of a 0.45-m resolution multispectral image, with 356 features calculated on each object. The study area is both large (9070 ha and diverse, which increases the possibility to generalize the results. The mean decrease in the Gini index was found to be the feature ranking method that provided highest accuracy for all of the classification algorithms. In addition, support vector machines and random forest obtained the highest accuracy in the classification, both using their default parameters. This is a useful result that could be taken into account in the processing of high-resolution images in large and diverse areas to obtain a land cover classification.

  12. 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.

  13. Noise-Tolerant Hyperspectral Signature Classification in Unresolved Object Detection with Adaptive Tabular Nearest Neighbor Encoding

    Science.gov (United States)

    Schmalz, M.; Key, G.

    Accurate spectral signature classification is a crucial step in the nonimaging detection and recognition of spaceborne objects. In classical hyperspectral recognition applications, especially where linear mixing models are employed, signature classification accuracy depends on accurate spectral endmember discrimination. In selected target recognition (ATR) applications, previous non-adaptive techniques for signature classification have yielded class separation and classifier refinement results that tend to be suboptimal. In practice, the number of signatures accurately classified often depends linearly on the number of inputs. This can lead to potentially severe classification errors in the presence of noise or densely interleaved signatures. In this paper, we present an enhancement of an emerging technology for nonimaging spectral signature classification based on a highly accurate, efficient search engine called Tabular Nearest Neighbor Encoding (TNE). Adaptive TNE can optimize its classifier performance to track input nonergodicities and yield measures of confidence or caution for evaluation of classification results. Unlike neural networks, TNE does not have a hidden intermediate data structure (e.g., a neural net weight matrix). Instead, TNE generates and exploits a user-accessible data structure called the agreement map (AM), which can be manipulated by Boolean logic operations to effect accurate classifier refinement through programmable algorithms. The open architecture and programmability of TNE's pattern-space (AM) processing allows a TNE developer to determine the qualitative and quantitative reasons for classification accuracy, as well as characterize in detail the signatures for which TNE does not obtain classification matches, and why such mis-matches occur. In this study AM-based classification has been modified to partially compensate for input statistical changes, in response to performance metrics such as probability of correct classification (Pd

  14. 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...

  15. 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

  16. PSO optimized Feed Forward Neural Network for offline Signature Classification

    Directory of Open Access Journals (Sweden)

    Pratik R. Hajare

    2015-07-01

    Full Text Available The paper is based on feed forward neural network (FFNN optimization by particle swarm intelligence (PSI used to provide initial weights and biases to train neural network. Once the weights and biases are found using Particle swarm optimization (PSO with neural network used as training algorithm for specified epoch, the same are used to train the neural network for training and classification of benchmark problems. Further the approach is tested for offline signature classifications. A comparison is made between normal FFNN with random weights and biases and FFNN with particle swarm optimized weights and biases. Firstly, the performance is tested on two benchmark databases for neural network, The Breast Cancer Database and the Diabetic Database. Result shows that neural network performs better with initial weights and biases obtained by Particle Swarm optimization. The network converges faster with PSO obtained initial weights and biases for FFNN and classification accuracy is increased.

  17. Sources of variation in hydrological classifications: Time scale, flow series origin and classification procedure

    Science.gov (United States)

    Peñas, Francisco J.; Barquín, José; Álvarez, César

    2016-07-01

    Classification of flow regimes in water management and hydroecological research has grown significantly in recent years. However, depending on available data and the procedures applied, there may be several credible classifications for a specific catchment. In this study, three inductive classifications derived from different initial flow data and one expert-driven classification were defined. The hydrological interpretation, statistical performance and spatial correspondence of these classifications were compared. Daily Gauged Classification (DC) was derived from daily flow data while Monthly Gauged Classification (MC) and Monthly Modeled Classification (MMC) were derived from monthly flow series, using gauged and modeled flow data, respectively. Expert-Driven Classification (EDC) was based on a Spanish nationwide hydrological classification, which is being used in the current River Basin Management Plans. The results showed that MC accounted for much of the critical hydrological information variability comprised within the DC. However, it also presented limitations regarding the inability to represent important hydroecological attributes, especially those related to droughts and high flow events. In addition, DC and MC presented an equivalent performance more than 60% of the time and obtained a mean ARI value of 0.4, indicating a similar classification structure. DC and MC outperformed MMC 100% and more than 50% of the times when they were compared by means of the classification strength and ANOVA, respectively. MMC also showed low correspondence with these classifications (ARI = 0.20). Thus, the use of modeled flow series should be limited to poorly gauged areas. Finally, the significantly reduced performance and the uneven distribution of classes found in EDC questions its application for different management objectives. This study shows that the selection of the most suitable approach according to the available data has significant implications for the

  18. Cluster Based Text Classification Model

    DEFF Research Database (Denmark)

    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 th...... datasets. Our model also outperforms A Decision Cluster Classification (ADCC) and the Decision Cluster Forest Classification (DCFC) models on the Reuters-21578 dataset....

  19. The defence of body weight: a physiological basis for weight regain after weight loss.

    Science.gov (United States)

    Sumithran, Priya; Proietto, Joseph

    2013-02-01

    Although weight loss can usually be achieved by restricting food intake, the majority of dieters regain weight over the long-term. In the hypothalamus, hormonal signals from the gastrointestinal tract, adipose tissue and other peripheral sites are integrated to influence appetite and energy expenditure. Diet-induced weight loss is accompanied by several physiological changes which encourage weight regain, including alterations in energy expenditure, substrate metabolism and hormone pathways involved in appetite regulation, many of which persist beyond the initial weight loss period. Safe effective long-term strategies to overcome these physiological changes are needed to help facilitate maintenance of weight loss. The present review, which focuses on data from human studies, begins with an outline of body weight regulation to provide the context for the subsequent discussion of short- and long-term physiological changes which accompany diet-induced weight loss.

  20. Estimating and verifying soil unit weight determined on the basis of SCPTu tests

    Directory of Open Access Journals (Sweden)

    Bagińska Irena

    2016-09-01

    Full Text Available The unit weight, as a basic physical feature of soil, is an elementary quantity, and knowledge of this parameter is necessary in each geotechnical and geo-engineering task. Estimation of this quantity can be made with both laboratory and field techniques. The paper comprises a multi-scale evaluation of unit weight of cohesive soil, based on several measurements made in nearby locations using the SCPTu static probe. The procedures used were based on the two classifications and two solutions from literature. The results were referenced to the actual values of unit weight determined with a direct procedure from undisturbed samples. The resulting solutions were the basis for proposing a new formula to determine the soil unit weight from SCPTu measurements, as well as comparative analysis using exemplary values taken from the national Polish standard.

  1. 基于选权迭代估计与非监督分类的多光谱图像变化检测%Change detection of multi-spectral images based on iterative estimation with weight selection and unsupervised classification

    Institute of Scientific and Technical Information of China (English)

    李莎; 倪维平; 严卫东; 吴俊政; 张晗

    2014-01-01

    针对多光谱图像的变化检测问题,提出了一种基于选权迭代估计( iterative estimation with weight selection, IEWS)与非监督分类( unsupervised classification,UC)的多光谱图像变化检测方法。借鉴IEWS的思想,并以类似于迭代加权多元变化检测( iteratively reweighted multivariate alteration detection,IRMAD)的迭代模式进行回归估计,得到初步的变化检测结果;并通过对初始变化信息的UC处理,以及对不同类别的IEWS,得到最终的变化检测结果。利用该方法对TM图像进行了实验,结果表明:所得到的变化信息在空间位置上同该区域相应时间段内土地利用/覆盖的变化情况具有很好的一致性;同时与多元变化检测及IRMAD方法变化检测的结果相比较,表明该方法对相对较小的变化信息具有更好的变化检测能力。%To solve the change detection problem of multi-channel remote sensing images, this paper proposes a method based on iterative estimation with weight selection ( IEWS) and unsupervised classification ( UC) . Firstly, the primary change information is obtained according to the concept of IEWS, and the iteration scheme of the estimation is also similar to that of the iteratively re -weighted multivariate alteration detection ( IRMAD ) . And then, the primary change information is classified by the UC and processed by the IEWS, which can get the eventual change information. The experimental results with multi-spectral data indicate that the method proposed in this paper is effective. By using this method, the spatial coherence between the change information and the change of land use/cover in this area is good. As for the detection of change in small regions, the method is especially obviouely better than the commonly-used methods of multivariate alteration detection ( MAD) and IR-MAD.

  2. Clinical Study on Treatment of the Low Molecular Weight Heparin in Children Severe Sepsis%低分子肝素治疗小儿严重脓毒症临床研究

    Institute of Scientific and Technical Information of China (English)

    莫巧字; 贾雯

    2016-01-01

    Objective To explore therapy values of the low molecular weight heparin in children severe sepsis.Method 38 children with severe sepsis were randomly divided into the experimental group and the control group,each group had 19 chil-dren.Both of two groups were treated with symptomatic and supportive treatment.Besides,the former was to be treated with LM-WH.And comparison of coagulation indexes of two groups in before and after the treatment,time in PICU,acute physiology and chronic health evaluation (APACHEⅡscore)and case -fatality rate.Results After treatment,in the experimental group the blood coagulation indexes was obviously improved compared with before treatment,the difference was statistically significant (P 0.05).Experimental group PLT,FIB and PT was higher than the control group,the difference was statistically significant (P <0.05).D -dimer,APTT was lower than the control group,the difference was statistically significant (P <0.05).Experimental group in PICU was shorter than the control group,the difference was statistically significant (P <0.05).Experimental group A-PACHEⅡscore was lower than the control group,the difference was statistically significant (P <0.05).Experimental group case fa-tality rate was lower than the control group,the difference was statistically significant (P <0.05).Conclusion LMWH has impor-tant clinical significance because it can improve children with severe sepsis in coagulation disorders,reduce case -fatality rate,and improve prognosis.%目的:探讨低分子肝素(LMWH)治疗小儿严重脓毒症的临床价值。方法:将38例严重脓毒症患儿随机分成试验组和对照组各19例,两组患儿均予以对症支持治疗,试验组在此基础上加用 LMWH 治疗,比较治疗前后两组凝血指标、住 PICU 时间、急性生理与慢性健康状况评分(APACHEⅡ评分)及病死率。结果:治疗后,试验组各项凝血指标较治疗前有明显改善,差异有统计学意义(P

  3. Real-time Classification of Non-Weight Bearing Lower-Limb Movements Using EMG to Facilitate Phantom Motor Execution: Engineering and Case Study Application on Phantom Limb Pain

    Directory of Open Access Journals (Sweden)

    Eva Lendaro

    2017-09-01

    Full Text Available Phantom motor execution (PME, facilitated by myoelectric pattern recognition (MPR and virtual reality (VR, is positioned to be a viable option to treat phantom limb pain (PLP. A recent clinical trial using PME on upper-limb amputees with chronic intractable PLP yielded promising results. However, further work in the area of signal acquisition is needed if such technology is to be used on subjects with lower-limb amputation. We propose two alternative electrode configurations to conventional, bipolar, targeted recordings for acquiring surface electromyography. We evaluated their performance in a real-time MPR task for non-weight-bearing, lower-limb movements. We found that monopolar recordings using a circumferential electrode of conductive fabric, performed similarly to classical bipolar recordings, but were easier to use in a clinical setting. In addition, we present the first case study of a lower-limb amputee with chronic, intractable PLP treated with PME. The patient’s Pain Rating Index dropped by 22 points (from 32 to 10, 68% after 23 PME sessions. These results represent a methodological advancement and a positive proof-of-concept of PME in lower limbs. Further work remains to be conducted for a high-evidence level clinical validation of PME as a treatment of PLP in lower-limb amputees.

  4. Neural net classification and LMS reconstruction to halftone images

    Science.gov (United States)

    Chang, Pao-Chi; Yu, Che-Sheng

    1998-01-01

    The objective of this work is to reconstruct high quality gray-level images from halftone images, or the inverse halftoning process. We develop high performance halftone reconstruction methods for several commonly used halftone techniques. For better reconstruction quality, image classification based on halftone techniques is placed before the reconstruction process so that the halftone reconstruction process can be fine tuned for each halftone technique. The classification is based on enhanced 1D correlation of halftone images and processed with a three- layer back propagation neural network. This classification method reached 100 percent accuracy with a limited set of images processed by dispersed-dot ordered dithering, clustered-dot ordered dithering, constrained average, and error diffusion methods in our experiments. For image reconstruction, we apply the least-mean-square adaptive filtering algorithm which intends to discover the optimal filter weights and the mask shapes. As a result, it yields very good reconstruction image quality. The error diffusion yields the best reconstructed quality among the halftone methods. In addition, the LMS method generates optimal image masks which are significantly different for each halftone method. These optimal masks can also be applied to more sophisticated reconstruction methods as the default filter masks.

  5. Sever's Disease

    Science.gov (United States)

    ... take place on hard surfaces, such as track, basketball, soccer, and gymnastics. Sever's disease also can result ... diagnosing Sever's disease, some doctors order them to rule out other problems, such as fractures. Sever's disease ...

  6. European Hernia Society classification of parastomal hernias.

    Science.gov (United States)

    Śmietański, M; Szczepkowski, M; Alexandre, J A; Berger, D; Bury, K; Conze, J; Hansson, B; Janes, A; Miserez, M; Mandala, V; Montgomery, A; Morales Conde, S; Muysoms, F

    2014-02-01

    A classification of parastomal hernias (PH) is needed to compare different populations described in various trials and cohort studies, complete the previous inguinal and ventral hernia classifications of the European Hernia Society (EHS) and will be integrated into the EuraHS database (European Registry of Abdominal Wall Hernias). Several members of the EHS board and invited experts gathered for 2 days to discuss the development of an EHS classification of PH. The discussions were based on a literature review and critical appraisal of existing classifications. The classification proposal is based on the PH defect size (small is ≤5 cm) and the presence of a concomitant incisional hernia (cIH). Four types were defined: Type I, small PH without cIH; Type II, small PH with cIH; Type III, large PH without cIH; and Type IV, large PH with cIH. In addition, the classification grid includes details about whether the hernia recurs after a previous PH repair or whether it is a primary PH. Clinical validation is needed in the future to assess if the classification allows us to differentiate the treatment strategy and if the classification impacts outcome in these different subgroups. A classification of PH divided into subgroups according to size and cIH was formulated with the aim of improving the ability to compare different studies and their results.

  7. Classification Criteria for Systemic Sclerosis: An ACR-EULAR Collaborative Initiative

    Science.gov (United States)

    van den Hoogen, Frank; Khanna, Dinesh; Fransen, Jaap; Johnson, Sindhu R.; Baron, Murray; Tyndall, Alan; Matucci-Cerinic, Marco; Naden, Raymond; Riemekasten, Gabriela; Carreira, Patricia; Gabrielli, Armando; Distler, Oliver; van Laar, Jacob M; Valentini, Gabriele; Denton, Christopher P; Kowal-Bielecka, Otylia; Inanc, Murat; Allanore, Yannick; Walker, Ulrich A; Müller-Ladner, Ulf; Vonk, Madelon; Czirjak, Laszlo; Herrick, Ariane; Sierakowski, Stanislav; Veale, Douglas; Chung, Lorinda; Clements, Phillip; Fessler, Barry J; Furst, Dan; Guiducci, Serena; Hsu, Vivian; Mayes, Maureen; Medsger, Thomas A; Merkel, Peter; Silver, Richard; Steen, Virginia; Varga, John; Collier, David; Csuka, Mary Ell; Jimenez, Sergio; Kahaleh, Bashar; Seibold, James R; Simms, Robert; Pope, Janet

    2013-01-01

    Background The 1980 classification criteria for systemic sclerosis (SSc) lack sensitivity in early SSc and limited cutaneous SSc. A joint ACR-EULAR committee was established to develop new classification criteria for SSc. Methods Using consensus methods, 23 candidate items were arranged in a multi-criteria additive point system with a threshold to classify cases as SSc. The classification system was reduced by clustering items, and simplifying weights. The system was tested by: a) determining specificity and sensitivity in SSc cases and controls with scleroderma-like disorders; b) validating against the combined view of a group of experts on a set of cases with or without SSc. Results Skin thickening of the fingers extending proximal to the MCPs is sufficient to be classified as SSc, if that is not present, seven additive items apply with varying weights for each: skin thickening of the fingers, finger tip lesions, telangiectasia, abnormal nailfold capillaries, interstitial lung disease or pulmonary arterial hypertension, Raynaud's phenomenon, and SSc-related autoantibodies. Sensitivity and specificity in the validation sample were 0.91 and 0.92 for the new classification criteria and 0.75 and 0.72 for the 1980 ARA classification criteria. All selected cases were classified in accordance with consensus-based expert opinion. All cases classified as SSc by the 1980 ARA criteria were classified with the new criteria, and several additional cases were now considered to be SSc. Conclusion The ACR-EULAR classification criteria for SSc performed better than the 1980 ARA Criteria for SSc and should allow for more patients to be classified correctly as SSc. PMID:24122180

  8. Classification of cultivated plants.

    NARCIS (Netherlands)

    Brandenburg, W.A.

    1986-01-01

    Agricultural practice demands principles for classification, starting from the basal entity in cultivated plants: the cultivar. In establishing biosystematic relationships between wild, weedy and cultivated plants, the species concept needs re-examination. Combining of botanic classification, based

  9. Spatiotemporal representations of rapid visual target detection: a single-trial EEG classification algorithm.

    Science.gov (United States)

    Fuhrmann Alpert, Galit; Manor, Ran; Spanier, Assaf B; Deouell, Leon Y; Geva, Amir B

    2014-08-01

    Brain computer interface applications, developed for both healthy and clinical populations, critically depend on decoding brain activity in single trials. The goal of the present study was to detect distinctive spatiotemporal brain patterns within a set of event related responses. We introduce a novel classification algorithm, the spatially weighted FLD-PCA (SWFP), which is based on a two-step linear classification of event-related responses, using fisher linear discriminant (FLD) classifier and principal component analysis (PCA) for dimensionality reduction. As a benchmark algorithm, we consider the hierarchical discriminant component Analysis (HDCA), introduced by Parra, et al. 2007. We also consider a modified version of the HDCA, namely the hierarchical discriminant principal component analysis algorithm (HDPCA). We compare single-trial classification accuracies of all the three algorithms, each applied to detect target images within a rapid serial visual presentation (RSVP, 10 Hz) of images from five different object categories, based on single-trial brain responses. We find a systematic superiority of our classification algorithm in the tested paradigm. Additionally, HDPCA significantly increases classification accuracies compared to the HDCA. Finally, we show that presenting several repetitions of the same image exemplars improve accuracy, and thus may be important in cases where high accuracy is crucial.

  10. Discriminative multi-task feature selection for multi-modality classification of Alzheimer's disease.

    Science.gov (United States)

    Ye, Tingting; Zu, Chen; Jie, Biao; Shen, Dinggang; Zhang, Daoqiang

    2016-09-01

    Recently, multi-task based feature selection methods have been used in multi-modality based classification of Alzheimer's disease (AD) and its prodromal stage, i.e., mild cognitive impairment (MCI). However, in traditional multi-task feature selection methods, some useful discriminative information among subjects is usually not well mined for further improving the subsequent classification performance. Accordingly, in this paper, we propose a discriminative multi-task feature selection method to select the most discriminative features for multi-modality based classification of AD/MCI. Specifically, for each modality, we train a linear regression model using the corresponding modality of data, and further enforce the group-sparsity regularization on weights of those regression models for joint selection of common features across multiple modalities. Furthermore, we propose a discriminative regularization term based on the intra-class and inter-class Laplacian matrices to better use the discriminative information among subjects. To evaluate our proposed method, we perform extensive experiments on 202 subjects, including 51 AD patients, 99 MCI patients, and 52 healthy controls (HC), from the baseline MRI and FDG-PET image data of the Alzheimer's Disease Neuroimaging Initiative (ADNI). The experimental results show that our proposed method not only improves the classification performance, but also has potential to discover the disease-related biomarkers useful for diagnosis of disease, along with the comparison to several state-of-the-art methods for multi-modality based AD/MCI classification.

  11. Volumetric magnetic resonance imaging classification for Alzheimer's disease based on kernel density estimation of local features

    Institute of Scientific and Technical Information of China (English)

    YAN Hao; WANG Hu; WANG Yong-hui; ZHANG Yu-mei

    2013-01-01

    Background The classification of Alzheimer's disease (AD) from magnetic resonance imaging (MRI) has been challenged by lack of effective and reliable biomarkers due to inter-subject variability.This article presents a classification method for AD based on kernel density estimation (KDE) of local features.Methods First,a large number of local features were extracted from stable image blobs to represent various anatomical patterns for potential effective biomarkers.Based on distinctive descriptors and locations,the local features were robustly clustered to identify correspondences of the same underlying patterns.Then,the KDE was used to estimate distribution parameters of the correspondences by weighting contributions according to their distances.Thus,biomarkers could be reliably quantified by reducing the effects of further away correspondences which were more likely noises from inter-subject variability.Finally,the Bayes classifier was applied on the distribution parameters for the classification of AD.Results Experiments were performed on different divisions of a publicly available database to investigate the accuracy and the effects of age and AD severity.Our method achieved an equal error classification rate of 0.85 for subject aged 60-80 years exhibiting mild AD and outperformed a recent local feature-based work regardless of both effects.Conclusions We proposed a volumetric brain MRI classification method for neurodegenerative disease based on statistics of local features using KDE.The method may be potentially useful for the computer-aided diagnosis in clinical settings.

  12. Spectral Classification Beyond M

    CERN Document Server

    Leggett, S K; Burgasser, A J; Jones, H R A; Marley, M S; Tsuji, T

    2004-01-01

    Significant populations of field L and T dwarfs are now known, and we anticipate the discovery of even cooler dwarfs by Spitzer and ground-based infrared surveys. However, as the number of known L and T dwarfs increases so does the range in their observational properties, and difficulties have arisen in interpreting the observations. Although modellers have made significant advances, the complexity of the very low temperature, high pressure, photospheres means that problems remain such as the treatment of grain condensation as well as incomplete and non-equilibrium molecular chemistry. Also, there are several parameters which control the observed spectral energy distribution - effective temperature, grain sedimentation efficiency, metallicity and gravity - and their effects are not well understood. In this paper, based on a splinter session, we discuss classification schemes for L and T dwarfs, their dependency on wavelength, and the effects of the parameters T_eff, f_sed, [m/H] and log g on optical and infra...

  13. Weight Management in Phenylketonuria

    DEFF Research Database (Denmark)

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

    2016-01-01

    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-term....... 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...

  14. CT classification of acetabular fractures

    Energy Technology Data Exchange (ETDEWEB)

    Marincek, B.; Porcellini, B.; Robotti, G.

    1984-05-01

    The contribution of computed tomography (CT) in classifying acetabular fractures was analysed retrospectively in 33 cases. CT and plain radiography classification agreed in 27 cases (82%). CT revealed more extensive fractures in 6 patients (thereof 5 patients with associated fractures). In 10 patients (thereof 9 patients with associated fractures) CT showed intraarticular fragments; radiographically intraarticular fragments were seen only in 2 patients and suspected in 4. CT is of considerable aid in defining the fracture pattern. It should be used mainly in patients with radiographically difficult interpretable associated fractures in order to assess preoperatively the weight-bearing part of the acetabulum, the degree of displacement and the presence of intraarticular fragments.

  15. Expression levels of obesity-related genes are associated with weight change in kidney transplant recipients.

    Directory of Open Access Journals (Sweden)

    Ann Cashion

    Full Text Available BACKGROUND: The aim of this study was to investigate the association of gene expression profiles in subcutaneous adipose tissue with weight change in kidney transplant recipients and to gain insights into the underlying mechanisms of weight gain. METHODOLOGY/PRINCIPAL FINDINGS: A secondary data analysis was done on a subgroup (n = 26 of existing clinical and gene expression data from a larger prospective longitudinal study examining factors contributing to weight gain in transplant recipients. Measurements taken included adipose tissue gene expression profiles at time of transplant, baseline and six-month weight, and demographic data. Using multivariate linear regression analysis controlled for race and gender, expression levels of 1553 genes were significantly (p<0.05 associated with weight change. Functional analysis using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes classifications identified metabolic pathways that were enriched in this dataset. Furthermore, GeneIndexer literature mining analysis identified a subset of genes that are highly associated with obesity in the literature and Ingenuity pathway analysis revealed several significant gene networks associated with metabolism and endocrine function. Polymorphisms in several of these genes have previously been linked to obesity. CONCLUSIONS/SIGNIFICANCE: We have successfully identified a set of molecular pathways that taken together may provide insights into the mechanisms of weight gain in kidney transplant recipients. Future work will be done to determine how these pathways may contribute to weight gain.

  16. Expression Levels of Obesity-Related Genes Are Associated with Weight Change in Kidney Transplant Recipients

    Science.gov (United States)

    Cashion, Ann; Stanfill, Ansley; Thomas, Fridtjof; Xu, Lijing; Sutter, Thomas; Eason, James; Ensell, Mang; Homayouni, Ramin

    2013-01-01

    Background The aim of this study was to investigate the association of gene expression profiles in subcutaneous adipose tissue with weight change in kidney transplant recipients and to gain insights into the underlying mechanisms of weight gain. Methodology/Principal Findings A secondary data analysis was done on a subgroup (n = 26) of existing clinical and gene expression data from a larger prospective longitudinal study examining factors contributing to weight gain in transplant recipients. Measurements taken included adipose tissue gene expression profiles at time of transplant, baseline and six-month weight, and demographic data. Using multivariate linear regression analysis controlled for race and gender, expression levels of 1553 genes were significantly (p<0.05) associated with weight change. Functional analysis using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes classifications identified metabolic pathways that were enriched in this dataset. Furthermore, GeneIndexer literature mining analysis identified a subset of genes that are highly associated with obesity in the literature and Ingenuity pathway analysis revealed several significant gene networks associated with metabolism and endocrine function. Polymorphisms in several of these genes have previously been linked to obesity. Conclusions/Significance We have successfully identified a set of molecular pathways that taken together may provide insights into the mechanisms of weight gain in kidney transplant recipients. Future work will be done to determine how these pathways may contribute to weight gain. PMID:23544116

  17. 1984–2010 trends in fire burn severity and area for the conterminous US

    Science.gov (United States)

    Picotte, Joshua J.; Peterson, Birgit E.; Meier, Gretchen; Howard, Stephen M.

    2016-01-01

    Burn severity products created by the Monitoring Trends in Burn Severity (MTBS) project were used to analyse historical trends in burn severity. Using a severity metric calculated by modelling the cumulative distribution of differenced Normalized Burn Ratio (dNBR) and Relativized dNBR (RdNBR) data, we examined burn area and burn severity of 4893 historical fires (1984–2010) distributed across the conterminous US (CONUS) and mapped by MTBS. Yearly mean burn severity values (weighted by area), maximum burn severity metric values, mean area of burn, maximum burn area and total burn area were evaluated within 27 US National Vegetation Classification macrogroups. Time series assessments of burned area and severity were performed using Mann–Kendall tests. Burned area and severity varied by vegetation classification, but most vegetation groups showed no detectable change during the 1984–2010 period. Of the 27 analysed vegetation groups, trend analysis revealed burned area increased in eight, and burn severity has increased in seven. This study suggests that burned area and severity, as measured by the severity metric based on dNBR or RdNBR, have not changed substantially for most vegetation groups evaluated within CONUS.

  18. 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.)

  19. 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.

  20. Assessment of liver cirrhosis severity in 1015 patients of the Euricterus database with Campbell-Child, Pugh-Child and with ascites and ascites-nutritional state (ANS) related classifications

    NARCIS (Netherlands)

    Reisman, Y; Gips, CH; Lavelle, SM; CuervasMons, [No Value; deDombal, FT; Gauthier, A; MalchowMoeller, A; Molino, G; Theodossi, A; Tsiftsis, DD

    1997-01-01

    Background/Aims: The assessment of disease stage in cirrhosis is important for the individual patient (prognosis, timing and risk for requiring surgical intervention) and also for population comparisons and trials. There are several established methods, and we have aimed at comparison of the methods

  1. A clinical classification of hypertension

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    @@ Hypertension is a common cardiovascular problem worldwide. As with any other disease it is important to assess the severity of the disease. However the present classification of hypertension by the Joint National Committee in its seventh report (JNC 7) with numerical values staging the severity of hypertension is theoretically correct but difficult to apply in practice (Table 1).1 Admittedly this is a step in the right direction with lesser number of stages compared to the sixth report.2 The World Health Organization- International Society of Hypertension (WHO-ISH)-1999 3 and the European Society of Hypertension - European Society of Cardiology (ESH-ESC)4 guidelines follow similar numerical classifications (Table 2). All these papers are referred to as 'guidelines' in this article.

  2. 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.

  3. Cirrhosis Classification Based on Texture Classification of Random Features

    Directory of Open Access Journals (Sweden)

    Hui Liu

    2014-01-01

    Full Text Available Accurate staging of hepatic cirrhosis is important in investigating the cause and slowing down the effects of cirrhosis. Computer-aided diagnosis (CAD can provide doctors with an alternative second opinion and assist them to make a specific treatment with accurate cirrhosis stage. MRI has many advantages, including high resolution for soft tissue, no radiation, and multiparameters imaging modalities. So in this paper, multisequences MRIs, including T1-weighted, T2-weighted, arterial, portal venous, and equilibrium phase, are applied. However, CAD does not meet the clinical needs of cirrhosis and few researchers are concerned with it at present. Cirrhosis is characterized by the presence of widespread fibrosis and regenerative nodules in the hepatic, leading to different texture patterns of different stages. So, extracting texture feature is the primary task. Compared with typical gray level cooccurrence matrix (GLCM features, texture classification from random features provides an effective way, and we adopt it and propose CCTCRF for triple classification (normal, early, and middle and advanced stage. CCTCRF does not need strong assumptions except the sparse character of image, contains sufficient texture information, includes concise and effective process, and makes case decision with high accuracy. Experimental results also illustrate the satisfying performance and they are also compared with typical NN with GLCM.

  4. Cirrhosis classification based on texture classification of random features.

    Science.gov (United States)

    Liu, Hui; Shao, Ying; Guo, Dongmei; Zheng, Yuanjie; Zhao, Zuowei; Qiu, Tianshuang

    2014-01-01

    Accurate staging of hepatic cirrhosis is important in investigating the cause and slowing down the effects of cirrhosis. Computer-aided diagnosis (CAD) can provide doctors with an alternative second opinion and assist them to make a specific treatment with accurate cirrhosis stage. MRI has many advantages, including high resolution for soft tissue, no radiation, and multiparameters imaging modalities. So in this paper, multisequences MRIs, including T1-weighted, T2-weighted, arterial, portal venous, and equilibrium phase, are applied. However, CAD does not meet the clinical needs of cirrhosis and few researchers are concerned with it at present. Cirrhosis is characterized by the presence of widespread fibrosis and regenerative nodules in the hepatic, leading to different texture patterns of different stages. So, extracting texture feature is the primary task. Compared with typical gray level cooccurrence matrix (GLCM) features, texture classification from random features provides an effective way, and we adopt it and propose CCTCRF for triple classification (normal, early, and middle and advanced stage). CCTCRF does not need strong assumptions except the sparse character of image, contains sufficient texture information, includes concise and effective process, and makes case decision with high accuracy. Experimental results also illustrate the satisfying performance and they are also compared with typical NN with GLCM.

  5. Weighted ensemble based automatic detection of exudates in fundus photographs.

    Science.gov (United States)

    Prentasic, Pavle; Loncaric, Sven

    2014-01-01

    Diabetic retinopathy (DR) is a visual complication of diabetes, which has become one of the leading causes of preventable blindness in the world. Exudate detection is an important problem in automatic screening systems for detection of diabetic retinopathy using color fundus photographs. In this paper, we present a method for detection of exudates in color fundus photographs, which combines several preprocessing and candidate extraction algorithms to increase the exudate detection accuracy. The first stage of the method consists of an ensemble of several exudate candidate extraction algorithms. In the learning phase, simulated annealing is used to determine weights for combining the results of the ensemble candidate extraction algorithms. The second stage of the method uses a machine learning-based classification for detection of exudate regions. The experimental validation was performed using the DRiDB color fundus image set. The validation has demonstrated that the proposed method achieved higher accuracy in comparison to state-of-the art methods.

  6. 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.

  7. 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 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.

  8. Physiological adaptations to weight loss and factors favouring weight regain.

    Science.gov (United States)

    Greenway, F L

    2015-08-01

    Obesity is a major global health problem and predisposes individuals to several comorbidities that can affect life expectancy. Interventions based on lifestyle modification (for example, improved diet and exercise) are integral components in the management of obesity. However, although weight loss can be achieved through dietary restriction and/or increased physical activity, over the long term many individuals regain weight. The aim of this article is to review the research into the processes and mechanisms that underpin weight regain after weight loss and comment on future strategies to address them. Maintenance of body weight is regulated by the interaction of a number of processes, encompassing homoeostatic, environmental and behavioural factors. In homoeostatic regulation, the hypothalamus has a central role in integrating signals regarding food intake, energy balance and body weight, while an 'obesogenic' environment and behavioural patterns exert effects on the amount and type of food intake and physical activity. The roles of other environmental factors are also now being considered, including sleep debt and iatrogenic effects of medications, many of which warrant further investigation. Unfortunately, physiological adaptations to weight loss favour weight regain. These changes include perturbations in the levels of circulating appetite-related hormones and energy homoeostasis, in addition to alterations in nutrient metabolism and subjective appetite. To maintain weight loss, individuals must adhere to behaviours that counteract physiological adaptations and other factors favouring weight regain. It is difficult to overcome physiology with behaviour. Weight loss medications and surgery change the physiology of body weight regulation and are the best chance for long-term success. An increased understanding of the physiology of weight loss and regain will underpin the development of future strategies to support overweight and obese individuals in their efforts

  9. 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.

  10. Random forest algorithm for classification of multiwavelength data

    Institute of Scientific and Technical Information of China (English)

    Dan Gao; Yan-Xia Zhang; Yong-Heng Zhao

    2009-01-01

    We introduced a decision tree method called Random Forests for multiwavelength data classification. The data were adopted from different databases, including the Sloan Digital Sky Survey (SDSS) Data Release five, USNO, FIRST and ROSAT.We then studied the discrimination of quasars from stars and the classification of quasars,stars and galaxies with the sample from optical and radio bands and with that from optical and X-ray bands. Moreover, feature selection and feature weighting based on Random Forests were investigated. The performances based on different input patterns were compared. The experimental results show that the random forest method is an effective method for astronomical object classification and can be applied to other classification problems faced in astronomy. In addition, Random Forests will show its superiorities due to its own merits, e.g. classification, feature selection, feature weighting as well as outlier detection.

  11. 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.

  12. Security classification of information

    Energy Technology Data Exchange (ETDEWEB)

    Quist, A.S.

    1989-09-01

    Certain governmental information must be classified for national security reasons. However, the national security benefits from classifying information are usually accompanied by significant costs -- those due to a citizenry not fully informed on governmental activities, the extra costs of operating classified programs and procuring classified materials (e.g., weapons), the losses to our nation when advances made in classified programs cannot be utilized in unclassified programs. The goal of a classification system should be to clearly identify that information which must be protected for national security reasons and to ensure that information not needing such protection is not classified. This document was prepared to help attain that goal. This document is the first of a planned four-volume work that comprehensively discusses the security classification of information. Volume 1 broadly describes the need for classification, the basis for classification, and the history of classification in the United States from colonial times until World War 2. Classification of information since World War 2, under Executive Orders and the Atomic Energy Acts of 1946 and 1954, is discussed in more detail, with particular emphasis on the classification of atomic energy information. Adverse impacts of classification are also described. Subsequent volumes will discuss classification principles, classification management, and the control of certain unclassified scientific and technical information. 340 refs., 6 tabs.

  13. 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

  14. 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.

  15. Class-specific weighting for Markov random field estimation: application to medical image segmentation.

    Science.gov (United States)

    Monaco, James P; Madabhushi, Anant

    2012-12-01

    Many estimation tasks require Bayesian classifiers capable of adjusting their performance (e.g. sensitivity/specificity). In situations where the optimal classification decision can be identified by an exhaustive search over all possible classes, means for adjusting classifier performance, such as probability thresholding or weighting the a posteriori probabilities, are well established. Unfortunately, analogous methods compatible with Markov random fields (i.e. large collections of dependent random variables) are noticeably absent from the literature. Consequently, most Markov random field (MRF) based classification systems typically restrict their performance to a single, static operating point (i.e. a paired sensitivity/specificity). To address this deficiency, we previously introduced an extension of maximum posterior marginals (MPM) estimation that allows certain classes to be weighted more heavily than others, thus providing a means for varying classifier performance. However, this extension is not appropriate for the more popular maximum a posteriori (MAP) estimation. Thus, a strategy for varying the performance of MAP estimators is still needed. Such a strategy is essential for several reasons: (1) the MAP cost function may be more appropriate in certain classification tasks than the MPM cost function, (2) the literature provides a surfeit of MAP estimation implementations, several of which are considerably faster than the typical Markov Chain Monte Carlo methods used for MPM, and (3) MAP estimation is used far more often than MPM. Consequently, in this paper we introduce multiplicative weighted MAP (MWMAP) estimation-achieved via the incorporation of multiplicative weights into the MAP cost function-which allows certain classes to be preferred over others. This creates a natural bias for specific classes, and consequently a means for adjusting classifier performance. Similarly, we show how this multiplicative weighting strategy can be applied to the MPM

  16. The quest for conditional independence in prospectivity modeling: weights-of-evidence, boost weights-of-evidence, and logistic regression

    Science.gov (United States)

    Schaeben, Helmut; Semmler, Georg

    2016-09-01

    The objective of prospectivity modeling is prediction of the conditional probability of the presence T = 1 or absence T = 0 of a target T given favorable or prohibitive predictors B, or construction of a two classes 0,1 classification of T. A special case of logistic regression called weights-of-evidence (WofE) is geologists' favorite method of prospectivity modeling due to its apparent simplicity. However, the numerical simplicity is deceiving as it is implied by the severe mathematical modeling assumption of joint conditional independence of all predictors given the target. General weights of evidence are explicitly introduced which are as simple to estimate as conventional weights, i.e., by counting, but do not require conditional independence. Complementary to the regression view is the classification view on prospectivity modeling. Boosting is the construction of a strong classifier from a set of weak classifiers. From the regression point of view it is closely related to logistic regression. Boost weights-of-evidence (BoostWofE) was introduced into prospectivity modeling to counterbalance violations of the assumption of conditional independence even though relaxation of modeling assumptions with respect to weak classifiers was not the (initial) purpose of boosting. In the original publication of BoostWofE a fabricated dataset was used to "validate" this approach. Using the same fabricated dataset it is shown that BoostWofE cannot generally compensate lacking conditional independence whatever the consecutively processing order of predictors. Thus the alleged features of BoostWofE are disproved by way of counterexamples, while theoretical findings are confirmed that logistic regression including interaction terms can exactly compensate violations of joint conditional independence if the predictors are indicators.

  17. Intelligent Classification in Huge Heterogeneous Data Sets

    Science.gov (United States)

    2015-06-01

    INTELLIGENT CLASSIFICATION IN HUGE HETEROGENEOUS DATA SETS JUNE 2015 FINAL TECHNICAL REPORT APPROVED FOR PUBLIC RELEASE; DISTRIBUTION UNLIMITED...To) JUL 2013 – APR 2015 4. TITLE AND SUBTITLE INTELLIGENT CLASSIFICATION IN HUGE HETEROGENEOUS DATA SETS 5a. CONTRACT NUMBER IN-HOUSE 5b. GRANT...signals and through data dimension reduction, and to develop and tailor algorithms for the extraction of intelligence from several huge heterogeneous

  18. 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

  19. 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 d...... classification systems and meta data taxonomies, should be based on ontologies.......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...

  20. Hyperspectral image classification based on spatial and spectral features and sparse representation

    Institute of Scientific and Technical Information of China (English)

    Yang Jing-Hui; Wang Li-Guo; Qian Jin-Xi

    2014-01-01

    To minimize the low classification accuracy and low utilization of spatial information in traditional hyperspectral image classification methods, we propose a new hyperspectral image classification method, which is based on the Gabor spatial texture features and nonparametric weighted spectral features, and the sparse representation classification method (Gabor–NWSF and SRC), abbreviated GNWSF–SRC. The proposed (GNWSF–SRC) method first combines the Gabor spatial features and nonparametric weighted spectral features to describe the hyperspectral image, and then applies the sparse representation method. Finally, the classification is obtained by analyzing the reconstruction error. We use the proposed method to process two typical hyperspectral data sets with different percentages of training samples. Theoretical analysis and simulation demonstrate that the proposed method improves the classification accuracy and Kappa coefficient compared with traditional classification methods and achieves better classification performance.

  1. Classification of Spreadsheet Errors

    OpenAIRE

    Rajalingham, Kamalasen; Chadwick, David R.; Knight, Brian

    2008-01-01

    This paper describes a framework for a systematic classification of spreadsheet errors. This classification or taxonomy of errors is aimed at facilitating analysis and comprehension of the different types of spreadsheet errors. The taxonomy is an outcome of an investigation of the widespread problem of spreadsheet errors and an analysis of specific types of these errors. This paper contains a description of the various elements and categories of the classification and is supported by appropri...

  2. Information gathering for CLP classification

    OpenAIRE

    Ida Marcello; Felice Giordano; Francesca Marina Costamagna

    2011-01-01

    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 requireme...

  3. 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.

  4. 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.

  5. 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.

  6. 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

  7. Concepts of Classification and Taxonomy. Phylogenetic Classification

    CERN Document Server

    Fraix-Burnet, Didier

    2016-01-01

    Phylogenetic approaches to classification have been heavily developed in biology by bioinformaticians. But these techniques have applications in other fields, in particular in linguistics. Their main characteristics is to search for relationships between the objects or species in study, instead of grouping them by similarity. They are thus rather well suited for any kind of evolutionary objects. For nearly fifteen years, astrocladistics has explored the use of Maximum Parsimony (or cladistics) for astronomical objects like galaxies or globular clusters. In this lesson we will learn how it works. 1 Why phylogenetic tools in astrophysics? 1.1 History of classification The need for classifying living organisms is very ancient, and the first classification system can be dated back to the Greeks. The goal was very practical since it was intended to distinguish between eatable and toxic aliments, or kind and dangerous animals. Simple resemblance was used and has been used for centuries. Basically, until the XVIIIth...

  8. 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

  9. HOSPITAL BIRTHS OF LOW BIRTH WEIGHT IN THE CITY OF CUIABÁ THE PERIOD 2000 TO 2008.

    Directory of Open Access Journals (Sweden)

    Carolina Sampaio Oliveira

    2011-01-01

    Full Text Available The ocurrence of low birth weight infants varies among contries, and even a general inidcator of health status of a population to be highly associated with socieconomic conditions(3. Newborns with low birth weight are more vulnerable to problems that increase the risk of morbidity and mortality(9. Several factors may be associated with low newborn weight among mothers with less than 20 years or over 35 years(16,17. Objectives: To describe the low-weight births in hospitals in the city of Cuiaba in the period 2000 to 2008 using the variables of the birth certificate (race, sex of infant and maternal age Method: a quantitative study, cross-sectional, restrospective and described with the use of secundary sources of data obtained from the Information System on Live Births (SINASC. The study population was constituted by the set of all vital statistics records of hospital deliveries of low birth weight infants n= 6.523, in the municipality of Cuiabá – MT in the period 2000 to 2008. Included only information from births and hospital births only, and with body weight equal to or less than 2,500g, this criterion is basead on the WHO classification. Results/Conclusion: The low birth weight hospital in the city of Cuiabá – MT in the period 2000 to 2008, has a prevalence of 6,6%, ocurred among newborns with GA between 37 and 41 weeks (43,3% n= 2827. The low weight births in the state of MT, evolve with the growing reduction of body weight, the highest prevalence being concentrated in the range of 1500 to 2499g weight. The low birth weight are more prevalent in females (53,7%, n=3506 and mullattos (70.4% n= 4595. 49% of mother of lbw infants are those who are aged 21 to 35 years of age (49,7%, n= 3240.

  10. Meta Classification for Variable Stars

    CERN Document Server

    Pichara, Karim; León, Daniel

    2016-01-01

    The need for the development of automatic tools to explore astronomical databases has been recognized since the inception of CCDs and modern computers. Astronomers already have developed solutions to tackle several science problems, such as automatic classification of stellar objects, outlier detection, and globular clusters identification, among others. New science problems emerge and it is critical to be able to re-use the models learned before, without rebuilding everything from the beginning when the science problem changes. In this paper, we propose a new meta-model that automatically integrates existing classification models of variable stars. The proposed meta-model incorporates existing models that are trained in a different context, answering different questions and using different representations of data. Conventional mixture of experts algorithms in machine learning literature can not be used since each expert (model) uses different inputs. We also consider computational complexity of the model by ...

  11. 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…

  12. Multiple sparse representations classification

    NARCIS (Netherlands)

    E. Plenge (Esben); S.K. Klein (Stefan); W.J. Niessen (Wiro); E. Meijering (Erik)

    2015-01-01

    textabstractSparse representations classification (SRC) is a powerful technique for pixelwise classification of images and it is increasingly being used for a wide variety of image analysis tasks. The method uses sparse representation and learned redundant dictionaries to classify image pixels. In t

  13. 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…

  14. Text Classification Using Sentential Frequent Itemsets

    Institute of Scientific and Technical Information of China (English)

    Shi-Zhu Liu; He-Ping Hu

    2007-01-01

    Text classification techniques mostly rely on single term analysis of the document data set, while more concepts,especially the specific ones, are usually conveyed by set of terms. To achieve more accurate text classifier, more informative feature including frequent co-occurring words in the same sentence and their weights are particularly important in such scenarios. In this paper, we propose a novel approach using sentential frequent itemset, a concept comes from association rule mining, for text classification, which views a sentence rather than a document as a transaction, and uses a variable precision rough set based method to evaluate each sentential frequent itemset's contribution to the classification. Experiments over the Reuters and newsgroup corpus are carried out, which validate the practicability of the proposed system.

  15. Segmentation and classification of biological objects

    DEFF Research Database (Denmark)

    Schultz, Nette

    1995-01-01

    The present thesis is on segmentation and classification of biological objects using statistical methods. It is based on case studies dealing with different kinds of pork meat images, and we introduce appropriate statistical methods to solve the tasks in the case studies. The case studies concern...... classification of back bacon slices from images of back bacon, prediction of ham weight from images of the carcass, and estimation of meat percent from cross-sectional images of the carcass. The first case study investigates three different classifiers ability to classify the quality of back bacon slices....... The back bacon slices are classified into four ordered classes representing the quality, and we use the sizes of different meat and fat areas of the slices as variables. The classifiers are Bayesian discriminant functions, Classification and Regression Trees, and feed-forward neural networks with back...

  16. Autonomous Ship Classification By Moment Invariants

    Science.gov (United States)

    Zvolanek, Budimir

    1981-12-01

    An algorithm to classify ships from images generated by an infrared (IR) imaging sensor is described. The algorithm is based on decision-theoretic classification of Moment Invariant Functions (MIFs). The MIFs are computed from two-dimensional gray-level images to form a feature vector uniquely describing the ship. The MIF feature vector is classified by a Distance-Weighted k-Nearest Neighbor (D-W k-NN) decision rule to identify the ship type. Significant advantage of the MIF feature extraction coupled with D-W k-NN classification is the invariance of the classification accuracies to ship/sensor orienta-tion - aspect, depression, roll angles and range. The accuracy observed from a set of simulated IR test images reveals a good potential of the classifier algorithm for ship screening.

  17. Extending self-organizing maps for supervised classification of remotely sensed data

    Institute of Scientific and Technical Information of China (English)

    CHEN Yongliang

    2009-01-01

    An extended self-organizing map for supervised classification is proposed in this paper. Unlike other traditional SOMs, the model has an input layer, a Kohonen layer, and an output layer. The number of neurons in the input layer depends on the dimensionality of input patterns. The number of neurons in the output layer equals the number of the desired classes. The number of neurons in the Kohonen layer may be a few to several thousands, which depends on the complexity of classification problems and the classification precision. Each training sample is expressed by a pair of vectors: an input vector and a class codebook vector. When a training sample is input into the model, Kohonens competitive learning rule is applied to selecting the winning neuron from the Kohonen layer and the weight coefficients connecting all the neurons in the input layer with both the winning neuron and its neighbors in the Kohonen layer are modified to be closer to the input vector, and those connecting all the neurons around the winning neuron within a certain diameter in the Kohonen layer with all the neurons in the output layer are adjusted to be closer to the class codebook vector. If the number of training samples is sufficiently large and the learning epochs iterate enough times, the model will be able to serve as a supervised classifier. The model has been tentatively applied to the supervised classification of multispectral remotely sensed data. The author compared the performances of the extended SOM and BPN in remotely sensed data classification. The investigation manifests that the extended SOM is feasible for supervised classification.

  18. Classifier in Age classification

    Directory of Open Access Journals (Sweden)

    B. Santhi

    2012-12-01

    Full Text Available Face is the important feature of the human beings. We can derive various properties of a human by analyzing the face. The objective of the study is to design a classifier for age using facial images. Age classification is essential in many applications like crime detection, employment and face detection. The proposed algorithm contains four phases: preprocessing, feature extraction, feature selection and classification. The classification employs two class labels namely child and Old. This study addresses the limitations in the existing classifiers, as it uses the Grey Level Co-occurrence Matrix (GLCM for feature extraction and Support Vector Machine (SVM for classification. This improves the accuracy of the classification as it outperforms the existing methods.

  19. Comparison of chi-squared automatic interaction detection classification trees vs TNM classification for patients with head and neck squamous cell carcinoma.

    Science.gov (United States)

    Avilés-Jurado, F Xavier; Terra, Ximena; Figuerola, Enric; Quer, Miquel; León, Xavier

    2012-03-01

    To compare chi-squared automatic interaction detection (CHAID) classification trees vs the seventh edition of the TNM classification for patients with head and neck squamous cell carcinoma and to assess whether CHAID classification trees might improve results obtained with the TNM classification. Patient disease was classified according to CHAID classification trees and the TNM classification, and the results were compared. Academic research. A total of 3373 patients with carcinoma of the oral cavity, oropharynx, hypopharynx, or larynx. The 2 classification methods were evaluated objectively, measuring intrastage homogeneity (hazard consistency), interstage heterogeneity (hazard discrimination), and disease stage distribution among patients (balance). In addition, to assess agreement between CHAID classification trees and the TNM classification, we calculated the κ statistic, weighted linearly and quadratically. Objective evaluation of the quality of the classification methods indicated that CHAID classification trees performed better than the TNM classification in terms of hazard consistency (2.51 for CHAID and 3.01 for TNM) and hazard discrimination (70.9% for CHAID and 52.7% for TNM) but not balance (-31.7% for CHAID and -15.5% for TNM). Analysis of concordance between the classification methods showed that the quadratic κ statistic was 0.77 (95% CI, 0.76-0.78) and the linear κ statistic was 0.59 (95% CI, 0.57-0.60) (P TNM classification and offer potential inclusion of new prognostic factors.

  20. Radar clutter classification

    Science.gov (United States)

    Stehwien, Wolfgang

    1989-11-01

    The problem of classifying radar clutter as found on air traffic control radar systems is studied. An algorithm based on Bayes decision theory and the parametric maximum a posteriori probability classifier is developed to perform this classification automatically. This classifier employs a quadratic discriminant function and is optimum for feature vectors that are distributed according to the multivariate normal density. Separable clutter classes are most likely to arise from the analysis of the Doppler spectrum. Specifically, a feature set based on the complex reflection coefficients of the lattice prediction error filter is proposed. The classifier is tested using data recorded from L-band air traffic control radars. The Doppler spectra of these data are examined; the properties of the feature set computed using these data are studied in terms of both the marginal and multivariate statistics. Several strategies involving different numbers of features, class assignments, and data set pretesting according to Doppler frequency and signal to noise ratio were evaluated before settling on a workable algorithm. Final results are presented in terms of experimental misclassification rates and simulated and classified plane position indicator displays.

  1. Multiple Spectral-Spatial Classification Approach for Hyperspectral Data

    Science.gov (United States)

    Tarabalka, Yuliya; Benediktsson, Jon Atli; Chanussot, Jocelyn; Tilton, James C.

    2010-01-01

    A .new multiple classifier approach for spectral-spatial classification of hyperspectral images is proposed. Several classifiers are used independently to classify an image. For every pixel, if all the classifiers have assigned this pixel to the same class, the pixel is kept as a marker, i.e., a seed of the spatial region, with the corresponding class label. We propose to use spectral-spatial classifiers at the preliminary step of the marker selection procedure, each of them combining the results of a pixel-wise classification and a segmentation map. Different segmentation methods based on dissimilar principles lead to different classification results. Furthermore, a minimum spanning forest is built, where each tree is rooted on a classification -driven marker and forms a region in the spectral -spatial classification: map. Experimental results are presented for two hyperspectral airborne images. The proposed method significantly improves classification accuracies, when compared to previously proposed classification techniques.

  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...... 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....... 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...

  3. Supernova Classification Using Swift UVOT Photometry

    Science.gov (United States)

    Smith, Madison; Brown, Peter J.

    2017-01-01

    With the great influx of supernova discoveries over the past few years, the observation time needed to acquire the spectroscopic data needed to classify supernova by type has become unobtainable. Instead, using the photometry of supernovae could greatly reduce the amount of time between discovery and classification. For this project we looked at the relationship between colors and supernova types through machine learning packages in Python. Using data from the Swift Ultraviolet/Optical Telescope (UVOT), each photometric point was assigned values corresponding to colors, absolute magnitudes, and the relative times from the peak brightness in several filters. These values were fed into three classifying methods, the nearest neighbors, decision tree, and random forest methods. We will discuss the success of these classification systems, the optimal filters for photometric classification, and ways to improve the classification.

  4. Regional manifold learning for disease classification.

    Science.gov (United States)

    Ye, Dong Hye; Desjardins, Benoit; Hamm, Jihun; Litt, Harold; Pohl, Kilian M

    2014-06-01

    While manifold learning from images itself has become widely used in medical image analysis, the accuracy of existing implementations suffers from viewing each image as a single data point. To address this issue, we parcellate images into regions and then separately learn the manifold for each region. We use the regional manifolds as low-dimensional descriptors of high-dimensional morphological image features, which are then fed into a classifier to identify regions affected by disease. We produce a single ensemble decision for each scan by the weighted combination of these regional classification results. Each weight is determined by the regional accuracy of detecting the disease. When applied to cardiac magnetic resonance imaging of 50 normal controls and 50 patients with reconstructive surgery of Tetralogy of Fallot, our method achieves significantly better classification accuracy than approaches learning a single manifold across the entire image domain.

  5. Classification method of matching knowledgeable manufacturing mode with dynamic environment based on nonlinear fuzzy weight SVM%基于非线性模糊支持向量机的知识化制造模式与动态环境匹配分类方法

    Institute of Scientific and Technical Information of China (English)

    王玉芳; 严洪森

    2014-01-01

    为了评价企业当前知识化制造模式与动态环境因素的匹配性,为企业的快速响应提供依据,提出了一种考虑模糊输入和不均衡样本的非线性模糊加权支持向量机(NFW-SVM)模型。考虑到实际生产面临的动态环境因素具有模糊性和不确定性,引入三角模糊数对模糊因素进行描述。针对不同匹配类别数据样本的不均衡性,设置了不同的分类惩罚因子,以降低小样本错分的比例。将变异算子和具有收缩因子的动态惯性权重引入到标准粒子群优化算法中,利用改进的粒子群算法对模型参数进行优化,提高模型的分类精度。给出了基于NFW-SVM模型的知识化制造模式与动态环境匹配的分类方法。最后,通过实例验证了该方法的有效性和可行性。%To correctly judge the matching category between current knowledgeable manufacturing mode and dynamic environment factors,and provide the basis for rapid response,a model of nonlin-ear fuzzy weight-support vector machine (NFW-SVM)is proposed in which fuzzy inputs and imbal-ance of the different matching categories of samples are considered.Considering the vagueness and uncertainty of the dynamic production environment in the actual production,the triangular fuzzy number is adopted to describe the vague factor.For the imbalance characters of the data sample in different categories,different category penalty factors are set up in the model to reduce the fault pro-portions of small samples.The mutation operator and dynamic inertia weight with constriction factors are introduced to the standard particle swarm optimization algorithm.To enhance the classification accuracy,the model parameters are optimized by the improved particle swarm optimization algo-rithm.The classification method based on NFW-SVM to judge the matching category between dy-namic environment factors and current manufacturing mode is presented.Finally,the effectiveness and

  6. 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.

  7. ON STABLE PERTURBATIONS OF THE STIFFLY WEIGHTED PSEUDOINVERSE AND WEIGHTED LEAST SQUARES PROBLEM

    Institute of Scientific and Technical Information of China (English)

    Mu-sheng Wei

    2005-01-01

    In this paper we study perturbations of the stiffly weighted pseudoinverse (W1/2 A)+W1/2 and the related stiffly weighted least squares problem, where both the matrices A and W are given with W positive diagonal and severely stiff. We show that the perturbations to the stiffly weighted pseudoinverse and the related stiffly weighted least squares problem are stable, if and only if the perturbed matrices (^)A = A+δA satisfy several row rank preserving conditions.

  8. A statistical approach to root system classification.

    Science.gov (United States)

    Bodner, Gernot; Leitner, Daniel; Nakhforoosh, Alireza; Sobotik, Monika; Moder, Karl; Kaul, Hans-Peter

    2013-01-01

    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. The classification method presented is based on a data-defined statistical procedure without a priori decision on the classifiers. The study demonstrates that principal component based rooting types provide efficient and meaningful multi-trait classifiers. 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. Rooting types emerging from measured data, mainly distinguished by diameter/weight and density dominated types. 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 techniques are essential.

  9. Gallstone Classification in Western Countries.

    Science.gov (United States)

    Cariati, Andrea

    2015-12-01

    In order to compare gallstone disease data from India and Asian countries with Western countries, it is fundamental to follow a common gallstone classification. Gallstone disease has afflicted humans since the time of Egyptian kings, and gallstones have been found during autopsies on mummies. Gallstone prevalence in adult population ranges from 10 to 15 %. Gallstones in Western countries are distinguished into the following classes: cholesterol gallstones that contain more than 50 % of cholesterol (nearly 75 % of gallstones) and pigment gallstones that contain less than 30 % of cholesterol by weight, which can be subdivided into black pigment gallstones and brown pigment gallstones. It has been shown that ultrastructural analysis with scanning electron microscopy is useful in the classification and study of pigment gallstones. Moreover, x-ray diffractometry analysis and infrared spectroscopy of gallstones are of fundamental importance for an accurate stone analysis. An accurate study of gallstones is useful to understand gallstone pathogenesis. In fact, bacteria are not important in cholesterol gallstone nucleation and growth, but they are important in brown pigment gallstone formation. On the contrary, calcium bilirubinate is fundamental in black pigment gallstone formation and probably also plays an important role in cholesterol gallstone nucleation and growth.

  10. Analyzing Tag Distributions in Folksonomies for Resource Classification

    CERN Document Server

    Zubiaga, Arkaitz; Fresno, Víctor

    2012-01-01

    Recent research has shown the usefulness of social tags as a data source to feed resource classification. Little is known about the effect of settings on folksonomies created on social tagging systems. In this work, we consider the settings of social tagging systems to further understand tag distributions in folksonomies. We analyze in depth the tag distributions on three large-scale social tagging datasets, and analyze the effect on a resource classification task. To this end, we study the appropriateness of applying weighting schemes based on the well-known TF-IDF for resource classification. We show the great importance of settings as to altering tag distributions. Among those settings, tag suggestions produce very different folksonomies, which condition the success of the employed weighting schemes. Our findings and analyses are relevant for researchers studying tag-based resource classification, user behavior in social networks, the structure of folksonomies and tag distributions, as well as for develope...

  11. Chemical Classification of Space Debris

    Institute of Scientific and Technical Information of China (English)

    LI Chunlai; ZUO Wei; LIU Jianjun; OUYANG Ziyuan

    2004-01-01

    Space debris, here referring to all non-operating orbital objects, has steadily increased in number so that it has become a potential barrier to the exploration of space. The ever-increasing number of space debris pieces in space has created an increasingly threatening hazard to all on-the-orbit spacecraft, and all future space exploration activities have to be designed and operated with respect to the increasing threat posed by space debris. Generally, space debris is classified as large, medium and small debris pieces based on their sizes. The large debris piece is easily catalogued, but medium to small debris pieces are very difficult to track and also quite different in damage mechanisms from the large ones. In this paper, a scheme of chemical classification of space debris is developed. In our scheme, the first-order classification is employed to divide space debris into two groups: natural micrometeoroids and artificial space debris.The second-order classification is based on their chemical patterns and compositions. The natural micrometeoroids are further divided into three types, namely maric, metal and phyllosilicate micrometeorites, while the artificial space debris is divided into seven types, which are polymers, non-metal debris, metals and their alloys, oxides, sulphides and their analogs, halides and carbides. Of the latter seven types, some can also be further divided into several sub-types. Chemical classification of space debris is very useful for the study of the chemical damage mechanism of small debris pieces, and also is of great significance in constraining the origin and source of space debris and assessing their impact on spacecraft and human space activities.

  12. Acute kidney injury in patients with severe sepsis or septic shock: a comparison between the ‘Risk, Injury, Failure, Loss of kidney function, End-stage kidney disease’ (RIFLE), Acute Kidney Injury Network (AKIN) and Kidney Disease: Improving Global Outcomes (KDIGO) classifications

    Science.gov (United States)

    Pereira, Marta; Rodrigues, Natacha; Godinho, Iolanda; Gameiro, Joana; Neves, Marta; Gouveia, João; Costa e Silva, Zélia; Lopes, José António

    2017-01-01

    Purpose Using the Risk, Injury, Failure, Loss of kidney function, End-stage kidney disease (RIFLE), Acute Kidney Injury Network (AKIN) and Kidney Disease: Improving Global Outcomes (KDIGO) systems, the incidence of acute kidney injury (AKI) and their ability to predict in-hospital mortality in severe sepsis or septic shock was compared. Materials and methods We performed a retrospective analysis of 457 critically ill patients with severe sepsis or septic shock hospitalized between January 2008 and December 2014. Multivariate logistic regression was employed to evaluate the association between the RIFLE, AKIN and KDIGO systems with in-hospital mortality. Model fit was assessed by the goodness-of-fit test and discrimination by the area under the receiver operating characteristic (AUROC) curve. Statistical significance was defined as P RIFLE (84.2%) and KDIGO (87.5%) identified more patients with AKI than AKIN (72.8%) (P RIFLE was not [adjusted OR 2.0 (95% CI 1–4), P = 0.063]. The AUROC curve for in-hospital mortality was similar between the three classifications (RIFLE 0.652, P RIFLE and KDIGO diagnosed more patients with AKI than AKIN, but the prediction ability for in-hospital mortality was similar between the three systems. PMID:28616211

  13. Acute kidney injury in patients with severe sepsis or septic shock: a comparison between the 'Risk, Injury, Failure, Loss of kidney function, End-stage kidney disease' (RIFLE), Acute Kidney Injury Network (AKIN) and Kidney Disease: Improving Global Outcomes (KDIGO) classifications.

    Science.gov (United States)

    Pereira, Marta; Rodrigues, Natacha; Godinho, Iolanda; Gameiro, Joana; Neves, Marta; Gouveia, João; Costa E Silva, Zélia; Lopes, José António

    2017-06-01

    Using the Risk, Injury, Failure, Loss of kidney function, End-stage kidney disease (RIFLE), Acute Kidney Injury Network (AKIN) and Kidney Disease: Improving Global Outcomes (KDIGO) systems, the incidence of acute kidney injury (AKI) and their ability to predict in-hospital mortality in severe sepsis or septic shock was compared. We performed a retrospective analysis of 457 critically ill patients with severe sepsis or septic shock hospitalized between January 2008 and December 2014. Multivariate logistic regression was employed to evaluate the association between the RIFLE, AKIN and KDIGO systems with in-hospital mortality. Model fit was assessed by the goodness-of-fit test and discrimination by the area under the receiver operating characteristic (AUROC) curve. Statistical significance was defined as P RIFLE (84.2%) and KDIGO (87.5%) identified more patients with AKI than AKIN (72.8%) (P RIFLE was not [adjusted OR 2.0 (95% CI 1-4), P = 0.063]. The AUROC curve for in-hospital mortality was similar between the three classifications (RIFLE 0.652, P RIFLE and KDIGO diagnosed more patients with AKI than AKIN, but the prediction ability for in-hospital mortality was similar between the three systems.

  14. Perceived size of friends and weight evaluation among low-income adolescents.

    Science.gov (United States)

    Ramirez, Jenna C; Milan, Stephanie

    2016-04-01

    Drawing from social comparison theory, we examine how perceptions of friends' body sizes may influence adolescents' subjective evaluations of their own body (e.g., how accurate they are in judging their weight, how much body dissatisfaction they feel), particularly for adolescent females. Participants were low-income, minority adolescents (Study 1: N = 194 females, Mean age = 15.4; Study 2: N = 409 males and females; Mean age = 14.9). Adolescents used figure rating scales to indicate their perceived size and that of four of their closest friends and completed several measures of subjective weight evaluation (e.g., weight classification, body dissatisfaction, internalized weight bias). In both studies, how adolescents perceived their body size and the body sizes of their thinnest and heaviest friends were positively correlated. In Study 1, overweight females based on measured BMI were less likely to accurately judge themselves as overweight if they had a close friend they perceived as heavy. In addition, females who viewed themselves as having a larger figure reported more internalized weight bias when they had friends they viewed as relatively thin. Findings from Study 2 suggest that how friends' bodies are perceived is predictive of subjective weight evaluation measures only for adolescent females. Programs that address negative aspects of social comparison may be important in preventing both obesity and eating disorder symptoms in adolescent females.

  15. Review of classification criteria for systemic lupus erythematosus.

    Science.gov (United States)

    Petri, Michelle

    2005-05-01

    The American College of Rheumatology classification criteria were devised in 1982. In 1997, the immunologic disorder criterion was revised by a committee (without validation). All 11 criteria in the American College of Rheumatology criteria set have limitations. One of the most important laboratory tests, hypocomplementemia, was excluded entirely. Other classification criteria, emphasizing weighting or recursive partitioning, exist, but they are more cumbersome. Revised criteria are needed, not just for systemic lupus erythematosus, but also for chronic cutaneous lupus.

  16. 78 FR 54970 - Cotton Futures Classification: Optional Classification Procedure

    Science.gov (United States)

    2013-09-09

    ... process in March 2012 (77 FR 5379). When verified by a futures classification, Smith-Doxey data serves as... Classification: Optional Classification Procedure AGENCY: Agricultural Marketing Service, USDA. ACTION: Proposed... for the addition of an optional cotton futures classification procedure--identified and known...

  17. On the atomic masses (weights?) Of the elements

    OpenAIRE

    Kaptay G.

    2012-01-01

    Atomic masses (weights?) is an essential information for mining and metallurgy. The paper discusses four subjects around this problem. First, the classification of all the elements is suggested into 4 classes, based on their isotope features, determining the accuracy of their known atomic masses. As part of that, the class of elements is discussed with uncertain atomic weights in accordance with the 2009 IUPAC recommendations. A better (easier to use) format of atomic weights is present...

  18. 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....

  19. 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.

  20. 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.

  1. Carbohydrate terminology and classification

    National Research Council Canada - National Science Library

    Cummings, J H; Stephen, A M

    2007-01-01

    ...) and polysaccharides (DP> or =10). Within this classification, a number of terms are used such as mono- and disaccharides, polyols, oligosaccharides, starch, modified starch, non-starch polysaccharides, total carbohydrate, sugars, etc...

  2. Classification of Sets using Restricted Boltzmann Machines

    CERN Document Server

    Louradour, Jérôme

    2011-01-01

    We consider the problem of classification when inputs correspond to sets of vectors. This setting occurs in many problems such as the classification of pieces of mail containing several pages, of web sites with several sections or of images that have been pre-segmented into smaller regions. We propose generalizations of the restricted Boltzmann machine (RBM) that are appropriate in this context and explore how to incorporate different assumptions about the relationship between the input sets and the target class within the RBM. In experiments on standard multiple-instance learning datasets, we demonstrate the competitiveness of approaches based on RBMs and apply the proposed variants to the problem of incoming mail classification.

  3. 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.

  4. Completion of the classification

    CERN Document Server

    Strade, Helmut

    2012-01-01

    This is the last of three volumes about ""Simple Lie Algebras over Fields of Positive Characteristic""by Helmut Strade, presenting the state of the art of the structure and classification of Lie algebras over fields of positive characteristic. In this monograph the proof of the Classification Theorem presented in the first volumeis concluded.Itcollects all the important results on the topic whichcan be found only in scatteredscientific literaturso far.

  5. Twitter content classification

    OpenAIRE

    2010-01-01

    This paper delivers a new Twitter content classification framework based sixteen existing Twitter studies and a grounded theory analysis of a personal Twitter history. It expands the existing understanding of Twitter as a multifunction tool for personal, profession, commercial and phatic communications with a split level classification scheme that offers broad categorization and specific sub categories for deeper insight into the real world application of the service.

  6. Thyroid and Weight

    Science.gov (United States)

    ... weight) weight loss. As in the treatment with hyperthyroidism, treatment of the abnormal state of hypothyroidism with thyroid ... Goiter Graves’ Disease Graves’ Eye Disease Hashimoto’s Thyroiditis Hyperthyroidism ... & Weight Thyroiditis Thyroid ...

  7. 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 ... caused by obesity. There are different types of weight loss surgery. They often limit the amount of food ...

  8. 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.

  9. [Severe asthma].

    Science.gov (United States)

    González, Claudio D

    2016-01-01

    The objectives of this work were to investigate the frequency of severe asthma (SA) according to WHO definition and to compare SA patients' characteristics with those of non-severe asthma (NSA); secondly, to investigate the level of control reached throughout a period of regular treatment. Between 1-1-2005 and 12-31-2014, 471 medical records from patients with bronchial asthma assisted in Buenos Aires City were analyzed. SA frequency was 40.1% (189/471), being significantly higher among patients from the public health system (47.7%, 108/226 vs. 33%, 81/245, p = 0.001). SA patients were older than NSA ones (51.3 ± 17.4 vs. 42.6 ± 17.1 years, p = 0.000), presented longer time since onset of the disease (median 30 vs. 20 years, p = 0.000), lower educational levels (secondary level or higher 41.7% vs. 58.1%, p = 0.000), lower frequency of rhinitis (47% vs. 60.6%, p = 0.004), more severe levels of airway obstruction (FEV% 50.2 ± 13.7 vs. 77.7 ± 12.4, p = 0.000), more frequent antecedents of Near Fatal Asthma (11.1% vs. 2.8%, p = 0.000), higher levels of serum IgE (median of 410 vs. 279 UI/l, p = 0.01) and higher demand of systemic steroids requirements and hospitalizations (68.7% vs. 50.7%, p = 0.000 and 37.5% vs. 15.9%, p = 0.000, respectively). A 30.6% of SA patients (58/189) reached a follow-up period of 12 months, 13 (22.5%) of whom reached the controlled asthma level. The frequency of SA found seems to be considerable. Multicenter studies to investigate the levels of control reached by SA patients with access to proper treatment are recommended.

  10. Words semantic orientation classification based on HowNet

    Institute of Scientific and Technical Information of China (English)

    LI Dun; MA Yong-tao; GUO Jian-li

    2009-01-01

    Based on the text orientation classification, a new measurement approach to semantic orientation of words was proposed. According to the integrated and detailed definition of words in HowNet, seed sets including the words with intense orientations were built up. The orientation similarity between the seed words and the given word was then calculated using the sentiment weight priority to recognize the semantic orientation of common words. Finally, the words' semantic orientation and the context were combined to recognize the given words' orientation. The experiments show that the measurement approach achieves better results for common words' orientation classification and contributes particularly to the text orientation classification of large granularities.

  11. A NEW SVM BASED EMOTIONAL CLASSIFICATION OF IMAGE

    Institute of Scientific and Technical Information of China (English)

    Wang Weining; Yu Yinglin; Zhang Jianchao

    2005-01-01

    How high-level emotional representation of art paintings can be inferred from percep tual level features suited for the particular classes (dynamic vs. static classification)is presented. The key points are feature selection and classification. According to the strong relationship between notable lines of image and human sensations, a novel feature vector WLDLV (Weighted Line Direction-Length Vector) is proposed, which includes both orientation and length information of lines in an image. Classification is performed by SVM (Support Vector Machine) and images can be classified into dynamic and static. Experimental results demonstrate the effectiveness and superiority of the algorithm.

  12. 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…

  13. The Effect of Sunspot Weighting

    Science.gov (United States)

    Svalgaard, Leif; Cagnotti, Marco; Cortesi, Sergio

    2017-02-01

    Although W. Brunner began to weight sunspot counts (from 1926), using a method whereby larger spots were counted more than once, he compensated for the weighting by not counting enough smaller spots in order to maintain the same reduction factor (0.6) as was used by his predecessor A. Wolfer to reduce the count to R. Wolf's original scale, so that the weighting did not have any effect on the scale of the sunspot number. In 1947, M. Waldmeier formalized the weighting (on a scale from 1 to 5) of the sunspot count made at Zurich and its auxiliary station Locarno. This explicit counting method, when followed, inflates the relative sunspot number over that which corresponds to the scale set by Wolfer (and matched by Brunner). Recounting some 60,000 sunspots on drawings from the reference station Locarno shows that the number of sunspots reported was "over counted" by {≈} 44 % on average, leading to an inflation (measured by an effective weight factor) in excess of 1.2 for high solar activity. In a double-blind parallel counting by the Locarno observer M. Cagnotti, we determined that Svalgaard's count closely matches that of Cagnotti, allowing us to determine from direct observation the daily weight factor for spots since 2003 (and sporadically before). The effective total inflation turns out to have two sources: a major one (15 - 18 %) caused by weighting of spots, and a minor source (4 - 5 %) caused by the introduction of the Zürich classification of sunspot groups which increases the group count by 7 - 8 % and the relative sunspot number by about half that. We find that a simple empirical equation (depending on the activity level) fits the observed factors well, and use that fit to estimate the weighting inflation factor for each month back to the introduction of effective inflation in 1947 and thus to be able to correct for the over-counts and to reduce sunspot counting to the Wolfer method in use from 1894 onwards.

  14. Models for warehouse management: classification and examples

    NARCIS (Netherlands)

    Berg, van den J.P.; Zijm, W.H.M.

    1999-01-01

    In this paper we discuss warehousing systems and present a classification of warehouse management problems. We start with a typology and a brief description of several types of warehousing systems. Next, we present a hierarchy of decision problems encountered in setting up warehousing systems, inclu

  15. Severity grading in radial dysplasia.

    Science.gov (United States)

    Vilkki, S K

    2014-11-01

    A functional scoring method to grade the usefulness and quality of the upper limbs in congenital radial dysplasia is presented. It is based on the author's examinations of 44 arms with congenital deficiency of the radius. The hand (H), wrist (W) and proximal parts (P) of the extremity are each scored from 0 to 10 points for severity. The scoring is expressed similarly to the TNM (tumour, nodes, metastasis) tumour classification, for example as H5W4P2. The maximum severity index is 30 points. A severity grade of mild is between 1 and 8 points, moderate between 9 and 16 points and severe 17 points and over. In the author's series, the grades were mild in eight, moderate in 21 and severe in 15 cases. The functional severity grading should allow better comparison of radially deficient limbs and the results of treatment between groups of patients. © The Author(s) 2014.

  16. 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

    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......: Of the 120 women, 32 (26.7%) were classified as having fatty and 88 (73.3%) as mixed/dense mammographic density, according to Danish dichotomous classification. According to BI-RADS density classification, 12 (10.0%) women were classified as having predominantly fatty (BI-RADS code 1), 46 (38.3%) as having...

  17. 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.

  18. 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

  19. 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.

  20. Weighted Polynomial Approximation for Automated Detection of Inspiratory Flow Limitation.

    Science.gov (United States)

    Huang, Sheng-Cheng; Jan, Hao-Yu; Fu, Tieh-Cheng; Lin, Wen-Chen; Lin, Geng-Hong; Lin, Wen-Chi; Tsai, Cheng-Lun; Lin, Kang-Ping

    2017-01-01

    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.

  1. Weight loss, weight regain and bone health.

    Science.gov (United States)

    Pines, Amos

    2012-08-01

    The ideal body image for women these days is being slim but, in the real world, obesity becomes a major health problem even in the developing countries. Overweight, but also underweight, may have associated adverse outcomes in many bodily systems, including the bone. Only a few studies have investigated the consequences of intentional weight loss, then weight regain, on bone metabolism and bone density. It seems that the negative impact of bone loss is not reversed when weight partially rebounds following the end of active intervention programs. Thus the benefits and risks of any weight loss program should be addressed individually, and monitoring of bone parameters is recommended.

  2. Concepts of Classification and Taxonomy Phylogenetic Classification

    Science.gov (United States)

    Fraix-Burnet, D.

    2016-05-01

    Phylogenetic approaches to classification have been heavily developed in biology by bioinformaticians. But these techniques have applications in other fields, in particular in linguistics. Their main characteristics is to search for relationships between the objects or species in study, instead of grouping them by similarity. They are thus rather well suited for any kind of evolutionary objects. For nearly fifteen years, astrocladistics has explored the use of Maximum Parsimony (or cladistics) for astronomical objects like galaxies or globular clusters. In this lesson we will learn how it works.

  3. Spectral-Spatial Hyperspectral Image Classification Based on KNN

    Science.gov (United States)

    Huang, Kunshan; Li, Shutao; Kang, Xudong; Fang, Leyuan

    2016-12-01

    Fusion of spectral and spatial information is an effective way in improving the accuracy of hyperspectral image classification. In this paper, a novel spectral-spatial hyperspectral image classification method based on K nearest neighbor (KNN) is proposed, which consists of the following steps. First, the support vector machine is adopted to obtain the initial classification probability maps which reflect the probability that each hyperspectral pixel belongs to different classes. Then, the obtained pixel-wise probability maps are refined with the proposed KNN filtering algorithm that is based on matching and averaging nonlocal neighborhoods. The proposed method does not need sophisticated segmentation and optimization strategies while still being able to make full use of the nonlocal principle of real images by using KNN, and thus, providing competitive classification with fast computation. Experiments performed on two real hyperspectral data sets show that the classification results obtained by the proposed method are comparable to several recently proposed hyperspectral image classification methods.

  4. Weighted norm inequalities and indices

    Directory of Open Access Journals (Sweden)

    Joaquim Martín

    2006-01-01

    Full Text Available We extend and simplify several classical results on weighted norm inequalities for classical operators acting on rearrangement invariant spaces using the theory of indices. As an application we obtain necessary and sufficient conditions for generalized Hardy type operators to be bounded on ?p(w, ?p,8(w, Gp(w and Gp,8(w.

  5. Psychosocial Consequences of Weight Cycling.

    Science.gov (United States)

    Bartlett, Susan J.; And Others

    1996-01-01

    Participants were 130 obese women who reported undertaking a mean lifetime total of 4.7 major diets on which they had lost a mean of 45.9 kilograms. Participants with a severe history of weight cycling had a significantly younger age of onset of obesity than mild cyclers and reported initiating dieting at a significantly younger age and lower…

  6. 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.

  7. 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. ... limiting calories) usually isn’t enough to cause weight loss. But exercise plays an important part in helping ...

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

    African Journals Online (AJOL)

    ADOWIE PERE

    Density-based Clustering for Traffic Accident Risk (DBCTAR) was carried out to assist in ascertaining the distribution of ... least one road vehicle, occurring on a road open to ... Road Safety Agency (FRSC), the Lagos State Traffic. Management ...

  9. Review of feed forward neural network classification preprocessing techniques

    Science.gov (United States)

    Asadi, Roya; Kareem, Sameem Abdul

    2014-06-01

    The best feature of artificial intelligent Feed Forward Neural Network (FFNN) classification models is learning of input data through their weights. Data preprocessing and pre-training are the contributing factors in developing efficient techniques for low training time and high accuracy of classification. In this study, we investigate and review the powerful preprocessing functions of the FFNN models. Currently initialization of the weights is at random which is the main source of problems. Multilayer auto-encoder networks as the latest technique like other related techniques is unable to solve the problems. Weight Linear Analysis (WLA) is a combination of data pre-processing and pre-training to generate real weights through the use of normalized input values. The FFNN model by using the WLA increases classification accuracy and improve training time in a single epoch without any training cycle, the gradient of the mean square error function, updating the weights. The results of comparison and evaluation show that the WLA is a powerful technique in the FFNN classification area yet.

  10. Discriminative Structured Dictionary Learning for Image Classification

    Institute of Scientific and Technical Information of China (English)

    王萍; 兰俊花; 臧玉卫; 宋占杰

    2016-01-01

    In this paper, a discriminative structured dictionary learning algorithm is presented. To enhance the dictionary’s discriminative power, the reconstruction error, classification error and inhomogeneous representation error are integrated into the objective function. The proposed approach learns a single structured dictionary and a linear classifier jointly. The learned dictionary encourages the samples from the same class to have similar sparse codes, and the samples from different classes to have dissimilar sparse codes. The solution to the objective function is achieved by employing a feature-sign search algorithm and Lagrange dual method. Experimental results on three public databases demonstrate that the proposed approach outperforms several recently proposed dictionary learning techniques for classification.

  11. Classification of human leukocyte antigen (HLA) supertypes

    DEFF Research Database (Denmark)

    Wang, Mingjun; Claesson, Mogens H

    2014-01-01

    Identification of new antigenic peptides, derived from infectious agents or cancer cells, which bind to human leukocyte antigen (HLA) class I and II molecules, is of importance for the development of new effective vaccines capable of activating the cellular arm of the immune response. However...... this complexity is to group thousands of different HLA molecules into several so-called HLA supertypes: a classification that refers to a group of HLA alleles with largely overlapping peptide binding specificities. In this chapter, we focus on the state-of-the-art classification of HLA supertypes including HLA...

  12. Astrophysical Weighted Particle Magnetohydrodynamics

    CERN Document Server

    Gaburov, Evghenii

    2010-01-01

    This paper presents applications of weighted meshless scheme for conservation laws to the Euler equations and the equations of ideal magnetohydrodynamics. The divergence constraint of the latter is maintained to the truncation error by a new meshless divergence cleaning procedure. The physics of the interaction between the particles is described by an one-dimensional Riemann problem in a moving frame. As a result, necessary diffusion which is required to treat dissipative processes is added automatically. As a result, our scheme has no free parameters that controls the physics of inter-particle interaction, with the exception of the number of the interacting neighbours which control the resolution and accuracy. The resulting equations have the form similar to SPH equations, and therefore existing SPH codes can be used to implement the weighed particle scheme. The scheme is validated in several hydrodynamic and MHD test cases. In particular, we demonstrate for the first time the ability of a meshless MHD schem...

  13. Optimally weighted L(2) distance for functional data.

    Science.gov (United States)

    Chen, Huaihou; Reiss, Philip T; Tarpey, Thaddeus

    2014-09-01

    Many techniques of functional data analysis require choosing a measure of distance between functions, with the most common choice being L2 distance. In this article we show that using a weighted L2 distance, with a judiciously chosen weight function, can improve the performance of various statistical methods for functional data, including k-medoids clustering, nonparametric classification, and permutation testing. Assuming a quadratically penalized (e.g., spline) basis representation for the functional data, we consider three nontrivial weight functions: design density weights, inverse-variance weights, and a new weight function that minimizes the coefficient of variation of the resulting squared distance by means of an efficient iterative procedure. The benefits of weighting, in particular with the proposed weight function, are demonstrated both in simulation studies and in applications to the Berkeley growth data and a functional magnetic resonance imaging data set.

  14. Supernova Photometric Classification Challenge

    CERN Document Server

    Kessler, Richard; Jha, Saurabh; Kuhlmann, Stephen

    2010-01-01

    We have publicly released a blinded mix of simulated SNe, with types (Ia, Ib, Ic, II) selected in proportion to their expected rate. The simulation is realized in the griz filters of the Dark Energy Survey (DES) with realistic observing conditions (sky noise, point spread function and atmospheric transparency) based on years of recorded conditions at the DES site. Simulations of non-Ia type SNe are based on spectroscopically confirmed light curves that include unpublished non-Ia samples donated from the Carnegie Supernova Project (CSP), the Supernova Legacy Survey (SNLS), and the Sloan Digital Sky Survey-II (SDSS-II). We challenge scientists to run their classification algorithms and report a type for each SN. A spectroscopically confirmed subset is provided for training. The goals of this challenge are to (1) learn the relative strengths and weaknesses of the different classification algorithms, (2) use the results to improve classification algorithms, and (3) understand what spectroscopically confirmed sub-...

  15. 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......, a good metric is required to measure distance or similarity between feature points so that the classification becomes feasible. Furthermore, in order to build a successful classifier, one needs to deeply understand how classifiers work. This thesis focuses on these three aspects of classification...... to segment breast tissue and pectoral muscle area from the background in mammogram. The second focus is the choices of metric and its influence to the feasibility of a classifier, especially on k-nearest neighbors (k-NN) algorithm, with medical applications on breast cancer prediction and calcification...

  16. 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...... HE, protein contact dermatitis/contact urticaria, hyperkeratotic endogenous eczema and vesicular endogenous eczema, respectively. An additional diagnosis was given if symptoms indicated that factors additional to the main diagnosis were of importance for the disease. RESULTS: Four hundred and twenty......%) could not be classified. 38% had one additional diagnosis and 26% had two or more additional diagnoses. Eczema on feet was found in 30% of the patients, statistically significantly more frequently associated with hyperkeratotic and vesicular endogenous eczema. CONCLUSION: We find that the classification...

  17. Classification problem in CBIR

    Directory of Open Access Journals (Sweden)

    Tatiana Jaworska

    2013-04-01

    Full Text Available At present a great deal of research is being done in different aspects of Content-Based Im-age Retrieval (CBIR. Image classification is one of the most important tasks in image re-trieval that must be dealt with. The primary issue we have addressed is: how can the fuzzy set theory be used to handle crisp image data. We propose fuzzy rule-based classification of image objects. To achieve this goal we have built fuzzy rule-based classifiers for crisp data. In this paper we present the results of fuzzy rule-based classification in our CBIR. Further-more, these results are used to construct a search engine taking into account data mining.

  18. 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...

  19. Relevant XML Documents - Approach Based on Vectors and Weight Calculation of Terms

    Directory of Open Access Journals (Sweden)

    Abdeslem DENNAI

    2016-10-01

    Full Text Available Three classes of documents, based on their data, circulate in the web: Unstructured documents (.Doc, .html, .pdf ..., semi-structured documents (.xml, .Owl ... and structured documents (Tables database for example. A semi-structured document is organized around predefined tags or defined by its author. However, many studies use a document classification by taking into account their textual content and underestimate their structure. We attempt in this paper to propose a representation of these semi-structured web documents based on weighted vectors allowing exploiting their content for a possible treatment. The weight of terms is calculated using: The normal frequency for a document, TF-IDF (Term Frequency - Inverse Document Frequency and logic (Boolean frequency for a set of documents. To assess and demonstrate the relevance of our proposed approach, we will realize several experiments on different corpus.

  20. [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.

  1. Fuzzy Naive Bayesian for constructing regulated network with weights.

    Science.gov (United States)

    Zhou, Xi Y; Tian, Xue W; Lim, Joon S

    2015-01-01

    In the data mining field, classification is a very crucial technology, and the Bayesian classifier has been one of the hotspots in classification research area. However, assumptions of Naive Bayesian and Tree Augmented Naive Bayesian (TAN) are unfair to attribute relations. Therefore, this paper proposes a new algorithm named Fuzzy Naive Bayesian (FNB) using neural network with weighted membership function (NEWFM) to extract regulated relations and weights. Then, we can use regulated relations and weights to construct a regulated network. Finally, we will classify the heart and Haberman datasets by the FNB network to compare with experiments of Naive Bayesian and TAN. The experiment results show that the FNB has a higher classification rate than Naive Bayesian and TAN.

  2. 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...

  3. Information gathering for CLP classification.

    Science.gov (United States)

    Marcello, Ida; Giordano, Felice; Costamagna, Francesca Marina

    2011-01-01

    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.

  4. 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.

  5. Computer Classification of Triangles and Quadrilaterals--A Challenging Application

    Science.gov (United States)

    Dennis, J. Richard

    1978-01-01

    Two computer exercises involving the classification of geometric figures are given. The mathematics required is relatively simple but comes from several areas--synthetic geometry, analytic geometry, and linear algebra. (MN)

  6. 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...

  7. Classification problem in CBIR

    OpenAIRE

    Tatiana Jaworska

    2013-01-01

    At present a great deal of research is being done in different aspects of Content-Based Im-age Retrieval (CBIR). Image classification is one of the most important tasks in image re-trieval that must be dealt with. The primary issue we have addressed is: how can the fuzzy set theory be used to handle crisp image data. We propose fuzzy rule-based classification of image objects. To achieve this goal we have built fuzzy rule-based classifiers for crisp data. In this paper we present the results ...

  8. Latent classification models

    DEFF Research Database (Denmark)

    Langseth, Helge; Nielsen, Thomas Dyhre

    2005-01-01

    One of the simplest, and yet most consistently well-performing setof classifiers is the \\NB models. These models rely on twoassumptions: $(i)$ All the attributes used to describe an instanceare conditionally independent given the class of that instance,and $(ii)$ all attributes follow a specific...... 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....

  9. 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.

  10. Constructing criticality by classification

    DEFF Research Database (Denmark)

    Machacek, Erika

    2017-01-01

    This paper explores the role of expertise, the nature of criticality, and their relationship to securitisation as mineral raw materials are classified. It works with the construction of risk along the liberal logic of security to explore how "key materials" are turned into "critical materials......, 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...

  11. 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

  12. Classification rules for Indian Rice diseases

    Directory of Open Access Journals (Sweden)

    A. Nithya

    2011-01-01

    Full Text Available Many techniques have been developed for learning rules and relationships automatically from diverse data sets, to simplify the often tedious and error-prone process of acquiring knowledge from empirical data. Decision tree is one of learning algorithm which posses certain advantages that make it suitable for discovering the classification rule for data mining applications. Normally Decision trees widely used learning method and do not require any prior knowledge of data distribution, works well on noisy data .It has been applied to classify Rice disease based on the symptoms. This paper intended to discover classification rules for the Indian rice diseases using the c4.5 decision trees algorithm. Expert systems have been used in agriculture since the early 1980s. Several systems have been developed in different countries including the USA, Europe, and Egypt for plant-disorder diagnosis, management and other production aspects. This paper explores what Classification rule can do in the agricultural domain.

  13. Automated classification of landforms on Mars

    Science.gov (United States)

    Bue, B. D.; Stepinski, T. F.

    2006-06-01

    We propose a numerical method for classification and characterization of landforms on Mars. The method provides an alternative to manual geomorphic mapping of the Martian surface. Digital elevation data is used to calculate several topographic attributes for each pixel in a landscape. Unsupervised classification, based on the self-organizing map technique, divides all pixels into mutually exclusive and exhaustive landform classes on the basis of similarity between attribute vectors. The results are displayed as a thematic map of landforms and statistics of attributes are used to assign semantic meaning to the classes. This method is used to produce a geomorphic map of the Terra Cimmeria region on Mars. We assess the quality of the automated classification and discuss differences between results of automated and manual mappings. Potential applications of our method, including crater counting, landscape feature search, and large scale quantitative comparisons of Martian surface morphology, are identified and evaluated.

  14. 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.

  15. What is new in genetics and osteogenesis imperfecta classification?

    OpenAIRE

    Eugênia R. Valadares; Carneiro, Túlio B.; Santos, Paula M.; Oliveira, Ana Cristina; Zabel, Bernhard

    2014-01-01

    OBJECTIVE: Literature review of new genes related to osteogenesis imperfecta (OI) and update of its classification. SOURCES: Literature review in the PubMed and OMIM databases, followed by selection of relevant references. SUMMARY OF THE FINDINGS: In 1979, Sillence et al. developed a classification of OI subtypes based on clinical features and disease severity: OI type I, mild, common, with blue sclera; OI type II, perinatal lethal form; OI type III, severe and progressively deformin...

  16. Random forests for classification in ecology.

    Science.gov (United States)

    Cutler, D Richard; Edwards, Thomas C; Beard, Karen H; Cutler, Adele; Hess, Kyle T; Gibson, Jacob; Lawler, Joshua J

    2007-11-01

    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.

  17. Dramatic weight loss with rufinamide.

    Science.gov (United States)

    Mourand, Isabelle; Crespel, Arielle; Gelisse, Philippe

    2013-01-01

    Rufinamide (RUF) is a novel antiepileptic drug considered as second-line therapy in the treatment of Lennox-Gastaut syndrome. Treatment-emergent adverse events (AEs) have consisted mainly of drowsiness, irritability, vomiting, and loss of appetite. RUF is considered as a "weight-neutral" drug. We found clinically significant weight loss in 7 of 15 consecutive adult patients (47%; 3 male, 4 female, aged 18-31 years) treated with RUF as add-on therapy (800-2,400 mg/day: 23.5-57.1 mg/kg/day). The body mass index (BMI) decreased by 7.3-18.7%. Two patients were obese class I before RUF. Five patients (71%) were underweight before RUF (mild in one case, moderate in two cases, and severe in two cases). Four of these patients stopped RUF because of this adverse effect. RUF was recommenced in two patients using a lower and slower dosing strategy; one patient showed improvement in seizure control and no weight loss but RUF was re-stopped in the second patient because of continued weight loss. Despite of weight loss, RUF was continued in two other patients because it reduced seizure activity. We primarily related weight loss to reduced food intake, that is, loss of appetite and nausea, although in two patients no obvious loss of appetite was reported. RUF can cause clinically significant weight loss in adult patients, even at low dose. This AE can affect patients who are already underweight. There is a possibility that lower starting doses and slower escalation might minimize weight loss, but further information is required to determine whether this is the case.

  18. Tissue tracking: applications for brain MRI classification

    Science.gov (United States)

    Melonakos, John; Gao, Yi; Tannenbaum, Allen

    2007-03-01

    Bayesian classification methods have been extensively used in a variety of image processing applications, including medical image analysis. The basic procedure is to combine data-driven knowledge in the likelihood terms with clinical knowledge in the prior terms to classify an image into a pre-determined number of classes. In many applications, it is difficult to construct meaningful priors and, hence, homogeneous priors are assumed. In this paper, we show how expectation-maximization weights and neighboring posterior probabilities may be combined to make intuitive use of the Bayesian priors. Drawing upon insights from computer vision tracking algorithms, we cast the problem in a tissue tracking framework. We show results of our algorithm on the classification of gray and white matter along with surrounding cerebral spinal fluid in brain MRI scans. We show results of our algorithm on 20 brain MRI datasets along with validation against expert manual segmentations.

  19. Personality: Description, Classification and Evaluation

    Directory of Open Access Journals (Sweden)

    Ibrahim Taymur

    2012-06-01

    Full Text Available Many descriptions and classifications of personality have been made to understand and acknowledge human being through out the history. During the developmental process of psychiatry, almost every school defined and assessed personality regarding to their own perspective. As DSM (Diagnostical and Statistical Manual of Mental Disorders and ICD (International Classification of Diseases being available to common usage, scientists conducted studies to set a common terminology for personality. Categorical and dimensional approaches are the most fundamentally different assessment strategies in the research and clinical aspects about personality. While categorical approach views the personality as dichotomies which consists of different groups, dimensional approach aims to describe the personality on the basis of dimensions, thus suggests that the personality is a structure formed by definite dimensions. Several advantages and disadvantages can be noticed when descriptions of personality and tools for the evaluation of personality are reviewed. When the section making suggestions about personality disorder in DSM-5 is evaluated, it is seen that it aims to restructure the personality disorder diagnostic group according to new findings and critiques. In this article, the description of personality throughout the history, dimensional, categorical and cognitive approaches to personality, the features of the tools that are used to assess and measure the personality are reviewed.

  20. 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.

  1. 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…

  2. Sandwich classification theorem

    Directory of Open Access Journals (Sweden)

    Alexey Stepanov

    2015-09-01

    Full Text Available The present note arises from the author's talk at the conference ``Ischia Group Theory 2014''. For subgroups FleN of a group G denote by Lat(F,N the set of all subgroups of N , containing F . Let D be a subgroup of G . In this note we study the lattice LL=Lat(D,G and the lattice LL ′ of subgroups of G , normalized by D . We say that LL satisfies sandwich classification theorem if LL splits into a disjoint union of sandwiches Lat(F,N G (F over all subgroups F such that the normal closure of D in F coincides with F . Here N G (F denotes the normalizer of F in G . A similar notion of sandwich classification is introduced for the lattice LL ′ . If D is perfect, i.,e. coincides with its commutator subgroup, then it turns out that sandwich classification theorem for LL and LL ′ are equivalent. We also show how to find basic subroup F of sandwiches for LL ′ and review sandwich classification theorems in algebraic groups over rings.

  3. 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...... in the process as well as modeling dependences between attributes....

  4. An automated cirrus classification

    Science.gov (United States)

    Gryspeerdt, Edward; Quaas, Johannes; Sourdeval, Odran; Goren, Tom

    2017-04-01

    Cirrus clouds play an important role in determining the radiation budget of the earth, but our understanding of the lifecycle and controls on cirrus clouds remains incomplete. Cirrus clouds can have very different properties and development depending on their environment, particularly during their formation. However, the relevant factors often cannot be distinguished using commonly retrieved satellite data products (such as cloud optical depth). In particular, the initial cloud phase has been identified as an important factor in cloud development, but although back-trajectory based methods can provide information on the initial cloud phase, they are computationally expensive and depend on the cloud parametrisations used in re-analysis products. In this work, a classification system (Identification and Classification of Cirrus, IC-CIR) is introduced. Using re-analysis and satellite data, cirrus clouds are separated in four main types: frontal, convective, orographic and in-situ. The properties of these classes show that this classification is able to provide useful information on the properties and initial phase of cirrus clouds, information that could not be provided by instantaneous satellite retrieved cloud properties alone. This classification is designed to be easily implemented in global climate models, helping to improve future comparisons between observations and models and reducing the uncertainty in cirrus clouds properties, leading to improved cloud parametrisations.

  5. 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 questio

  6. Nearest convex hull classification

    NARCIS (Netherlands)

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

    2006-01-01

    textabstractConsider the classification task of assigning a test object to one of two or more possible groups, or classes. An intuitive way to proceed is to assign the object to that class, to which the distance is minimal. As a distance measure to a class, we propose here to use the distance to the

  7. 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.

  8. 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…

  9. Classification of waste packages

    Energy Technology Data Exchange (ETDEWEB)

    Mueller, H.P.; Sauer, M.; Rojahn, T. [Versuchsatomkraftwerk GmbH, Kahl am Main (Germany)

    2001-07-01

    A barrel gamma scanning unit has been in use at the VAK for the classification of radioactive waste materials since 1998. The unit provides the facility operator with the data required for classification of waste barrels. Once these data have been entered into the AVK data processing system, the radiological status of raw waste as well as pre-treated and processed waste can be tracked from the point of origin to the point at which the waste is delivered to a final storage. Since the barrel gamma scanning unit was commissioned in 1998, approximately 900 barrels have been measured and the relevant data required for classification collected and analyzed. Based on the positive results of experience in the use of the mobile barrel gamma scanning unit, the VAK now offers the classification of barrels as a service to external users. Depending upon waste quantity accumulation, this measurement unit offers facility operators a reliable and time-saving and cost-effective means of identifying and documenting the radioactivity inventory of barrels scheduled for final storage. (orig.)

  10. 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

  11. Munitions Classification Library

    Science.gov (United States)

    2016-04-04

    the MM and TEMTADS 2x2 systems , with dynamic data handling for these systems on the horizon. Using UX-Analyze, a data processor can apply physics ... classification libraries. DRAFT 4 2.0 TECHNOLOGY Three different sensor systems were used during the initial phase of the data collection: a modified...

  12. 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 mod

  13. Modality-Invariant Image Classification Based on Modality Uniqueness and Dictionary Learning.

    Science.gov (United States)

    Kim, Seungryong; Cai, Rui; Park, Kihong; Kim, Sunok; Sohn, Kwanghoon

    2016-12-02

    We present a unified framework for image classification of image sets taken under varying modality conditions. Our method is motivated by a key observation that the image feature distribution is simultaneously influenced by the semantic-class and the modality category label, which limits the performance of conventional methods for that task. With this insight, we introduce modality uniqueness as a discriminative weight that divides each modality cluster from all other clusters. By leveraging the modality uniqueness, our framework is formulated as unsupervised modality clustering and classifier learning based on modality-invariant similarity kernel. Specifically, in the assignment step, each training image is first assigned to the most similar cluster according to its modality. In the update step, based on the current cluster hypothesis, the modality uniqueness and the sparse dictionary are updated. These two steps are formulated in an iterative manner. Based on the final clusters, a modalityinvariant marginalized kernel is then computed, where the similarities between the reconstructed features of each modality are aggregated across all clusters. Our framework enables the reliable inference of semantic-class category for an image, even across large photometric variations. Experimental results show that our method outperforms conventional methods on various benchmarks, such as landmark identification under severely varying weather conditions, domain-adapting image classification, and RGB and near-infrared (NIR) image classification.

  14. An automated classification approach to ranking photospheric proxies of magnetic energy build-up

    CERN Document Server

    Al-Ghraibah, Amani; McAteer, R T James

    2015-01-01

    We study the photospheric magnetic field of ~2000 active regions in solar cycle 23 to search for parameters indicative of energy build-up and subsequent release as a solar flare. We extract three sets of parameters: snapshots in space and time- total flux, magnetic gradients, and neutral lines; evolution in time- flux evolution; structures at multiple size scales- wavelet analysis. This combines pattern recognition and classification techniques via a relevance vector machine to determine whether a region will flare. We consider classification performance using all 38 extracted features and several feature subsets. Classification performance is quantified using both the true positive rate and the true negative rate. Additionally, we compute the true skill score which provides an equal weighting to true positive rate and true negative rate and the Heidke skill score to allow comparison to other flare forecasting work. We obtain a true skill score of ~0.5 for any predictive time window in the range 2-24hr, with ...

  15. An improved hyperspectral image classification approach based on ISODATA and SKR method

    Science.gov (United States)

    Hong, Pu; Ye, Xiao-feng; Yu, Hui; Zhang, Zhi-jie; Cai, Yu-fei; Tang, Xin; Tang, Wei; Wang, Chensheng

    2016-11-01

    Hyper-spectral images can not only provide spatial information but also a wealth of spectral information. A short list of applications includes environmental mapping, global change research, geological research, wetlands mapping, assessment of trafficability, plant and mineral identification and abundance estimation, crop analysis, and bathymetry. A crucial aspect of hyperspectral image analysis is the identification of materials present in an object or scene being imaged. Classification of a hyperspectral image sequence amounts to identifying which pixels contain various spectrally distinct materials that have been specified by the user. Several techniques for classification of multi-hyperspectral pixels have been used from minimum distance and maximum likelihood classifiers to correlation matched filter-based approaches such as spectral signature matching and the spectral angle mapper. In this paper, an improved hyperspectral images classification algorithm is proposed. In the proposed method, an improved similarity measurement method is applied, in which both the spectrum similarity and space similarity are considered. We use two different weighted matrix to estimate the spectrum similarity and space similarity between two pixels, respectively. And then whether these two pixels represent the same material can be determined. In order to reduce the computational cost the wavelet transform is also applied prior to extract the spectral and space features. The proposed method is tested using hyperspectral imagery collected by the National Aeronautics and Space Administration Jet Propulsion Laboratory. Experimental results the efficiency of this new method on hyperspectral images associated with space object material identification.

  16. Random Forest Classification of Sediments on Exposed Intertidal Flats Using ALOS-2 Quad-Polarimetric SAR Data

    Science.gov (United States)

    Wang, W.; Yang, X.; Liu, G.; Zhou, H.; Ma, W.; Yu, Y.; Li, Z.

    2016-06-01

    Coastal zones are one of the world's most densely populated areas and it is necessary to propose an accurate, cost effective, frequent, and synoptic method of monitoring these complex ecosystems. However, misclassification of sediments on exposed intertidal flats restricts the development of coastal zones surveillance. With the advent of SAR (Synthetic Aperture Radar) satellites, polarimetric SAR satellite imagery plays an increasingly important role in monitoring changes in coastal wetland. This research investigated the necessity of combining SAR polarimetric features with optical data, and their contribution in accurately sediment classification. Three experimental groups were set to make assessment of the most appropriate descriptors. (i) Several SAR polarimetric descriptors were extracted from scattering matrix using Cloude-Pottier, Freeman-Durden and Yamaguchi methods; (ii) Optical remote sensing (RS) data with R, G and B channels formed the second feature combinations; (iii) The chosen SAR and optical RS indicators were both added into classifier. Classification was carried out using Random Forest (RF) classifiers and a general result mapping of intertidal flats was generated. Experiments were implemented using ALOS-2 L-band satellite imagery and GF-1 optical multi-spectral data acquired in the same period. The weights of descriptors were evaluated by VI (RF Variable Importance). Results suggested that optical data source has few advantages on sediment classification, and even reduce the effect of SAR indicators. Polarimetric SAR feature sets show great potentials in intertidal flats classification and are promising in classifying mud flats, sand flats, bare farmland and tidal water.

  17. An improved k-NN method based on multiple-point statistics for classification of high-spatial resolution imagery

    Science.gov (United States)

    Tang, Y.; Jing, L.; Li, H.; Liu, Q.; Ding, H.

    2016-04-01

    In this paper, the potential of multiple-point statistics (MPS) for object-based classification is explored using a modified k-nearest neighbour (k-NN) classification method (MPk-NN). The method first utilises a training image derived from a classified map to characterise the spatial correlation between multiple points of land cover classes, overcoming the limitations of two-point geostatistical methods, and then the spatial information in the form of multiple-point probability is incorporated into the k-NN classifier. The remotely sensed image of an IKONOS subscene of the Beijing urban area was selected to evaluate the method. The image was object-based classified using the MPk-NN method and several alternatives, including the traditional k-NN, the geostatistically weighted k-NN, the Bayesian method, the decision tree classifier (DTC), and the support vector machine classifier (SVM). It was demonstrated that the MPk-NN approach can achieve greater classification accuracy relative to the alternatives, which are 82.05% and 89.12% based on pixel and object testing data, respectively. Thus, the proposed method is appropriate for object-based classification.

  18. Misperceptions of weight status among adolescents: sociodemographic and behavioral correlates

    Directory of Open Access Journals (Sweden)

    Bodde AE

    2014-12-01

    Full Text Available Amy E Bodde,1 Timothy J Beebe,1 Laura P Chen,2 Sarah Jenkins,3 Kelly Perez-Vergara,4 Lila J Finney Rutten,5 Jeanette Y Ziegenfuss6 1Division of Health Care Policy and Research, Mayo Clinic, Rochester, MN, USA; 2Seattle Children’s Hospital, Seattle, WA, USA; 3Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, USA; 4Children’s Hospital, Boston, MA, USA; 5Division of Epidemiology, Mayo Clinic, Rochester, MN USA; 6HealthPartners Institute for Education and Research, Minneapolis, MN, USA Objective: Accurate perceptions of weight status are important motivational triggers for weight loss among overweight or obese individuals, yet weight misperception is prevalent. To identify and characterize individuals holding misperceptions around their weight status, it may be informative for clinicians to assess self-reported body mass index (BMI classification (ie, underweight, normal, overweight, obese in addition to clinical weight measurement. Methods: Self-reported weight classification data from the 2007 Current Visit Information – Child and Adolescent Survey collected at Mayo Clinic in Rochester, MN, were compared with measured clinical height and weight for 2,993 adolescents. Results: While, overall, 74.2% of adolescents accurately reported their weight status, females, younger adolescents, and proxy (vs self reporters were more accurate. Controlling for demographic and behavioral characteristics, the higher an individual's BMI percentile, the less likely there was agreement between self-report and measured BMI percentile. Those with high BMI who misperceive their weight status were less likely than accurate perceivers to attempt weight loss. Conclusion: Adolescents’ and proxies’ misperception of weight status increases with BMI percentile. Obtaining an adolescent's self-perceived weight status in addition to measured height and weight offers clinicians valuable baseline information to discuss motivation for weight

  19. 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

  20. 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.

  1. Weight loss, weight maintenance, and adaptive thermogenesis.

    Science.gov (United States)

    Camps, Stefan G J A; Verhoef, Sanne P M; Westerterp, Klaas R

    2013-05-01

    Diet-induced weight loss is accompanied by adaptive thermogenesis, ie, a disproportional or greater than expected reduction of resting metabolic rate (RMR). The aim of this study was to investigate whether adaptive thermogenesis is sustained during weight maintenance after weight loss. Subjects were 22 men and 69 women [mean ± SD age: 40 ± 9 y; body mass index (BMI; in kg/m(2)): 31.9 ± 3.0]. They followed a very-low-energy diet for 8 wk, followed by a 44-wk period of weight maintenance. Body composition was assessed with a 3-compartment model based on body weight, total body water (deuterium dilution), and body volume. RMR was measured (RMRm) with a ventilated hood. In addition, RMR was predicted (RMRp) on the basis of the measured body composition: RMRp (MJ/d) = 0.024 × fat mass (kg) + 0.102 × fat-free mass (kg) + 0.85. Measurements took place before the diet and 8, 20, and 52 wk after the start of the diet. The ratio of RMRm to RMRp decreased from 1.004 ± 0.077 before the diet to 0.963 ± 0.073 after the diet (P after 20 wk (0.983 ± 0.063; P weight loss after 8 wk (P Weight loss results in adaptive thermogenesis, and there is no indication for a change in adaptive thermogenesis up to 1 y, when weight loss is maintained. This trial was registered at clinicaltrials.gov as NCT01015508.

  2. 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.

  3. Text Categorization Based on K-Nearest Neighbor Approach for Web Site Classification.

    Science.gov (United States)

    Kwon, Oh-Woog; Lee, Jong-Hyeok

    2003-01-01

    Discusses text categorization and Web site classification and proposes a three-step classification system that includes the use of Web pages linked with the home page. Highlights include the k-nearest neighbor (k-NN) approach; improving performance with a feature selection method and a term weighting scheme using HTML tags; and similarity…

  4. Sequence Classification: 389042 [

    Lifescience Database Archive (English)

    Full Text Available Non-TMB TMH TMB TMB TMB Non-TMB >gi|31793553|ref|NP_856046.1| LOW MOLECULAR WEIGHT ANTI...GEN CFP2 (LOW MOLECULAR WEIGHT PROTEIN ANTIGEN 2) (CFP-2) || http://www.ncbi.nlm.nih.gov/protein/31793553 ...

  5. Weighted-Fusion-Based Representation Classifiers for Hyperspectral Imagery

    Directory of Open Access Journals (Sweden)

    Bing Peng

    2015-11-01

    Full Text Available Spatial texture features have been demonstrated to be very useful for the recently-proposed representation-based classifiers, such as the sparse representation-based classifier (SRC and nearest regularized subspace (NRS. In this work, a weighted residual-fusion-based strategy with multiple features is proposed for these classifiers. Multiple features include local binary patterns (LBP, Gabor features, and the original spectral signatures. In the proposed classification framework, representation residuals for a testing pixel from using each type of features are weighted to generate the final representation residual, and then the label of the testing pixel is determined according to the class yielding the minimum final residual. The motivation of this work is that different features represent pixels from different perspectives and their fusion in the residual domain can enhance the discriminative ability. Experimental results of several real hyperspectral image datasets demonstrate that the proposed residual-based fusion outperforms the original NRS, SRC, support vector machine (SVM with LBP, and SVM with Gabor features, even in small-sample-size (SSS situations.

  6. Interpolatory Weighted-H2 Model Reduction

    CERN Document Server

    Anic, Branimir; Gugercin, Serkan; Antoulas, Athanasios C

    2012-01-01

    This paper introduces an interpolation framework for the weighted-H2 model reduction problem. We obtain a new representation of the weighted-H2 norm of SISO systems that provides new interpolatory first order necessary conditions for an optimal reduced-order model. The H2 norm representation also provides an error expression that motivates a new weighted-H2 model reduction algorithm. Several numerical examples illustrate the effectiveness of the proposed approach.

  7. Dietary protein, weight loss, and weight maintenance.

    Science.gov (United States)

    Westerterp-Plantenga, M S; Nieuwenhuizen, A; Tomé, D; Soenen, S; Westerterp, K R

    2009-01-01

    The role of dietary protein in weight loss and weight maintenance encompasses influences on crucial targets for body weight regulation, namely satiety, thermogenesis, energy efficiency, and body composition. Protein-induced satiety may be mainly due to oxidation of amino acids fed in excess, especially in diets with "incomplete" proteins. Protein-induced energy expenditure may be due to protein and urea synthesis and to gluconeogenesis; "complete" proteins having all essential amino acids show larger increases in energy expenditure than do lower-quality proteins. With respect to adverse effects, no protein-induced effects are observed on net bone balance or on calcium balance in young adults and elderly persons. Dietary protein even increases bone mineral mass and reduces incidence of osteoporotic fracture. During weight loss, nitrogen intake positively affects calcium balance and consequent preservation of bone mineral content. Sulphur-containing amino acids cause a blood pressure-raising effect by loss of nephron mass. Subjects with obesity, metabolic syndrome, and type 2 diabetes are particularly susceptible groups. This review provides an overview of how sustaining absolute protein intake affects metabolic targets for weight loss and weight maintenance during negative energy balance, i.e., sustaining satiety and energy expenditure and sparing fat-free mass, resulting in energy inefficiency. However, the long-term relationship between net protein synthesis and sparing fat-free mass remains to be elucidated.

  8. 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

  9. Weight gain - unintentional

    Science.gov (United States)

    ... be due to menstruation, heart or kidney failure, preeclampsia, or medicines you take. A rapid weight gain ... al. Position of the American Dietetic Association: weight management. J Am Diet Assoc . 2009;109:330-46. ...

  10. Weight management in pregnancy

    OpenAIRE

    Olander, E. K.

    2015-01-01

    Key learning points: - Women who start pregnancy in an overweight or obese weight category have increased health risks - Irrespective of pre-pregnancy weight category, there are health risks associated with gaining too much weight in pregnancy for both mother and baby - 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

  11. Validation and Classification of Web Services using Equalization Validation Classification

    Directory of Open Access Journals (Sweden)

    ALAMELU MUTHUKRISHNAN

    2012-12-01

    Full Text Available In the business process world, web services present a managed and middleware to connect huge number of services. Web service transaction is a mechanism to compose services with their desired quality parameters. If enormous transactions occur, the provider could not acquire the accurate data at the correct time. So it is necessary to reduce the overburden of web service t ransactions. In order to reduce the excess of transactions form customers to providers, this paper propose a new method called Equalization Validation Classification. This method introduces a new weight - reducing algorithm called Efficient Trim Down algorit hm to reduce the overburden of the incoming client requests. When this proposed algorithm is compared with Decision tree algorithms of (J48, Random Tree, Random Forest, AD Tree it produces a better accuracy and Validation than the existing algorithms. The proposed trimming method was analyzed with the Decision tree algorithms and the results implementation shows that the ETD algorithm provides better performance in terms of improved accuracy with Effective Validation. Therefore, the proposed method provide s a good gateway to reduce the overburden of the client requests in web services. Moreover analyzing the requests arrived from a vast number of clients and preventing the illegitimate requests save the service provider time

  12. 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 ...

  13. Class Discovery in Galaxy Classification

    CERN Document Server

    Bazell, D; Bazell, David; Miller, David J.

    2004-01-01

    In recent years, automated, supervised classification techniques have been fruitfully applied to labeling and organizing large astronomical databases. These methods require off-line classifier training, based on labeled examples from each of the (known) object classes. In practice, only a small batch of labeled examples, hand-labeled by a human expert, may be available for training. Moreover, there may be no labeled examples for some classes present in the data, i.e. the database may contain several unknown classes. Unknown classes may be present due to 1) uncertainty in or lack of knowledge of the measurement process, 2) an inability to adequately ``survey'' a massive database to assess its content (classes), and/or 3) an incomplete scientific hypothesis. In recent work, new class discovery in mixed labeled/unlabeled data was formally posed, with a proposed solution based on mixture models. In this work we investigate this approach, propose a competing technique suitable for class discovery in neural network...

  14. Weight Representations of Admissible Affine Vertex Algebras

    Science.gov (United States)

    Arakawa, Tomoyuki; Futorny, Vyacheslav; Ramirez, Luis Enrique

    2017-08-01

    For an admissible affine vertex algebra {V_k{(\\mathfrak{g})}} of type A, we describe a new family of relaxed highest weight representations of {V_k{(\\mathfrak{g})}}. They are simple quotients of representations of the affine Kac-Moody algebra {\\widehat{\\mathfrak{g}}} induced from the following {\\mathfrak{g}}-modules: (1) generic Gelfand-Tsetlin modules in the principal nilpotent orbit, in particular all such modules induced from {\\mathfrak{sl}_2}; (2) all Gelfand-Tsetlin modules in the principal nilpotent orbit that are induced from {\\mathfrak{sl}_3}; (3) all simple Gelfand-Tsetlin modules over {\\mathfrak{sl}_3}. This in particular gives the classification of all simple positive energy weight representations of {V_k{(\\mathfrak{g})}} with finite dimensional weight spaces for {\\mathfrak{g}=\\mathfrak{sl}_3}.

  15. Galaxy Zoo: quantitative visual morphological classifications for 48 000 galaxies from CANDELS

    Science.gov (United States)

    Simmons, B. D.; Lintott, Chris; Willett, Kyle W.; Masters, Karen L.; Kartaltepe, Jeyhan S.; Häußler, Boris; Kaviraj, Sugata; Krawczyk, Coleman; Kruk, S. J.; McIntosh, Daniel H.; Smethurst, R. J.; Nichol, Robert C.; Scarlata, Claudia; Schawinski, Kevin; Conselice, Christopher J.; Almaini, Omar; Ferguson, Henry C.; Fortson, Lucy; Hartley, William; Kocevski, Dale; Koekemoer, Anton M.; Mortlock, Alice; Newman, Jeffrey A.; Bamford, Steven P.; Grogin, N. A.; Lucas, Ray A.; Hathi, Nimish P.; McGrath, Elizabeth; Peth, Michael; Pforr, Janine; Rizer, Zachary; Wuyts, Stijn; Barro, Guillermo; Bell, Eric F.; Castellano, Marco; Dahlen, Tomas; Dekel, Avishai; Ownsworth, Jamie; Faber, Sandra M.; Finkelstein, Steven L.; Fontana, Adriano; Galametz, Audrey; Grützbauch, Ruth; Koo, David; Lotz, Jennifer; Mobasher, Bahram; Mozena, Mark; Salvato, Mara; Wiklind, Tommy

    2017-02-01

    We present quantified visual morphologies of approximately 48 000 galaxies observed in three Hubble Space Telescope legacy fields by the Cosmic Assembly Near-infrared Deep Extragalactic Legacy Survey (CANDELS) and classified by participants in the Galaxy Zoo project. 90 per cent of galaxies have z ≤ 3 and are observed in rest-frame optical wavelengths by CANDELS. Each galaxy received an average of 40 independent classifications, which we combine into detailed morphological information on galaxy features such as clumpiness, bar instabilities, spiral structure, and merger and tidal signatures. We apply a consensus-based classifier weighting method that preserves classifier independence while effectively down-weighting significantly outlying classifications. After analysing the effect of varying image depth on reported classifications, we also provide depth-corrected classifications which both preserve the information in the deepest observations and also enable the use of classifications at comparable depths across the full survey. Comparing the Galaxy Zoo classifications to previous classifications of the same galaxies shows very good agreement; for some applications, the high number of independent classifications provided by Galaxy Zoo provides an advantage in selecting galaxies with a particular morphological profile, while in others the combination of Galaxy Zoo with other classifications is a more promising approach than using any one method alone. We combine the Galaxy Zoo classifications of `smooth' galaxies with parametric morphologies to select a sample of featureless discs at 1 ≤ z ≤ 3, which may represent a dynamically warmer progenitor population to the settled disc galaxies seen at later epochs.

  16. Comparing two classifications of cancer cachexia and their association with survival in patients with unresected pancreatic cancer.

    Science.gov (United States)

    Wesseltoft-Rao, Nima; Hjermstad, Marianne J; Ikdahl, Tone; Dajani, Olav; Ulven, Stine M; Iversen, Per Ole; Bye, Asta

    2015-01-01

    There is no universally accepted definition of cancer cachexia. Two classifications have been proposed; the 3-factor classification requiring ≥ 2 of 3 factors; weight loss ≥ 10%, food intake ≤ 1500 kcal/day, and C-reactive protein ≥ 10 mg/l, and the consensus classification requiring weight loss >5% the past 6 mo, or body mass index 2%. Precachexia is the initial stage of the cachexia trajectory, identified by weight loss ≤ 5%, anorexia and metabolic change. We examined the consistency between the 2 classifications, and their association with survival in a palliative cohort of 45 (25 men, median age of 72 yr, range 35-89) unresected pancreatic cancer patients. Computed tomography images were used to determine sarcopenia. Height/weight/C-reactive protein and survival were extracted from medical records. Food intake was self-reported. The agreement for cachexia and noncachexia was 78% across classifications. Survival was poorer in cachexia compared to noncachexia (3-factor classification, P = 0.0052; consensus classification, P = 0.056; when precachexia was included in the consensus classification, P = 0.027). Both classifications showed a trend toward lower median survival (P cachexia. In conclusion, the two classifications showed good overall agreement in defining cachectic pancreatic cancer patients, and cachexia was associated with poorer survival according to both.

  17. 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.

  18. Weighted Watson-Crick automata

    Science.gov (United States)

    Tamrin, Mohd Izzuddin Mohd; Turaev, Sherzod; Sembok, Tengku Mohd Tengku

    2014-07-01

    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.

  19. Bosniak classification system

    DEFF Research Database (Denmark)

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

    2016-01-01

    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...... one category lower. Pathologic correlation in six lesions revealed four malignant and two benign lesions. CONCLUSION: CEUS and MR both up- and downgraded renal cysts compared to CT, and until these non-radiation modalities have been refined and adjusted, CT should remain the gold standard...

  20. BIRADS classification in mammography.

    Science.gov (United States)

    Balleyguier, Corinne; Ayadi, Salma; Van Nguyen, Kim; Vanel, Daniel; Dromain, Clarisse; Sigal, Robert

    2007-02-01

    The Breast Imaging Report and Data System (BIRADS) of the American College of Radiology (ACR) is today largely used in most of the countries where breast cancer screening is implemented. It is a tool defined to reduce variability between radiologists when creating the reports in mammography, ultrasonography or MRI. Some changes in the last version of the BIRADStrade mark have been included to reduce the inaccuracy of some categories, especially for category 4. The BIRADStrade mark includes a lexicon and descriptive diagrams of the anomalies, recommendations for the mammographic report as well as councils and examples of mammographic cases. This review describes the mammographic items of the BIRADS classification with its more recent developments, while detailing the advantages and limits of this classification.