Development of stump utilization in Finland

Energy Technology Data Exchange (ETDEWEB)

Karkkainen, M

1975-01-01

Presents a historical review of the utilization of stump- and rot-wood in Finland, based on Finnish literature from the mid 19th century until to-day. Pine stumps were used for tar production to a small extent during the 19th century, and on a much larger scale during the two World Wars. Other industrial uses of stumpwood have hitherto been of minor importance, but stumps are now beginning to be used in the pulp industry. The largest quantity of stumpwood used has always been that taken by the rural population for fuel; it amounted to >200 000 m/sup 3/ solid measure in the 1930's, and was still >100 000 m/sup 3/ in the 1960's.

Testing two novel stump-lifting heads in a final felling Norway spruce stand

Energy Technology Data Exchange (ETDEWEB)

Kaerhae, K. (Metsaeteho Oy, Helsinki (Finland)), Email: kalle.karha@metsateho.fi; Mutikainen, A. (TTS Research, Rajamaeki (Finland)), Email: arto.mutikainen@tts.fi

2009-07-01

The use of stump and root wood chips has increased very rapidly in the 21st century in Finland: in the year 2000, the total consumption of stump wood chips for energy generation was 10 GWh, while in 2008 it was around 1.2 TWh. Metsaeteho Oy and TTS Research tested two new stump-lifting devices for lifting stumps in a final felling Norway spruce (picea abies) stand. In the time study with the Vaekevae Stump Processor lifting head, the productivity of stump lifting was 7,5 m3 / E{sub 0}-hour when lifting spruce stumps with a diameter of 30 cm from clayey soil, and 8.3 m3 /E{sub 0}-hour when lifting spruce stumps from sandy soil. When lifting stumps with a diameter of 40 cm, the stump-lifting productivity was 9.0 m3 /E{sub 0}-h (clay) and 10,5 m3 / E{sub 0}-h (sand). The results of this relatively restricted test indicated that the Vaekevae Stump Processor is s reliable and effective stump-lifting head that enables the harvesting of high-quality stump raw material for energy generation. The stump lifting productivity of the other lifting head (Jaervinen) was lower than that of the Vaekevae Strump Processor. Some development suggestions for the Jaervinen lifting head were presented and discussed. (orig.)

Proposed Terminology and Classification of Pre-Malignant Neoplastic Conditions: A Consensus Proposal

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Peter Valent

2017-12-01

Full Text Available Cancer evolution is a step-wise non-linear process that may start early in life or later in adulthood, and includes pre-malignant (indolent and malignant phases. Early somatic changes may not be detectable or are found by chance in apparently healthy individuals. The same lesions may be detected in pre-malignant clonal conditions. In some patients, these lesions may never become relevant clinically whereas in others, they act together with additional pro-oncogenic hits and thereby contribute to the formation of an overt malignancy. Although some pre-malignant stages of a malignancy have been characterized, no global system to define and to classify these conditions is available. To discuss open issues related to pre-malignant phases of neoplastic disorders, a working conference was organized in Vienna in August 2015. The outcomes of this conference are summarized herein and include a basic proposal for a nomenclature and classification of pre-malignant conditions. This proposal should assist in the communication among patients, physicians and scientists, which is critical as genome-sequencing will soon be offered widely for early cancer-detection.

Thirteen Year Loblolly Pine Growth Following Machine Application of Cut-Stump Treament Herbicides For Hardwood Stump-Sprout Control

Science.gov (United States)

Clyde G. Vidrine; John C. Adams

2002-01-01

Thirteen year growth results of 1-0 out-planted loblolly pine seedlings on nonintensively prepared up-land mixed pine-hardwood sites receiving machine applied cut-stump treatment (CST) herbicides onto hardwood stumps at the time of harvesting is presented. Plantation pine growth shows significantly higher growth for pine in the CST treated plots compared to non-CST...

A New Feature Ensemble with a Multistage Classification Scheme for Breast Cancer Diagnosis

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Idil Isikli Esener

2017-01-01

Full Text Available A new and effective feature ensemble with a multistage classification is proposed to be implemented in a computer-aided diagnosis (CAD system for breast cancer diagnosis. A publicly available mammogram image dataset collected during the Image Retrieval in Medical Applications (IRMA project is utilized to verify the suggested feature ensemble and multistage classification. In achieving the CAD system, feature extraction is performed on the mammogram region of interest (ROI images which are preprocessed by applying a histogram equalization followed by a nonlocal means filtering. The proposed feature ensemble is formed by concatenating the local configuration pattern-based, statistical, and frequency domain features. The classification process of these features is implemented in three cases: a one-stage study, a two-stage study, and a three-stage study. Eight well-known classifiers are used in all cases of this multistage classification scheme. Additionally, the results of the classifiers that provide the top three performances are combined via a majority voting technique to improve the recognition accuracy on both two- and three-stage studies. A maximum of 85.47%, 88.79%, and 93.52% classification accuracies are attained by the one-, two-, and three-stage studies, respectively. The proposed multistage classification scheme is more effective than the single-stage classification for breast cancer diagnosis.

Cancer Feature Selection and Classification Using a Binary Quantum-Behaved Particle Swarm Optimization and Support Vector Machine

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Maolong Xi

2016-01-01

Full Text Available This paper focuses on the feature gene selection for cancer classification, which employs an optimization algorithm to select a subset of the genes. We propose a binary quantum-behaved particle swarm optimization (BQPSO for cancer feature gene selection, coupling support vector machine (SVM for cancer classification. First, the proposed BQPSO algorithm is described, which is a discretized version of original QPSO for binary 0-1 optimization problems. Then, we present the principle and procedure for cancer feature gene selection and cancer classification based on BQPSO and SVM with leave-one-out cross validation (LOOCV. Finally, the BQPSO coupling SVM (BQPSO/SVM, binary PSO coupling SVM (BPSO/SVM, and genetic algorithm coupling SVM (GA/SVM are tested for feature gene selection and cancer classification on five microarray data sets, namely, Leukemia, Prostate, Colon, Lung, and Lymphoma. The experimental results show that BQPSO/SVM has significant advantages in accuracy, robustness, and the number of feature genes selected compared with the other two algorithms.

Cancer Feature Selection and Classification Using a Binary Quantum-Behaved Particle Swarm Optimization and Support Vector Machine

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Sun, Jun; Liu, Li; Fan, Fangyun; Wu, Xiaojun

2016-01-01

This paper focuses on the feature gene selection for cancer classification, which employs an optimization algorithm to select a subset of the genes. We propose a binary quantum-behaved particle swarm optimization (BQPSO) for cancer feature gene selection, coupling support vector machine (SVM) for cancer classification. First, the proposed BQPSO algorithm is described, which is a discretized version of original QPSO for binary 0-1 optimization problems. Then, we present the principle and procedure for cancer feature gene selection and cancer classification based on BQPSO and SVM with leave-one-out cross validation (LOOCV). Finally, the BQPSO coupling SVM (BQPSO/SVM), binary PSO coupling SVM (BPSO/SVM), and genetic algorithm coupling SVM (GA/SVM) are tested for feature gene selection and cancer classification on five microarray data sets, namely, Leukemia, Prostate, Colon, Lung, and Lymphoma. The experimental results show that BQPSO/SVM has significant advantages in accuracy, robustness, and the number of feature genes selected compared with the other two algorithms. PMID:27642363

A protein and mRNA expression-based classification of gastric cancer.

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Setia, Namrata; Agoston, Agoston T; Han, Hye S; Mullen, John T; Duda, Dan G; Clark, Jeffrey W; Deshpande, Vikram; Mino-Kenudson, Mari; Srivastava, Amitabh; Lennerz, Jochen K; Hong, Theodore S; Kwak, Eunice L; Lauwers, Gregory Y

2016-07-01

The overall survival of gastric carcinoma patients remains poor despite improved control over known risk factors and surveillance. This highlights the need for new classifications, driven towards identification of potential therapeutic targets. Using sophisticated molecular technologies and analysis, three groups recently provided genetic and epigenetic molecular classifications of gastric cancer (The Cancer Genome Atlas, 'Singapore-Duke' study, and Asian Cancer Research Group). Suggested by these classifications, here, we examined the expression of 14 biomarkers in a cohort of 146 gastric adenocarcinomas and performed unsupervised hierarchical clustering analysis using less expensive and widely available immunohistochemistry and in situ hybridization. Ultimately, we identified five groups of gastric cancers based on Epstein-Barr virus (EBV) positivity, microsatellite instability, aberrant E-cadherin, and p53 expression; the remaining cases constituted a group characterized by normal p53 expression. In addition, the five categories correspond to the reported molecular subgroups by virtue of clinicopathologic features. Furthermore, evaluation between these clusters and survival using the Cox proportional hazards model showed a trend for superior survival in the EBV and microsatellite-instable related adenocarcinomas. In conclusion, we offer as a proposal a simplified algorithm that is able to reproduce the recently proposed molecular subgroups of gastric adenocarcinoma, using immunohistochemical and in situ hybridization techniques.

Fluorescently labeled bevacizumab in human breast cancer: defining the classification threshold

Science.gov (United States)

Koch, Maximilian; de Jong, Johannes S.; Glatz, Jürgen; Symvoulidis, Panagiotis; Lamberts, Laetitia E.; Adams, Arthur L. L.; Kranendonk, Mariëtte E. G.; Terwisscha van Scheltinga, Anton G. T.; Aichler, Michaela; Jansen, Liesbeth; de Vries, Jakob; Lub-de Hooge, Marjolijn N.; Schröder, Carolien P.; Jorritsma-Smit, Annelies; Linssen, Matthijs D.; de Boer, Esther; van der Vegt, Bert; Nagengast, Wouter B.; Elias, Sjoerd G.; Oliveira, Sabrina; Witkamp, Arjen J.; Mali, Willem P. Th. M.; Van der Wall, Elsken; Garcia-Allende, P. Beatriz; van Diest, Paul J.; de Vries, Elisabeth G. E.; Walch, Axel; van Dam, Gooitzen M.; Ntziachristos, Vasilis

2017-07-01

In-vivo fluorescently labelled drug (bevacizumab) breast cancer specimen where obtained from patients. We propose a new structured method to determine the optimal classification threshold in targeted fluorescence intra-operative imaging.

Proposed Terminology and Classification of Pre-Malignant Neoplastic Conditions: A Consensus Proposal.

Science.gov (United States)

Valent, Peter; Akin, Cem; Arock, Michel; Bock, Christoph; George, Tracy I; Galli, Stephen J; Gotlib, Jason; Haferlach, Torsten; Hoermann, Gregor; Hermine, Olivier; Jäger, Ulrich; Kenner, Lukas; Kreipe, Hans; Majeti, Ravindra; Metcalfe, Dean D; Orfao, Alberto; Reiter, Andreas; Sperr, Wolfgang R; Staber, Philipp B; Sotlar, Karl; Schiffer, Charles; Superti-Furga, Giulio; Horny, Hans-Peter

2017-12-01

Cancer evolution is a step-wise non-linear process that may start early in life or later in adulthood, and includes pre-malignant (indolent) and malignant phases. Early somatic changes may not be detectable or are found by chance in apparently healthy individuals. The same lesions may be detected in pre-malignant clonal conditions. In some patients, these lesions may never become relevant clinically whereas in others, they act together with additional pro-oncogenic hits and thereby contribute to the formation of an overt malignancy. Although some pre-malignant stages of a malignancy have been characterized, no global system to define and to classify these conditions is available. To discuss open issues related to pre-malignant phases of neoplastic disorders, a working conference was organized in Vienna in August 2015. The outcomes of this conference are summarized herein and include a basic proposal for a nomenclature and classification of pre-malignant conditions. This proposal should assist in the communication among patients, physicians and scientists, which is critical as genome-sequencing will soon be offered widely for early cancer-detection. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Relation of Stump Length with Various Gait Parameters in Trans-tibial Amputee

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Koyel Majumdar

2008-07-01

Full Text Available The purpose of this paper is evaluating the impact of stump length of unilateral below knee amputees (BKA on different gait parameters. Nine unilateral BKA were chosen and divided into three groups comprising patients with short, medium, and long stump length. Each of them underwent gait analysis test by Computer Dynography (CDG system to measure the gait parameters. It was found that the ground reaction force is higher in the patients with medium stump length whereas the velocity, step length both for the prosthetic and sound limb and cadence were high in longer stump length. Statistical analysis shows a significant difference (p<0.05 between the gait parameters of BKA with medium and longer stump length. The patients with longer stump length were more efficient than medium and short stump patients as they consumed comparatively lesser energy while walking with self-selected velocity and conventional (Solid ankle cushioned heel SACH foot.

Association between gastric cancer and the Kyoto classification of gastritis.

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Shichijo, Satoki; Hirata, Yoshihiro; Niikura, Ryota; Hayakawa, Yoku; Yamada, Atsuo; Koike, Kazuhiko

2017-09-01

Histological gastritis is associated with gastric cancer, but its diagnosis requires biopsy. Many classifications of endoscopic gastritis are available, but not all are useful for risk stratification of gastric cancer. The Kyoto Classification of Gastritis was proposed at the 85th Congress of the Japan Gastroenterological Endoscopy Society. This cross-sectional study evaluated the usefulness of the Kyoto Classification of Gastritis for risk stratification of gastric cancer. From August 2013 to September 2014, esophagogastroduodenoscopy was performed and the gastric findings evaluated according to the Kyoto Classification of Gastritis in a total of 4062 patients. The following five endoscopic findings were selected based on previous reports: atrophy, intestinal metaplasia, enlarged folds, nodularity, and diffuse redness. A total of 3392 patients (1746 [51%] men and 1646 [49%] women) were analyzed. Among them, 107 gastric cancers were diagnosed. Atrophy was found in 2585 (78%) and intestinal metaplasia in 924 (27%). Enlarged folds, nodularity, and diffuse redness were found in 197 (5.8%), 22 (0.6%), and 573 (17%), respectively. In univariate analyses, the severity of atrophy, intestinal metaplasia, diffuse redness, age, and male sex were associated with gastric cancer. In a multivariate analysis, atrophy and male sex were found to be independent risk factors. Younger age and severe atrophy were determined to be associated with diffuse-type gastric cancer. Endoscopic detection of atrophy was associated with the risk of gastric cancer. Thus, patients with severe atrophy should be examined carefully and may require intensive follow-up. © 2017 Journal of Gastroenterology and Hepatology Foundation and John Wiley & Sons Australia, Ltd.

Proteomic classification of breast cancer.

LENUS (Irish Health Repository)

Kamel, Dalia

2012-11-01

Being a significant health problem that affects patients in various age groups, breast cancer has been extensively studied to date. Recently, molecular breast cancer classification has advanced significantly with the availability of genomic profiling technologies. Proteomic technologies have also advanced from traditional protein assays including enzyme-linked immunosorbent assay, immunoblotting and immunohistochemistry to more comprehensive approaches including mass spectrometry and reverse phase protein lysate arrays (RPPA). The purpose of this manuscript is to review the current protein markers that influence breast cancer prediction and prognosis and to focus on novel advances in proteomic classification of breast cancer.

Three-class classification in computer-aided diagnosis of breast cancer by support vector machine

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Sun, Xuejun; Qian, Wei; Song, Dansheng

2004-05-01

Design of classifier in computer-aided diagnosis (CAD) scheme of breast cancer plays important role to its overall performance in sensitivity and specificity. Classification of a detected object as malignant lesion, benign lesion, or normal tissue on mammogram is a typical three-class pattern recognition problem. This paper presents a three-class classification approach by using two-stage classifier combined with support vector machine (SVM) learning algorithm for classification of breast cancer on mammograms. The first classification stage is used to detect abnormal areas and normal breast tissues, and the second stage is for classification of malignant or benign in detected abnormal objects. A series of spatial, morphology and texture features have been extracted on detected objects areas. By using genetic algorithm (GA), different feature groups for different stage classification have been investigated. Computerized free-response receiver operating characteristic (FROC) and receiver operating characteristic (ROC) analyses have been employed in different classification stages. Results have shown that obvious performance improvement in both sensitivity and specificity was observed through proposed classification approach compared with conventional two-class classification approaches, indicating its effectiveness in classification of breast cancer on mammograms.

Occurrence patterns of lichens on stumps in young managed forests.

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Svensson, Måns; Dahlberg, Anders; Ranius, Thomas; Thor, Göran

2013-01-01

The increasing demand for forest-derived bio-fuel may decrease the amount of dead wood and hence also the amount of available substrate for saproxylic ( = dead-wood dependent) organisms. Cut stumps constitute a large portion of dead wood in managed boreal forests. The lichen flora of such stumps has received little interest. Therefore, we investigated which lichens that occur on stumps in young (4-19 years), managed forests and analyzed how species richness and occurrence of individual species were related to stump and stand characteristics. We performed lichen inventories of 576 Norway spruce stumps in 48 forest stands in two study areas in Central Sweden, recording in total 77 lichen species. Of these, 14 were obligately lignicolous, while the remaining were generalists that also grow on bark, soil or rocks. We tested the effect of characteristics reflecting successional stage, microclimate, substrate patch size, and the species pool in the surrounding area on (1) total lichen species richness, (2) species richness of obligately lignicolous lichens and (3) the occurrence of four obligately lignicolous lichen species. The most important variables were stump age, with more species on old stumps, and study area, with similar total species richness but differences in occupancy for individual species. Responses for total lichen species richness and species richness of obligately lignicolous lichens were overall similar, indicating similar ecological requirements of these two groups. Our results indicate that species richness measurements serve as poor proxies for the responses of individual, obligately lignicolous lichen species.

Occurrence patterns of lichens on stumps in young managed forests.

Directory of Open Access Journals (Sweden)

Måns Svensson

Full Text Available The increasing demand for forest-derived bio-fuel may decrease the amount of dead wood and hence also the amount of available substrate for saproxylic ( = dead-wood dependent organisms. Cut stumps constitute a large portion of dead wood in managed boreal forests. The lichen flora of such stumps has received little interest. Therefore, we investigated which lichens that occur on stumps in young (4-19 years, managed forests and analyzed how species richness and occurrence of individual species were related to stump and stand characteristics. We performed lichen inventories of 576 Norway spruce stumps in 48 forest stands in two study areas in Central Sweden, recording in total 77 lichen species. Of these, 14 were obligately lignicolous, while the remaining were generalists that also grow on bark, soil or rocks. We tested the effect of characteristics reflecting successional stage, microclimate, substrate patch size, and the species pool in the surrounding area on (1 total lichen species richness, (2 species richness of obligately lignicolous lichens and (3 the occurrence of four obligately lignicolous lichen species. The most important variables were stump age, with more species on old stumps, and study area, with similar total species richness but differences in occupancy for individual species. Responses for total lichen species richness and species richness of obligately lignicolous lichens were overall similar, indicating similar ecological requirements of these two groups. Our results indicate that species richness measurements serve as poor proxies for the responses of individual, obligately lignicolous lichen species.

Stump treatment against Heterobasidion annosum - Techniques and biological effect in practical forestry

Energy Technology Data Exchange (ETDEWEB)

Thor, M. [SkogForsk, Uppsala (Sweden)

1997-12-31

This thesis summarises and discusses results from two studies on mechanized stump treatment to control the root rot fungus Heterobasidion annosum (Fr.) Bref. In Sweden, stump treatment is at present carried out with two chemical compounds, urea and disodium octaborate tetrahydrate (DOT), and a biological control agent, Phlebiopsis gigantea (Fr.) Juel. The first study investigated the H. annosum colonization of Norway spruce (Picea abies (L.) Karst) stumps following mechanized thinning and stump treatment with the three control agents mentioned. The stumps were treated in the summer and were compared with untreated stumps, cut in the summer and winter, respectively. Experimental plots were established in 12 first thinning stands of Norway spruce. Six to seven weeks after thinning and treatment, sample discs were collected (N=1246) and examined for presence of H. annosum. Stump treatment with any of the control agents reduced the colonized stump area 6-7 weeks after thinning by 88-98% as compared with untreated stumps cut in the summer. The effects of the different treatments differed neither from each other nor from the effect of winter thinning. The variation between the stands was considerable, but mechanized stump treatment provided as good protection as manual treatment against H. annosum infections. Study II examined the survival of P. gigantea oidiospores in aqueous suspension when exposed to high temperature or pressure, which are potential problems in mechanized application. In the laboratory, temperatures of 20, 30 or 35 deg C did not affect the survival. The spores could withstand 40 deg C for a short period, but died at 60 deg C. Pressure of up to 2 200 kPa for 24 h did not affect P. gigantea spore germination. In the field, temperatures of the working suspension (10{sup 7} spores I{sup -1}) was assessed during practical operations. Spore viability was maintained through the applicator system. As long as the prescriptions are followed up to the time of

BCDForest: a boosting cascade deep forest model towards the classification of cancer subtypes based on gene expression data.

Science.gov (United States)

Guo, Yang; Liu, Shuhui; Li, Zhanhuai; Shang, Xuequn

2018-04-11

The classification of cancer subtypes is of great importance to cancer disease diagnosis and therapy. Many supervised learning approaches have been applied to cancer subtype classification in the past few years, especially of deep learning based approaches. Recently, the deep forest model has been proposed as an alternative of deep neural networks to learn hyper-representations by using cascade ensemble decision trees. It has been proved that the deep forest model has competitive or even better performance than deep neural networks in some extent. However, the standard deep forest model may face overfitting and ensemble diversity challenges when dealing with small sample size and high-dimensional biology data. In this paper, we propose a deep learning model, so-called BCDForest, to address cancer subtype classification on small-scale biology datasets, which can be viewed as a modification of the standard deep forest model. The BCDForest distinguishes from the standard deep forest model with the following two main contributions: First, a named multi-class-grained scanning method is proposed to train multiple binary classifiers to encourage diversity of ensemble. Meanwhile, the fitting quality of each classifier is considered in representation learning. Second, we propose a boosting strategy to emphasize more important features in cascade forests, thus to propagate the benefits of discriminative features among cascade layers to improve the classification performance. Systematic comparison experiments on both microarray and RNA-Seq gene expression datasets demonstrate that our method consistently outperforms the state-of-the-art methods in application of cancer subtype classification. The multi-class-grained scanning and boosting strategy in our model provide an effective solution to ease the overfitting challenge and improve the robustness of deep forest model working on small-scale data. Our model provides a useful approach to the classification of cancer subtypes

Tinea corporis on the stump leg with Trichophyton rubrum infection

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Xin Ran

2015-09-01

Full Text Available We report a case of tinea corporis on amputated leg stump caused by Trichophyton rubrum. The patient, a 54-year-old male, experienced a serious traffic accident, resulted his right leg amputated 3 years ago. Since then prosthesis was fitted and protective equipment of silicone stocking was worn for the stump. He consulted with circular, patchy and scaly erythemas with itching on his right below knee amputation stump for 2 months. The diagnoses of tinea corporis on the stump was made based on a positive KOH direct microscopic examination, morphologic characteristics and sequencing of the internal transcribed spacers (ITS 1 and 4, confirmed that the isolate from the scales was T. rubrum. The patient was cured with oral terbinafine and topical naftifine-ketaconazole cream following 2% ketaconazole shampoo wash for 3 weeks. Long times using prosthesis together with protective equipment of silicone stocking, leading to the local environment of airtight and humid within the prosthesis favors T. rubrum infection of the stump could be considered as the precipitating factors.

Testing Open-Air Storage of Stumps to Provide Clean Biomass for Energy Production

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Luigi Pari

2017-10-01

Full Text Available When orchards reach the end of the productive cycle, the stumps removal becomes a mandatory operation to allow new soil preparation and to establish new cultivations. The exploitation of the removed stump biomass seems a valuable option, especially in the growing energy market of the biofuels; however, the scarce quality of the material obtained after the extraction compromises its marketability, making this product a costly waste to be disposed. In this regard, the identification of affordable strategies for the extraction and the cleaning of the material will be crucial in order to provide to plantation owners the chance to sell the biomass and offset the extraction costs. Mechanical extraction and cleaning technologies have been already tested on forest stumps, but these systems work on the singular piece and would be inefficient in the conditions of an intensive orchard, where stumps are small and numerous. The objective of this study was to test the possibility to exploit a natural stumps cleaning system through open-air storage. The tested stumps were obtained from two different vineyards, extracted with an innovative stump puller specifically designed for continuous stump removal in intensively-planted orchards. The effects of weathering were evaluated to determine the fuel quality immediately after the extraction and after a storage period of six months with respect to moisture content, ash content, and heating value. Results indicated interesting storage performance, showing also different dynamics depending on the stumps utilized.

Rectosigmoid stump washout as an alternative to permanent mucous fistula in patients undergoing subtotal colectomy for ulcerative colitis in emergency settings.

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Pellino, Gianluca; Sciaudone, Guido; Candilio, Giuseppe; Canonico, Silvestro; Selvaggi, Francesco

2012-01-01

Restorative proctocolectomy with ileopouch-anal anastomosis (IPAA) is the treatment of choice for intractable or complicated ulcerative colitis(UC). Elderly patients often present with acute colitis requiring emergent subtotal colectomy(SC). Frail patients are at risk of developing septic complications related to the closed rectosigmoidal stump, often requiring formation of a second stoma to be reversed at the time of completion proctectomy. This carries nuisance to such exhausted patients. We propose a simple and inexpensive trick to avoid the need for creating a mucous fistula. IPAA was performed as a 3-stage procedure in emergency settings. The rectosigmoidal stump was closed and placed subcutaneously; skin was closed over it. After SC, if patients showed signs of stump-related pelvic sepsis, a lavage of the rectal stump with povidone iodine solution and with saline was carried out as a rescue treatment aiming to avoid the need of opening the rectal stump to drain sepsis. Thirty-five patients underwent SC for UC between 1987 and 2012. The skin was closed over the closed stump in the 20. Seven patients out of these 20 experienced early stump-related septic complication. In five cases, we were able to avoid opening of the rectal stump, and a second stoma was unnecessary. After opening the closed stump in the remaining ones, a prompt improving of symptoms was observed. Rectal washout was well tolerated and avoided a second stoma in five out of seven patients, with better quality of life and body perception after IPAA surgery. This is relevant when dealing with geriatric patients, needing to completely recover before undergoing completion proctectomy.

A Rare Case: Appendectomy After Connected Stump Appendicitis Perforation of the Cecum

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Berke Manoglu

2016-01-01

Full Text Available Stump appendicitis is a rare complication after appendectomy . Stump appendicitis made of incomplete appendectomy after a rest appendix tissue develops as a result of the inflammation. Admitted to the emergency department with acute abdomen and a history of appendectomy in patients with a history of current pain in the right lower quadrant , especially that of the patient must be evaluated in terms of stump appendicitis. The fact that the earlier story appendectomy patients , causing a delay in diagnosis and increasing the morbidity Cecal perforation was offered an advanced case of delayed depending on the stump appendicitis in this article.

Cancer classification in the genomic era: five contemporary problems.

Science.gov (United States)

Song, Qingxuan; Merajver, Sofia D; Li, Jun Z

2015-10-19

Classification is an everyday instinct as well as a full-fledged scientific discipline. Throughout the history of medicine, disease classification is central to how we develop knowledge, make diagnosis, and assign treatment. Here, we discuss the classification of cancer and the process of categorizing cancer subtypes based on their observed clinical and biological features. Traditionally, cancer nomenclature is primarily based on organ location, e.g., "lung cancer" designates a tumor originating in lung structures. Within each organ-specific major type, finer subgroups can be defined based on patient age, cell type, histological grades, and sometimes molecular markers, e.g., hormonal receptor status in breast cancer or microsatellite instability in colorectal cancer. In the past 15+ years, high-throughput technologies have generated rich new data regarding somatic variations in DNA, RNA, protein, or epigenomic features for many cancers. These data, collected for increasingly large tumor cohorts, have provided not only new insights into the biological diversity of human cancers but also exciting opportunities to discover previously unrecognized cancer subtypes. Meanwhile, the unprecedented volume and complexity of these data pose significant challenges for biostatisticians, cancer biologists, and clinicians alike. Here, we review five related issues that represent contemporary problems in cancer taxonomy and interpretation. (1) How many cancer subtypes are there? (2) How can we evaluate the robustness of a new classification system? (3) How are classification systems affected by intratumor heterogeneity and tumor evolution? (4) How should we interpret cancer subtypes? (5) Can multiple classification systems co-exist? While related issues have existed for a long time, we will focus on those aspects that have been magnified by the recent influx of complex multi-omics data. Exploration of these problems is essential for data-driven refinement of cancer classification

Tree diameter at breast height in relation to stump diameter by species group

Science.gov (United States)

Arthur G. Horn; Richard C. Keller

1957-01-01

A stump tally is one method of determining the volume of timber previously removed from an area in a logging operation. To estimate volume of standing timber from stumps, foresters must first know the relationship between stump diameters and tree diameters at breast height (d.b.h.).

Marginal artery stump pressure in left colic artery-preserving rectal cancer surgery: a clinical trial.

Science.gov (United States)

Guo, Yuchen; Wang, Daguang; He, Liang; Zhang, Yang; Zhao, Shishun; Zhang, Luyao; Sun, Xuan; Suo, Jian

2017-07-01

The aim of this clinical trial is to evaluate the influence of high and low ligation of the inferior mesenteric artery with apical lymph node dissection on the anastomotic blood supply, lymph node retrieval rate, operative time and anastomotic leakage rate in rectal cancer surgery. A total of 57 Chinese patients were randomly distributed into group A and group B and underwent radical resection of rectal cancer. Patients in group A underwent high ligation of the inferior mesenteric artery, and patients in group B underwent apical lymph node resection around the root of the inferior mesenteric artery with preservation of the left colic artery. The marginal artery stump pressure was measured after colon and artery reconstruction. Systemic pressure, distal colon length, operative time and lymph node retrieval rate were measured and recorded. The results were analysed and related to patient characteristics and post-operative complications. The anastomotic blood supply negatively and linearly correlated with age and distal colon length and showed a positive linear correlation with systemic pressure. Patients who received low ligation with apical lymph node dissection had a better anastomotic blood supply than those who received high ligation. No differences were found in lymph node retrieval rate, operative time and anastomotic leakage rate. Anastomotic leakage was associated with a worse anastomotic blood supply. Low ligation with apical lymph node dissection in rectal cancer treatment provides better anastomotic blood supply but is not associated with differences in node retrieval rate or operation time. © 2015 Royal Australasian College of Surgeons.

Classification of breast cancer histology images using Convolutional Neural Networks.

Directory of Open Access Journals (Sweden)

Teresa Araújo

Full Text Available Breast cancer is one of the main causes of cancer death worldwide. The diagnosis of biopsy tissue with hematoxylin and eosin stained images is non-trivial and specialists often disagree on the final diagnosis. Computer-aided Diagnosis systems contribute to reduce the cost and increase the efficiency of this process. Conventional classification approaches rely on feature extraction methods designed for a specific problem based on field-knowledge. To overcome the many difficulties of the feature-based approaches, deep learning methods are becoming important alternatives. A method for the classification of hematoxylin and eosin stained breast biopsy images using Convolutional Neural Networks (CNNs is proposed. Images are classified in four classes, normal tissue, benign lesion, in situ carcinoma and invasive carcinoma, and in two classes, carcinoma and non-carcinoma. The architecture of the network is designed to retrieve information at different scales, including both nuclei and overall tissue organization. This design allows the extension of the proposed system to whole-slide histology images. The features extracted by the CNN are also used for training a Support Vector Machine classifier. Accuracies of 77.8% for four class and 83.3% for carcinoma/non-carcinoma are achieved. The sensitivity of our method for cancer cases is 95.6%.

Pathohistological classification systems in gastric cancer: diagnostic relevance and prognostic value.

Science.gov (United States)

Berlth, Felix; Bollschweiler, Elfriede; Drebber, Uta; Hoelscher, Arnulf H; Moenig, Stefan

2014-05-21

Several pathohistological classification systems exist for the diagnosis of gastric cancer. Many studies have investigated the correlation between the pathohistological characteristics in gastric cancer and patient characteristics, disease specific criteria and overall outcome. It is still controversial as to which classification system imparts the most reliable information, and therefore, the choice of system may vary in clinical routine. In addition to the most common classification systems, such as the Laurén and the World Health Organization (WHO) classifications, other authors have tried to characterize and classify gastric cancer based on the microscopic morphology and in reference to the clinical outcome of the patients. In more than 50 years of systematic classification of the pathohistological characteristics of gastric cancer, there is no sole classification system that is consistently used worldwide in diagnostics and research. However, several national guidelines for the treatment of gastric cancer refer to the Laurén or the WHO classifications regarding therapeutic decision-making, which underlines the importance of a reliable classification system for gastric cancer. The latest results from gastric cancer studies indicate that it might be useful to integrate DNA- and RNA-based features of gastric cancer into the classification systems to establish prognostic relevance. This article reviews the diagnostic relevance and the prognostic value of different pathohistological classification systems in gastric cancer.

First rotation Eucalyptus macarthurii cut stump control in KwaZulu ...

African Journals Online (AJOL)

Many cold tolerant eucalypts, E. macarthurii in particular, coppice vigorously following harvesting, and in contrast to E. grandis are proving difficult to kill by existing cut stump control methods. Based on past research, selected cut stump treatments were tested on single stem E. macarthurii trees, that had not been coppiced, ...

Using fuzzy association rule mining in cancer classification

International Nuclear Information System (INIS)

Mahmoodian, Hamid; Marhaban, M.H.; Abdulrahim, Raha; Rosli, Rozita; Saripan, Iqbal

2011-01-01

Full text: The classification of the cancer tumors based on gene expression profiles has been extensively studied in numbers of studies. A wide variety of cancer datasets have been implemented by the various methods of gene selec tion and classification to identify the behavior of the genes in tumors and find the relationships between them and outcome of diseases. Interpretability of the model, which is developed by fuzzy rules and linguistic variables in this study, has been rarely considered. In addition, creating a fuzzy classifier with high performance in classification that uses a subset of significant genes which have been selected by different types of gene selection methods is another goal of this study. A new algorithm has been developed to identify the fuzzy rules and significant genes based on fuzzy association rule mining. At first, different subset of genes which have been selected by different methods, were used to generate primary fuzzy classifiers separately and then proposed algorithm was implemented to mix the genes which have been associated in the primary classifiers and generate a new classifier. The results show that fuzzy classifier can classify the tumors with high performance while presenting the relationships between the genes by linguistic variables

X-ray diagnosis of esophageal cancer and application of Borrmann's classification

International Nuclear Information System (INIS)

Chin, Soo Yil

1985-01-01

In 126 cases and who were diagnosed as esophageal cancer and treated by radiation at Cancer Research Hospital, K. A. E. R. I., from January 1974 to July 1979, a study on the x-ray diagnosis of esophageal cancer was carried out mainly as to the type classification. The ordinary classification od esophageal cancer by x-ray picture was reviewed and Borrmann's classification using gastric cancer was tried to apply to the macroscopic classification of esophageal cancer, and also the application of this classification to x-ray diagnosis was discussed. And the effect of radiotherapy as to each type of cancer according to the ordinary x-ray classification and Borrmann's classification was studied too. The results were as follows: 1. The ordinary x-ray classification was not simple, because the degree of progression of cancer, difference of mural invasion, and position and method of radiography could make misinterpretation of the type of cancer and the therapeutic effect by radiation as to each type according to this classification did not represent a significant characteristic too, although the radiation was most effective in the polypoidal type and least effective in funnel type. 2. The Borrmann's classification was relatively easy even on the radiogram because of little overlapping between each type and the type became more evident on the resected specimen after operation. And also some correlation was recognized between the type of Borrmann's classification and radiotherapeutic effect. The effect was best in type I and It was gradually decreased in type II, III, and IV in the other. The radiotherapy was ineffective in about three quarters of type IV. 3. The Borrmann's classification is now employed to the carcinoma of large bowel, as well as to the gastric cancer. If it is applied to the esophageal cancer, the macroscopic classification for the cancer of digestive tract can be systemized and it will be convenient in clinical study.

A novel rat model of brachial plexus injury with nerve root stumps.

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Fang, Jintao; Yang, Jiantao; Yang, Yi; Li, Liang; Qin, Bengang; He, Wenting; Yan, Liwei; Chen, Gang; Tu, Zhehui; Liu, Xiaolin; Gu, Liqiang

2018-02-01

The C5-C6 nerve roots are usually spared from avulsion after brachial plexus injury (BPI) and thus can be used as donors for nerve grafting. To date, there are no appropriate animal models to evaluate spared nerve root stumps. Hence, the aim of this study was to establish and evaluate a rat model with spared nerve root stumps in BPI. In rupture group, the proximal parts of C5-T1 nerve roots were held with the surrounding muscles and the distal parts were pulled by a sudden force after the brachial plexus was fully exposed, and the results were compared with those of sham group. To validate the model, the lengths of C5-T1 spared nerve root stumps were measured and the histologies of the shortest one and the corresponding spinal cord were evaluated. C5 nerve root stump was found to be the shortest. Histology findings demonstrated that the nerve fibers became more irregular and the continuity decreased; numbers and diameters of myelinated axons and thickness of myelin sheaths significantly decreased over time. The survival of motoneurons was reduced, and the death of motoneurons may be related to the apoptotic process. Our model could successfully create BPI model with nerve root stumps by traction, which could simulate injury mechanisms. While other models involve root avulsion or rupturing by distal nerve transection. This model would be suitable for evaluating nerve root stumps and testing new therapeutic strategies for neuroprotection through nerve root stumps in the future. Copyright © 2017. Published by Elsevier B.V.

A Classification Framework Applied to Cancer Gene Expression Profiles

Directory of Open Access Journals (Sweden)

Hussein Hijazi

2013-01-01

Full Text Available Classification of cancer based on gene expression has provided insight into possible treatment strategies. Thus, developing machine learning methods that can successfully distinguish among cancer subtypes or normal versus cancer samples is important. This work discusses supervised learning techniques that have been employed to classify cancers. Furthermore, a two-step feature selection method based on an attribute estimation method (e.g., ReliefF and a genetic algorithm was employed to find a set of genes that can best differentiate between cancer subtypes or normal versus cancer samples. The application of different classification methods (e.g., decision tree, k-nearest neighbor, support vector machine (SVM, bagging, and random forest on 5 cancer datasets shows that no classification method universally outperforms all the others. However, k-nearest neighbor and linear SVM generally improve the classification performance over other classifiers. Finally, incorporating diverse types of genomic data (e.g., protein-protein interaction data and gene expression increase the prediction accuracy as compared to using gene expression alone.

Intercostal muscle flap to protect the bronchial stump in pediatric lobectomy for lung abscess.

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Lisi, Gabriele; Lauriti, Giuseppe; Cascini, Valentina; Lococo, Achille; Chiesa, Pierluigi Lelli

2013-01-01

Lung suppurative diseases in children are usually responsive to medical treatment or percutaneous drainage. Rarely, pulmonary resection is required for lung abscess in childhood, particularly in presence of co-morbidities. In these cases, a lobectomy is usually performed through an open thoracotomy, with a reported incidence of bronco-pleural fistula up to 9.1% of pediatric series. This consequence is mainly due to the inflammatory condition; however the lack of knowledge of pediatric and thoracic surgeons with this rare condition in childhood can also play a role. In adults with lung cancer, the buttressing of bronchial stump with the additional support of an intercostal muscle (ICM) flap has proved to prevent this complication, as well as to reduce post-operative pain. We report the first pediatric experience of ICM flap used in 2 immunocompetent children requiring lobectomy for suppurative lung conditions. Our preliminary experience confirms the feasibility of protecting the bronchial stump after lobectomy in children, especially in conditions at risk for bronco-pleural fistula development.

CrossLink: a novel method for cross-condition classification of cancer subtypes.

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Ma, Chifeng; Sastry, Konduru S; Flore, Mario; Gehani, Salah; Al-Bozom, Issam; Feng, Yusheng; Serpedin, Erchin; Chouchane, Lotfi; Chen, Yidong; Huang, Yufei

2016-08-22

We considered the prediction of cancer classes (e.g. subtypes) using patient gene expression profiles that contain both systematic and condition-specific biases when compared with the training reference dataset. The conventional normalization-based approaches cannot guarantee that the gene signatures in the reference and prediction datasets always have the same distribution for all different conditions as the class-specific gene signatures change with the condition. Therefore, the trained classifier would work well under one condition but not under another. To address the problem of current normalization approaches, we propose a novel algorithm called CrossLink (CL). CL recognizes that there is no universal, condition-independent normalization mapping of signatures. In contrast, it exploits the fact that the signature is unique to its associated class under any condition and thus employs an unsupervised clustering algorithm to discover this unique signature. We assessed the performance of CL for cross-condition predictions of PAM50 subtypes of breast cancer by using a simulated dataset modeled after TCGA BRCA tumor samples with a cross-validation scheme, and datasets with known and unknown PAM50 classification. CL achieved prediction accuracy >73 %, highest among other methods we evaluated. We also applied the algorithm to a set of breast cancer tumors derived from Arabic population to assign a PAM50 classification to each tumor based on their gene expression profiles. A novel algorithm CrossLink for cross-condition prediction of cancer classes was proposed. In all test datasets, CL showed robust and consistent improvement in prediction performance over other state-of-the-art normalization and classification algorithms.

Molecular Classification and Correlates in Colorectal Cancer

OpenAIRE

Ogino, Shuji; Goel, Ajay

2008-01-01

Molecular classification of colorectal cancer is evolving. As our understanding of colorectal carcinogenesis improves, we are incorporating new knowledge into the classification system. In particular, global genomic status [microsatellite instability (MSI) status and chromosomal instability (CIN) status] and epigenomic status [CpG island methylator phenotype (CIMP) status] play a significant role in determining clinical, pathological and biological characteristics of colorectal cancer. In thi...

Lauren classification and individualized chemotherapy in gastric cancer

OpenAIRE

MA, JUNLI; SHEN, HONG; KAPESA, LINDA; ZENG, SHAN

2016-01-01

Gastric cancer is one of the most common malignancies worldwide. During the last 50 years, the histological classification of gastric carcinoma has been largely based on Lauren's criteria, in which gastric cancer is classified into two major histological subtypes, namely intestinal type and diffuse type adenocarcinoma. This classification was introduced in 1965, and remains currently widely accepted and employed, since it constitutes a simple and robust classification approach. The two histol...

Genetic Bee Colony (GBC) algorithm: A new gene selection method for microarray cancer classification.

Science.gov (United States)

Alshamlan, Hala M; Badr, Ghada H; Alohali, Yousef A

2015-06-01

Naturally inspired evolutionary algorithms prove effectiveness when used for solving feature selection and classification problems. Artificial Bee Colony (ABC) is a relatively new swarm intelligence method. In this paper, we propose a new hybrid gene selection method, namely Genetic Bee Colony (GBC) algorithm. The proposed algorithm combines the used of a Genetic Algorithm (GA) along with Artificial Bee Colony (ABC) algorithm. The goal is to integrate the advantages of both algorithms. The proposed algorithm is applied to a microarray gene expression profile in order to select the most predictive and informative genes for cancer classification. In order to test the accuracy performance of the proposed algorithm, extensive experiments were conducted. Three binary microarray datasets are use, which include: colon, leukemia, and lung. In addition, another three multi-class microarray datasets are used, which are: SRBCT, lymphoma, and leukemia. Results of the GBC algorithm are compared with our recently proposed technique: mRMR when combined with the Artificial Bee Colony algorithm (mRMR-ABC). We also compared the combination of mRMR with GA (mRMR-GA) and Particle Swarm Optimization (mRMR-PSO) algorithms. In addition, we compared the GBC algorithm with other related algorithms that have been recently published in the literature, using all benchmark datasets. The GBC algorithm shows superior performance as it achieved the highest classification accuracy along with the lowest average number of selected genes. This proves that the GBC algorithm is a promising approach for solving the gene selection problem in both binary and multi-class cancer classification. Copyright © 2015 Elsevier Ltd. All rights reserved.

A proposed radiological classification of childhood intra-thoracic tuberculosis

International Nuclear Information System (INIS)

Marais, Ben J.; Gie, Robert P.; Schaaf, H. Simon; Hesseling, Anneke C.; Donald, Peter R.; Beyers, Nulda; Starke, Jeff R.

2004-01-01

One of the obstacles in discussing childhood tuberculosis (TB) is the lack of standard descriptive terminology to classify the diverse spectrum of disease. Accurate disease classification is important, because the correct identification of the specific disease entity has definite prognostic significance. Accurate classification will also improve study outcome definitions and facilitate scientific communication. The aim of this paper is to provide practical guidelines for the accurate radiological classification of intra-thoracic TB in children less than 15 years of age. The proposed radiological classification is based on the underlying disease and the principles of pathological disease progression. The hope is that the proposed classification will clarify concepts and stimulate discussion that may lead to future consensus. (orig.)

Des Ogle's old stump

International Nuclear Information System (INIS)

Jones, M.; Sutton, D.; Wallace, R.

1998-01-01

On 17 October 1997 Sylvia Bryan of RD4 Kaitaia wrote to 'Dear Somebody-Everybody' at the Anthropology Department, University of Auckland, urging further examination of an adzed stump found by Des Ogle during planting out of the Te Aupouri forest. The authors have since sought out relevant information and present it here for the interests of our readers. (author). 7 refs., 1 fig

A stump-to-mill timber production cost-estimating program for cable logging eastern hardwoods

Science.gov (United States)

Chris B. LeDoux

1987-01-01

ECOST utilizes data from stand inventory, cruise data, and the logging plan for the tract in question. The program produces detailed stump-to-mill cost estimates for specific proposed timber sales. These estimates are then utilized, in combination with specific landowner objectives, to assess the economic feasibility of cable logging a given area. The program output is...

IDM-PhyChm-Ens: intelligent decision-making ensemble methodology for classification of human breast cancer using physicochemical properties of amino acids.

Science.gov (United States)

Ali, Safdar; Majid, Abdul; Khan, Asifullah

2014-04-01

Development of an accurate and reliable intelligent decision-making method for the construction of cancer diagnosis system is one of the fast growing research areas of health sciences. Such decision-making system can provide adequate information for cancer diagnosis and drug discovery. Descriptors derived from physicochemical properties of protein sequences are very useful for classifying cancerous proteins. Recently, several interesting research studies have been reported on breast cancer classification. To this end, we propose the exploitation of the physicochemical properties of amino acids in protein primary sequences such as hydrophobicity (Hd) and hydrophilicity (Hb) for breast cancer classification. Hd and Hb properties of amino acids, in recent literature, are reported to be quite effective in characterizing the constituent amino acids and are used to study protein foldings, interactions, structures, and sequence-order effects. Especially, using these physicochemical properties, we observed that proline, serine, tyrosine, cysteine, arginine, and asparagine amino acids offer high discrimination between cancerous and healthy proteins. In addition, unlike traditional ensemble classification approaches, the proposed 'IDM-PhyChm-Ens' method was developed by combining the decision spaces of a specific classifier trained on different feature spaces. The different feature spaces used were amino acid composition, split amino acid composition, and pseudo amino acid composition. Consequently, we have exploited different feature spaces using Hd and Hb properties of amino acids to develop an accurate method for classification of cancerous protein sequences. We developed ensemble classifiers using diverse learning algorithms such as random forest (RF), support vector machines (SVM), and K-nearest neighbor (KNN) trained on different feature spaces. We observed that ensemble-RF, in case of cancer classification, performed better than ensemble-SVM and ensemble-KNN. Our

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.

Treatment of Picea abies and Pinus sylvestris Stumps with Urea and Phlebiopsis gigantea for Control of Heterobasidion

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Kalle Kärhä

2018-03-01

Full Text Available Heterobasidion spp. root rot causes severe damage to forests throughout the northern temperate zone. In order to prevent Heterobasidion infection in summertime cuttings, stumps can be treated with urea or Phlebiopsis gigantea. In this study, the consumption of stump treatment materials and the quality of stump treatment work were investigated. A total of 46 harvesters were examined in May–November 2016 in Finland. The average stem size of softwood removal and softwood removal per hectare explained the consumption of stump treatment material. The quality of stump treatment work was good in the study. The best coverage was achieved with the stumps of 20–39 cm diameter at stump height (d0. It can be recommended that the harvester operator self-monitors and actively controls his/her treatment result in cutting work and sets the stump treatment equipment in a harvester if needed. The results also suggested that when cutting mostly small- and medium-diameter (d0 ≤ 39 cm conifers, the stump treatment guide bars with relatively few (<18 open holes are used, and at the harvesting sites of large-diameter trees, the guide bars with a relatively great (>27 number of open holes are applied.

The classification of osteonecrosis in patients with cancer: validation of a new radiological classification system

International Nuclear Information System (INIS)

Niinimäki, T.; Niinimäki, J.; Halonen, J.; Hänninen, P.; Harila-Saari, A.; Niinimäki, R.

2015-01-01

Aim: To validate a new, non-joint-specific radiological classification system that is suitable regardless of the site of the osteonecrosis (ON) in patients with cancer. Material and methods: Critical deficiencies in the existing ON classification systems were identified and a new, non-joint-specific radiological classification system was developed. Seventy-two magnetic resonance imaging (MRI) images of patients with cancer and ON lesions were graded, and the validation of the new system was performed by assessing inter- and intra-observer reliability. Results: Intra-observer reliability of ON grading was good or very good, with kappa values of 0.79–0.86. Interobserver agreement was lower but still good, with kappa values of 0.62–0.77. Ninety-eight percent of all intra- or interobserver differences were within one grade. Interobserver reliability of assessing the location of ON was very good, with kappa values of 0.93–0.98. Conclusion: All the available radiological ON classification systems are joint specific. This limitation has spurred the development of multiple systems, which has led to the insufficient use of classifications in ON studies among patients with cancer. The introduced radiological classification system overcomes the problem of joint-specificity, was found to be reliable, and can be used to classify all ON lesions regardless of the affected site. - Highlights: • Patients with cancer may have osteonecrosis lesions at multiple sites. • There is no non-joint-specific osteonecrosis classification available. • We introduced a new non-joint-specific osteonecrosis classification. • The validation was performed by assessing inter- and intra-observer reliability. • The classification was reliable and could be used regardless of the affected site.

Biofuels from stumps and small roundwood - Costs and CO{sub 2} benefits

Energy Technology Data Exchange (ETDEWEB)

Eriksson, Lisa Naeslund; Gustavsson, Leif [Ecotechnology, Department of Engineering, Physics and Mathematics, Mid Sweden University, SE-831 25 Oestersund (Sweden)

2008-10-15

In this study, we analysed and compared costs, primary energy use and CO{sub 2} benefits of recovering stumps and small roundwood from thinnings, together with logging residues. Small roundwood, chipped at a terminal or end-user, has a cost comparable to the chip system and a primary energy use comparable to the bundle system used for recovery of logging residues. The small roundwood system with roadside chipping is more expensive. As productivity in the cutting process improves, the small roundwood alternatives become more cost-effective. The stump system has costs in the same range as or lower than the chip and bundle systems. Forestry operations for stump and small roundwood recovery require considerable primary energy, but net recovery per hectare is much greater than for the chip and bundle systems, which means that more fossil fuel can be displaced per hectare of clearcut than with a chip or a bundle system. Stumps and small roundwood from thinnings can become as cost-effective as logging residues in the near future. Furthermore, when stumps and small roundwood from thinnings are also used to replace fossil fuels, the potential CO{sub 2} reduction will be about four times as great as when only logging residues are used with a traditional chip system. (author)

[New molecular classification of colorectal cancer, pancreatic cancer and stomach cancer: Towards "à la carte" treatment?].

Science.gov (United States)

Dreyer, Chantal; Afchain, Pauline; Trouilloud, Isabelle; André, Thierry

2016-01-01

This review reports 3 of recently published molecular classifications of the 3 main gastro-intestinal cancers: gastric, pancreatic and colorectal adenocarcinoma. In colorectal adenocarcinoma, 6 independent classifications were combined to finally hold 4 molecular sub-groups, Consensus Molecular Subtypes (CMS 1-4), linked to various clinical, molecular and survival data. CMS1 (14% MSI with immune activation); CMS2 (37%: canonical with epithelial differentiation and activation of the WNT/MYC pathway); CMS3 (13% metabolic with epithelial differentiation and RAS mutation); CMS4 (23%: mesenchymal with activation of TGFβ pathway and angiogenesis with stromal invasion). In gastric adenocarcinoma, 4 groups were established: subtype "EBV" (9%, high frequency of PIK3CA mutations, hypermetylation and amplification of JAK2, PD-L1 and PD-L2), subtype "MSI" (22%, high rate of mutation), subtype "genomically stable tumor" (20%, diffuse histology type and mutations of RAS and genes encoding integrins and adhesion proteins including CDH1) and subtype "tumors with chromosomal instability" (50%, intestinal type, aneuploidy and receptor tyrosine kinase amplification). In pancreatic adenocarcinomas, a classification in four sub-groups has been proposed, stable subtype (20%, aneuploidy), locally rearranged subtype (30%, focal event on one or two chromosoms), scattered subtype (36%,200 structural variation events, defects in DNA maintenance). Although currently away from the care of patients, these classifications open the way to "à la carte" treatment depending on molecular biology. Copyright © 2016 Société Française du Cancer. Published by Elsevier Masson SAS. All rights reserved.

Morphohistological features of pancreatic stump are the main determinant of pancreatic fistula after pancreatoduodenectomy.

Science.gov (United States)

Ridolfi, Cristina; Angiolini, Maria Rachele; Gavazzi, Francesca; Spaggiari, Paola; Tinti, Maria Carla; Uccelli, Fara; Madonini, Marco; Montorsi, Marco; Zerbi, Alessandro

2014-01-01

Pancreatic surgery is challenging and associated with high morbidity, mainly represented by postoperative pancreatic fistula (POPF) and its further consequences. Identification of risk factors for POPF is essential for proper postoperative management. Evaluation of the role of morphological and histological features of pancreatic stump, other than main pancreatic duct diameter and glandular texture, in POPF occurrence after pancreaticoduodenectomy. Between March 2011 and April 2013, we performed 145 consecutive pancreaticoduodenectomies. We intraoperatively recorded morphological features of pancreatic stump and collected data about postoperative morbidity. Our dedicated pathologist designed a score to quantify fibrosis and inflammation of pancreatic tissue. Overall morbidity was 59,3%. Mortality was 4,1%. POPF rate was 28,3%, while clinically significant POPF were 15,8%. Male sex (P = 0.009), BMI ≥ 25 (P = 0.002), prolonged surgery (P = 0.001), soft pancreatic texture (P < 0.001), small pancreatic duct (P < 0.001), pancreatic duct decentralization on stump anteroposterior axis, especially if close to the posterior margin (P = 0.031), large stump area (P = 0.001), and extended stump mobilization (P = 0.001) were related to higher POPF rate. Our fibrosis-and-inflammation score is strongly associated with POPF (P = 0.001). Pancreatic stump features evaluation, including histology, can help the surgeon in fitting postoperative management to patient individual risk after pancreaticoduodenectomy.

Crown-Stump Diameter Model for Parkia biglobosa Benth. Species in Makurdi, Benue State, Nigeria

Directory of Open Access Journals (Sweden)

O. Chukwu

2017-07-01

Full Text Available The crown of tree is the centre of physiological activity which gives an indication of the potential photosynthetic capacity on a tree. Though, its measurement remains a challenge in forest inventory task. The ability to predict crown diameter from stump diameter provides an effective technique of obtaining its estimate. This helps in detecting the excessive tree felling than actual requirements and wildlife suitability.The main objective of this study was to develop and test crown diameter prediction models for silvicultural management of naturally grown Parkia biglobosa within the University of Agriculture, Makurdi. Nine 100 m x 100 m temporary sample plots were established using simple random sampling method. Crown diameter and stump diameter were measured in all living P. biglobosa trees with stump diameter ≥10.0 cm. Least square method was used to convert the counted stumps into harvested crown dimension. Three linear and three non-linear models using stump diameter as the exploratory variable were developed and evaluated using the adjusted coefficient of determination (Adj.R2, standard error of estimate (SEE, prediction error sum of squares (PRESS and Akaike information criterion (AIC. The crown-stump diameter relationship was best described by the double logarithmic function with .The result showed that Crown diameter estimation was feasible even when the only information available is stump diameter.The resulting equation was tested for validation with independent data obtained from additional plots and was found to be desirable for estimating the crown diameter for Parkia biglobosa in Makurdi, Benue State, Nigeria.

Influence of nuclei segmentation on breast cancer malignancy classification

Science.gov (United States)

Jelen, Lukasz; Fevens, Thomas; Krzyzak, Adam

2009-02-01

Breast Cancer is one of the most deadly cancers affecting middle-aged women. Accurate diagnosis and prognosis are crucial to reduce the high death rate. Nowadays there are numerous diagnostic tools for breast cancer diagnosis. In this paper we discuss a role of nuclear segmentation from fine needle aspiration biopsy (FNA) slides and its influence on malignancy classification. Classification of malignancy plays a very important role during the diagnosis process of breast cancer. Out of all cancer diagnostic tools, FNA slides provide the most valuable information about the cancer malignancy grade which helps to choose an appropriate treatment. This process involves assessing numerous nuclear features and therefore precise segmentation of nuclei is very important. In this work we compare three powerful segmentation approaches and test their impact on the classification of breast cancer malignancy. The studied approaches involve level set segmentation, fuzzy c-means segmentation and textural segmentation based on co-occurrence matrix. Segmented nuclei were used to extract nuclear features for malignancy classification. For classification purposes four different classifiers were trained and tested with previously extracted features. The compared classifiers are Multilayer Perceptron (MLP), Self-Organizing Maps (SOM), Principal Component-based Neural Network (PCA) and Support Vector Machines (SVM). The presented results show that level set segmentation yields the best results over the three compared approaches and leads to a good feature extraction with a lowest average error rate of 6.51% over four different classifiers. The best performance was recorded for multilayer perceptron with an error rate of 3.07% using fuzzy c-means segmentation.

Percutaneous Management of Postoperative Duodenal Stump Leakage with Foley Catheter

International Nuclear Information System (INIS)

Oh, Jung Suk; Lee, Hae Giu; Chun, Ho Jong; Choi, Byung Gil; Lee, Sang Hoon; Hahn, Seong Tai; Ohm, Joon Young

2013-01-01

Purpose: This study was designed to evaluate retrospectively the safety and efficacy of the percutaneous management of duodenal stump leakage with a Foley catheter after subtotal gastrectomy. Methods: Ten consecutive patients (M:F = 9:1, median age: 64 years) were included in this retrospective study. The duodenal stump leakages were diagnosed in all the patients within a median of 10 days (range, 6–20). At first, the patients underwent percutaneous drainage on the day of or the day after confirmation of the presence of duodenal stump leakage, and then the Foley catheters were replaced at a median of 9 days (range, 6–38) after the percutaneous drainage. Results: Foley catheters were placed successfully in the duodenal lumen of all the patients under a fluoroscopic guide. No complication was observed during and after the procedures in all the patients. All of the patients started a regular diet 1 day after the Foley catheter placement. The patients were discharged at a median of 7 days (range, 5–14) after the Foley catheter placement. The catheters were removed in an outpatient clinic 10–58 days (median, 28) after the Foley catheter placement. Conclusions: Fluoroscopy-guided percutaneous Foley catheter placement may be a safe and effective treatment option for postoperative duodenal stump leakage and may allow for shorter hospital stays, earlier oral intake, and more effective control of leakage sites

Pulsed radiofrequency of brachial plexus under ultrasound guidance for refractory stump pain: a case report

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Zheng B

2017-11-01

Full Text Available Bixin Zheng, Li Song, Hui Liu Department of Pain Management, West China Hospital of Sichuan University, Chengdu, China Abstract: The post-amputation (pain syndrome, including stump pain, phantom limb sensation, and phantom limb pain is common but difficult to treat. Refractory stump pain in the syndrome is an extremely challenging and troublesome clinical condition. Patients respond poorly to drugs, nerve blocks, and other effective treatments like spinal cord stimulation and surgery. Pulsed radiofrequency (PRF technique has been shown to be effective in reducing neuropathic pain. This report describes a patient with persistent and refractory upper limb stump pain being successfully relieved with PRF of brachial plexus under ultrasound guidance after a 6-month follow-up period, suggesting that PRF may be considered as an alternative treatment for refractory stump-neuroma pain. Keywords: ultrasound guidance, pulsed radiofrequency, brachial plexus, refractory stump pain 

Morphohistological Features of Pancreatic Stump Are the Main Determinant of Pancreatic Fistula after Pancreatoduodenectomy

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Cristina Ridolfi

2014-01-01

Full Text Available Introduction. Pancreatic surgery is challenging and associated with high morbidity, mainly represented by postoperative pancreatic fistula (POPF and its further consequences. Identification of risk factors for POPF is essential for proper postoperative management. Aim of the Study. Evaluation of the role of morphological and histological features of pancreatic stump, other than main pancreatic duct diameter and glandular texture, in POPF occurrence after pancreaticoduodenectomy. Patients and Methods. Between March 2011 and April 2013, we performed 145 consecutive pancreaticoduodenectomies. We intraoperatively recorded morphological features of pancreatic stump and collected data about postoperative morbidity. Our dedicated pathologist designed a score to quantify fibrosis and inflammation of pancreatic tissue. Results. Overall morbidity was 59,3%. Mortality was 4,1%. POPF rate was 28,3%, while clinically significant POPF were 15,8%. Male sex (P=0.009, BMI≥25 (P=0.002, prolonged surgery (P=0.001, soft pancreatic texture (P<0.001, small pancreatic duct (P<0.001, pancreatic duct decentralization on stump anteroposterior axis, especially if close to the posterior margin (P=0.031, large stump area (P=0.001, and extended stump mobilization (P=0.001 were related to higher POPF rate. Our fibrosis-and-inflammation score is strongly associated with POPF (P=0.001. Discussion and Conclusions. Pancreatic stump features evaluation, including histology, can help the surgeon in fitting postoperative management to patient individual risk after pancreaticoduodenectomy.

Classification of parotidectomy: a proposed modification to the European Salivary Gland Society classification system.

Science.gov (United States)

Wong, Wai Keat; Shetty, Subhaschandra

2017-08-01

Parotidectomy remains the mainstay of treatment for both benign and malignant lesions of the parotid gland. There exists a wide range of possible surgical options in parotidectomy in terms of extent of parotid tissue removed. There is increasing need for uniformity of terminology resulting from growing interest in modifications of the conventional parotidectomy. It is, therefore, of paramount importance for a standardized classification system in describing extent of parotidectomy. Recently, the European Salivary Gland Society (ESGS) proposed a novel classification system for parotidectomy. The aim of this study is to evaluate this system. A classification system proposed by the ESGS was critically re-evaluated and modified to increase its accuracy and its acceptability. Modifications mainly focused on subdividing Levels I and II into IA, IB, IIA, and IIB. From June 2006 to June 2016, 126 patients underwent 130 parotidectomies at our hospital. The classification system was tested in that cohort of patient. While the ESGS classification system is comprehensive, it does not cover all possibilities. The addition of Sublevels IA, IB, IIA, and IIB may help to address some of the clinical situations seen and is clinically relevant. We aim to test the modified classification system for partial parotidectomy to address some of the challenges mentioned.

[Evaluation of new and emerging health technologies. Proposal for classification].

Science.gov (United States)

Prados-Torres, J D; Vidal-España, F; Barnestein-Fonseca, P; Gallo-García, C; Irastorza-Aldasoro, A; Leiva-Fernández, F

2011-01-01

Review and develop a proposal for the classification of health technologies (HT) evaluated by the Health Technology Assessment Agencies (HTAA). Peer review of AETS of the previous proposed classification of HT. Analysis of their input and suggestions for amendments. Construction of a new classification. Pilot study with physicians. Andalusian Public Health System. Spanish HTAA. Experts from HTAA. Tutors of family medicine residents. HT Update classification previously made by the research team. Peer review by Spanish HTAA. Qualitative and quantitative analysis of responses. Construction of a new and pilot study based on 12 evaluation reports of the HTAA. We obtained 11 thematic categories that are classified into 6 major head groups: 1, prevention technology; 2, diagnostic technology; 3, therapeutic technologies; 4, diagnostic and therapeutic technologies; 5, organizational technology, and 6, knowledge management and quality of care. In the pilot there was a good concordance in the classification of 8 of the 12 reports reviewed by physicians. Experts agree on 11 thematic categories of HT. A new classification of HT with double entry (Nature and purpose of HT) is proposed. APPLICABILITY: According to experts, the classification of the work of the HTAA may represent a useful tool to transfer and manage knowledge. Moreover, an adequate classification of the HTAA reports would help clinicians and other potential users to locate them and this can facilitate their dissemination. Copyright © 2010 SECA. Published by Elsevier Espana. All rights reserved.

Variation in Measurements of Transtibial Stump Model Volume A Comparison of Five Methods

NARCIS (Netherlands)

Bolt, A.; de Boer-Wilzing, V. G.; Geertzen, J. H. B.; Emmelot, C. H.; Baars, E. C. T.; Dijkstra, P. U.

Objective: To determine the right moment for fitting the first prosthesis, it is necessary to know when the volume of the stump has stabilized. The aim of this study is to analyze variation in measurements of transtibial stump model volumes using the water immersion method, the Design TT system, the

Transcutaneous electrical nerve stimulation (TENS) for phantom pain and stump pain following amputation in adults.

Science.gov (United States)

Johnson, Mark I; Mulvey, Matthew R; Bagnall, Anne-Marie

2015-08-18

This is the first update of a Cochrane review published in Issue 5, 2010 on transcutaneous electrical nerve stimulation (TENS) for phantom pain and stump pain following amputation in adults. Pain may present in a body part that has been amputated (phantom pain) or at the site of amputation (stump pain), or both. Phantom pain and stump pain are complex and multidimensional and the underlying pathophysiology remains unclear. The condition remains a severe burden for those who are affected by it. The mainstay treatments are predominately pharmacological, with increasing acknowledgement of the need for non-drug interventions. TENS has been recommended as a treatment option but there has been no systematic review of available evidence. Hence, the effectiveness of TENS for phantom pain and stump pain is currently unknown. To assess the analgesic effectiveness of TENS for the treatment of phantom pain and stump pain following amputation in adults. For the original version of the review we searched the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, EMBASE, PsycINFO, AMED, CINAHL, PEDRO and SPORTDiscus (February 2010). For this update, we searched the same databases for relevant randomised controlled trials (RCTs) from 2010 to 25 March 2015. We only included RCTs investigating the use of TENS for the management of phantom pain and stump pain following an amputation in adults. Two review authors independently assessed trial quality and extracted data. We planned that where available and appropriate, data from outcome measures were to be pooled and presented as an overall estimate of the effectiveness of TENS. In the original review there were no RCTs that examined the effectiveness of TENS for the treatment of phantom pain and stump pain in adults. For this update, we did not identify any additional RCTs for inclusion. There were no RCTs to judge the effectiveness of TENS for the management of phantom pain and stump pain. The published literature on TENS

A proposed data base system for detection, classification and ...

African Journals Online (AJOL)

A proposed data base system for detection, classification and location of fault on electricity company of Ghana electrical distribution system. Isaac Owusu-Nyarko, Mensah-Ananoo Eugine. Abstract. No Abstract. Keywords: database, classification of fault, power, distribution system, SCADA, ECG. Full Text: EMAIL FULL TEXT ...

Histological Changes in the Proximal and Distal Tendon Stumps Following Transection of Achilles Tendon in the Rabbits.

Science.gov (United States)

Al-Qattan, Mohammad M; Mawlana, Ola Helmi; Mohammed Ahmed, Raeesa Abdel-Twab; Hawary, Khalid

2016-05-01

To determine tendon stump changes following unrepaired Achilles tendon lacerations in an animal model. An experimental study. King Saud University, Riyadh, Saudi Arabia, from October 2013 to January 2014. Arabbit model was developed and studied tendon retraction and histological changes in the proximal and distal stumps following transection of the Achilles tendon. Over a period of 12 weeks, retraction of the distal tendon stump was minimal (2 - 3 mm). In contrast, retraction of the proximal tendon stump peaked to reach 6 mm at 4 weeks post-injury and plateaued to reach 7 - 8 mm at the 12-week interval. Following complete transection of the Achilles tendon, tendon retraction correlated with the density of myofibroblast expression within the tendon stump. Further research is needed to investigate the pathophysiology of these findings.

Appalachian hardwood stump sprouts are potential sawlog crop trees. Research note NE-299. [Oak, maple, linden, cherry trees

Energy Technology Data Exchange (ETDEWEB)

Lanson, N.I.

1976-01-01

Dbh and height of 8- and 12-year-old coppice shoots and the number of live shoots were recorded for 736 stumps at least 12 inches in diameter of Liriodendron tulipifera, Prunus serotina, Quercus rubra, Acer rubrum, and Tilia americana in north-central West Virgina. Of the 8-year-old shoots, T. americana had the greatest number of live stems/stump (16.8) and the greatest number of potential crop trees (dominant or co-dominant shoots attached to the stump not more than 6 inches above the ground), averaging 2.5 stems/stump. The average numbers of potential crop trees/stump were similar at 8 and 12 year. At 12 years, at least 88% of stumps of each species had at least one stem of groundline origin with no forks below 25 feet were 84% for L. tulipifera, 59% for Q rubra, 73% for A. rubrum, and 65% for P. Serotina.

Stabilization of the ulnar stump using modified Breen method after the Sauve-Kapandji procedure in rheumatoid wrist

International Nuclear Information System (INIS)

Tanino, Yoshihiko; Yabe, Yutaka; Yamauchi, Kenji; Ikegami, Hiroyasu; Ichikawa, Tooru

2006-01-01

We report on the utility of the modified Breen method in addition to the Sauve-Kapandji operation for the treatment of instability and pain in the proximal ulnar stump in rheumatoid arthrities (RA) wrist. We treated a total of 15 hands in 12 patients with disturbances due to instability and pain at the proximal ulnar stump. The average follow-up period was 47 months. We evaluated the range of motion, grip strength, radioulnar distance, and the radioulnar distance at the stump using CT during pronation, supination, and neutral positions of the forearm in 11 of the 15 operated hands. We observed that none of the patients showed any signs of pain at the proximal ulnar stump and no scallop sign was observed. In all the cases, the line connecting the center of the radial head to the proximal ulnar stump served as the axis of rotation for the forearm; this was confirmed by the CT images. We concluded that our operative method resulted in stabilization of the proximal ulnar stump and recovery of powerful grip without pain during forearm rotation. (author)

Proposed changes in the classification of carcinogenic chemicals in the work area.

Science.gov (United States)

Neumann, H G; Thielmann, H W; Filser, J G; Gelbke, H P; Greim, H; Kappus, H; Norpoth, K H; Reuter, U; Vamvakas, S; Wardenbach, P; Wichmann, H E

1997-12-01

Carcinogenic chemicals in the work area are currently classified into three categories in Section III of the German List of MAK and BAT Values. This classification is based on qualitative criteria and reflects essentially the weight of evidence available for judging the carcinogenic potential of the chemicals. It is proposed that these Categories--IIIA1, IIIA2, and IIIB--be retained as Categories 1, 2, and 3, to conform with EU regulations. On the basis of our advancing knowledge of reaction mechanisms and the potency of carcinogens, it is now proposed that these three categories be supplemented with two additional categories. The essential feature of substances classified in the new categories is that exposure to these chemicals does not convey a significant risk of cancer to man, provided that an appropriate exposure limit (MAK value) is observed. It is proposed that chemicals known to act typically by nongenotoxic mechanisms and for which information is available that allows evaluation of the effects of low-dose exposures be classified in Category 4. Genotoxic chemicals for which low carcinogenic potency can be expected on the basis of dose-response relationships and toxicokinetics and for which risk at low doses can be assessed will be classified in Category 5. The basis for a better differentiation of carcinogens is discussed, the new categories are defined, and possible criteria for classification are described. Examples for Category 4 (1,4-dioxane) and Category 5 (styrene) are presented. The proposed changes in classifying carcinogenic chemicals in the work area are presented for further discussion.

Magnetic resonance imaging texture analysis classification of primary breast cancer

International Nuclear Information System (INIS)

Waugh, S.A.; Lerski, R.A.; Purdie, C.A.; Jordan, L.B.; Vinnicombe, S.; Martin, P.; Thompson, A.M.

2016-01-01

Patient-tailored treatments for breast cancer are based on histological and immunohistochemical (IHC) subtypes. Magnetic Resonance Imaging (MRI) texture analysis (TA) may be useful in non-invasive lesion subtype classification. Women with newly diagnosed primary breast cancer underwent pre-treatment dynamic contrast-enhanced breast MRI. TA was performed using co-occurrence matrix (COM) features, by creating a model on retrospective training data, then prospectively applying to a test set. Analyses were blinded to breast pathology. Subtype classifications were performed using a cross-validated k-nearest-neighbour (k = 3) technique, with accuracy relative to pathology assessed and receiver operator curve (AUROC) calculated. Mann-Whitney U and Kruskal-Wallis tests were used to assess raw entropy feature values. Histological subtype classifications were similar across training (n = 148 cancers) and test sets (n = 73 lesions) using all COM features (training: 75 %, AUROC = 0.816; test: 72.5 %, AUROC = 0.823). Entropy features were significantly different between lobular and ductal cancers (p < 0.001; Mann-Whitney U). IHC classifications using COM features were also similar for training and test data (training: 57.2 %, AUROC = 0.754; test: 57.0 %, AUROC = 0.750). Hormone receptor positive and negative cancers demonstrated significantly different entropy features. Entropy features alone were unable to create a robust classification model. Textural differences on contrast-enhanced MR images may reflect underlying lesion subtypes, which merits testing against treatment response. (orig.)

Magnetic resonance imaging texture analysis classification of primary breast cancer

Energy Technology Data Exchange (ETDEWEB)

Waugh, S.A.; Lerski, R.A. [Ninewells Hospital and Medical School, Department of Medical Physics, Dundee (United Kingdom); Purdie, C.A.; Jordan, L.B. [Ninewells Hospital and Medical School, Department of Pathology, Dundee (United Kingdom); Vinnicombe, S. [University of Dundee, Division of Imaging and Technology, Ninewells Hospital and Medical School, Dundee (United Kingdom); Martin, P. [Ninewells Hospital and Medical School, Department of Clinical Radiology, Dundee (United Kingdom); Thompson, A.M. [University of Texas MD Anderson Cancer Center, Department of Surgical Oncology, Houston, TX (United States)

2016-02-15

Patient-tailored treatments for breast cancer are based on histological and immunohistochemical (IHC) subtypes. Magnetic Resonance Imaging (MRI) texture analysis (TA) may be useful in non-invasive lesion subtype classification. Women with newly diagnosed primary breast cancer underwent pre-treatment dynamic contrast-enhanced breast MRI. TA was performed using co-occurrence matrix (COM) features, by creating a model on retrospective training data, then prospectively applying to a test set. Analyses were blinded to breast pathology. Subtype classifications were performed using a cross-validated k-nearest-neighbour (k = 3) technique, with accuracy relative to pathology assessed and receiver operator curve (AUROC) calculated. Mann-Whitney U and Kruskal-Wallis tests were used to assess raw entropy feature values. Histological subtype classifications were similar across training (n = 148 cancers) and test sets (n = 73 lesions) using all COM features (training: 75 %, AUROC = 0.816; test: 72.5 %, AUROC = 0.823). Entropy features were significantly different between lobular and ductal cancers (p < 0.001; Mann-Whitney U). IHC classifications using COM features were also similar for training and test data (training: 57.2 %, AUROC = 0.754; test: 57.0 %, AUROC = 0.750). Hormone receptor positive and negative cancers demonstrated significantly different entropy features. Entropy features alone were unable to create a robust classification model. Textural differences on contrast-enhanced MR images may reflect underlying lesion subtypes, which merits testing against treatment response. (orig.)

Histological Changes in the Proximal and Distal Tendon Stumps Following Transection of Achilles Tendon in the Rabbits

International Nuclear Information System (INIS)

Al-Qattan, M. M.; Hawary, K.; Mawlana, O. H.; Ahmed, R. A. M.

2016-01-01

Objective: To determine tendon stump changes following unrepaired Achilles tendon lacerations in an animal model. Study Design: An experimental study. Place and Duration of Study: King Saud University, Riyadh, Saudi Arabia, from October 2013 to January 2014. Methodology: Arabbit model was developed and studied tendon retraction and histological changes in the proximal and distal stumps following transection of the Achilles tendon. Result: Over a period of 12 weeks, retraction of the distal tendon stump was minimal (2 - 3 mm). In contrast, retraction of the proximal tendon stump peaked to reach 6 mm at 4 weeks post-injury and plateaued to reach 7 - 8 mm at the 12-week interval. Conclusion: Following complete transection of the Achilles tendon, tendon retraction correlated with the density of myofibroblast expression within the tendon stump. Further research is needed to investigate the pathophysiology of these findings. (author)

Gastric cancer: epidemiology, prevention, classification, and treatment

Directory of Open Access Journals (Sweden)

Sitarz R

2018-02-01

Full Text Available Robert Sitarz,1–3 Małgorzata Skierucha,1,2 Jerzy Mielko,1 G Johan A Offerhaus,3 Ryszard Maciejewski,2 Wojciech P Polkowski1 1Department of Surgical Oncology, Medical University of Lublin, Lublin, Poland; 2Department of Human Anatomy, Medical University of Lublin, Lublin, Poland; 3Department of Pathology, University Medical Centre, Utrecht, The Netherlands Abstract: Gastric cancer is the second most common cause of cancer-related deaths in the world, the epidemiology of which has changed within last decades. A trend of steady decline in gastric cancer incidence rates is the effect of the increased standards of hygiene, conscious nutrition, and Helicobacter pylori eradication, which together constitute primary prevention. Avoidance of gastric cancer remains a priority. However, patients with higher risk should be screened for early detection and chemoprevention. Surgical resection enhanced by standardized lymphadenectomy remains the gold standard in gastric cancer therapy. This review briefly summarizes the most important aspects of gastric cancers, which include epidemiology, risk factors, classification, diagnosis, prevention, and treatment. The paper is mostly addressed to physicians who are interested in updating the state of art concerning gastric carcinoma from easily accessible and credible source. Keywords: gastric cancer, epidemiology, classification, risk factors, treatment

From Molecular Classification to Targeted Therapeutics: The Changing Face of Systemic Therapy in Metastatic Gastroesophageal Cancer

Directory of Open Access Journals (Sweden)

Adrian Murphy

2015-01-01

Full Text Available Histological classification of adenocarcinoma or squamous cell carcinoma for esophageal cancer or using the Lauren classification for intestinal and diffuse type gastric cancer has limited clinical utility in the management of advanced disease. Germline mutations in E-cadherin (CDH1 or mismatch repair genes (Lynch syndrome were identified many years ago but given their rarity, the identification of these molecular alterations does not substantially impact treatment in the advanced setting. Recent molecular profiling studies of upper GI tumors have added to our knowledge of the underlying biology but have not led to an alternative classification system which can guide clinician’s therapeutic decisions. Recently the Cancer Genome Atlas Research Network has proposed four subtypes of gastric cancer dividing tumors into those positive for Epstein-Barr virus, microsatellite unstable tumors, genomically stable tumors, and tumors with chromosomal instability. Unfortunately to date, many phase III clinical trials involving molecularly targeted agents have failed to meet their survival endpoints due to their use in unselected populations. Future clinical trials should utilize molecular profiling of individual tumors in order to determine the optimal use of targeted therapies in preselected patients.

Alternative Polyadenylation Patterns for Novel Gene Discovery and Classification in Cancer

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Oguzhan Begik

2017-07-01

Full Text Available Certain aspects of diagnosis, prognosis, and treatment of cancer patients are still important challenges to be addressed. Therefore, we propose a pipeline to uncover patterns of alternative polyadenylation (APA, a hidden complexity in cancer transcriptomes, to further accelerate efforts to discover novel cancer genes and pathways. Here, we analyzed expression data for 1045 cancer patients and found a significant shift in usage of poly(A signals in common tumor types (breast, colon, lung, prostate, gastric, and ovarian compared to normal tissues. Using machine-learning techniques, we further defined specific subsets of APA events to efficiently classify cancer types. Furthermore, APA patterns were associated with altered protein levels in patients, revealed by antibody-based profiling data, suggesting functional significance. Overall, our study offers a computational approach for use of APA in novel gene discovery and classification in common tumor types, with important implications in basic research, biomarker discovery, and precision medicine approaches.

Growth of teak regenerated by coppice and stump planting in Mae Moh Plantation, Lampang province, Thailand

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Anatta Auykim

2017-08-01

Full Text Available The current annual increment (CAIdbh and the mean annual increment (MAIdbh both for the diameter at breast height (1.3 m were investigated to compare the differences between coppice and stump-planted teak in Mae Moh Plantation. Forty-eight sample cores were collected from a 9 yr-old teak plantation using an increment borer; annual increments were analyzed using dendrochronological techniques. The results indicated that there was no significant (p > 0.05 difference in the average diameter at breast height (DBH between the coppice and stump-planted teak, whereas the total height of stump planting was significantly greater than that of coppice teak. The CAIdbh of coppice teak was in the range 0.316–2.371 cm and continuously decreased throughout the 9 yr period. The CAIdbh of stump planting was in the range 0.162–1.982 cm and continuously increased from the beginning of growth for 5 yr followed by a decline thereafter for 4 yr. The CAIdbh of coppice showed rapid growth in the years 1–4 and was greater than for the stump-planted teak even in years 5–8 after planting; however, the growth of the stump-planted teak in the ninth year was higher than for the coppice. The MAIdbh values of coppice and stump-planted teak were not significantly (p > 0.05 different. The results showed that CAIdbh at age 5 yr can be used as a silvicultural guide to increase the yield of teak coppice.

Systematic analysis of ocular trauma by a new proposed ocular trauma classification

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Bhartendu Shukla

2017-01-01

Full Text Available Purpose: The current classification of ocular trauma does not incorporate adnexal trauma, injuries that are attributable to a nonmechanical cause and destructive globe injuries. This study proposes a new classification system of ocular trauma which is broader-based to allow for the classification of a wider range of ocular injuries not covered by the current classification. Methods: A clinic-based cross-sectional study to validate the proposed classification. We analyzed 535 cases of ocular injury from January 1, 2012 to February 28, 2012 over a 4-year period in an eye hospital in central India using our proposed classification system and compared it with conventional classification. Results: The new classification system allowed for classification of all 535 cases of ocular injury. The conventional classification was only able to classify 364 of the 535 trauma cases. Injuries involving the adnexa, nonmechanical injuries and destructive globe injuries could not be classified by the conventional classification, thus missing about 33% of cases. Conclusions: Our classification system shows an improvement over existing ocular trauma classification as it allows for the classification of all type of ocular injuries and will allow for better and specific prognostication. This system has the potential to aid communication between physicians and result in better patient care. It can also provide a more authentic, wide spectrum of ocular injuries in correlation with etiology. By including adnexal injuries and nonmechanical injuries, we have been able to classify all 535 cases of trauma. Otherwise, about 30% of cases would have been excluded from the study.

Gene selection for cancer classification with the help of bees.

Science.gov (United States)

Moosa, Johra Muhammad; Shakur, Rameen; Kaykobad, Mohammad; Rahman, Mohammad Sohel

2016-08-10

Development of biologically relevant models from gene expression data notably, microarray data has become a topic of great interest in the field of bioinformatics and clinical genetics and oncology. Only a small number of gene expression data compared to the total number of genes explored possess a significant correlation with a certain phenotype. Gene selection enables researchers to obtain substantial insight into the genetic nature of the disease and the mechanisms responsible for it. Besides improvement of the performance of cancer classification, it can also cut down the time and cost of medical diagnoses. This study presents a modified Artificial Bee Colony Algorithm (ABC) to select minimum number of genes that are deemed to be significant for cancer along with improvement of predictive accuracy. The search equation of ABC is believed to be good at exploration but poor at exploitation. To overcome this limitation we have modified the ABC algorithm by incorporating the concept of pheromones which is one of the major components of Ant Colony Optimization (ACO) algorithm and a new operation in which successive bees communicate to share their findings. The proposed algorithm is evaluated using a suite of ten publicly available datasets after the parameters are tuned scientifically with one of the datasets. Obtained results are compared to other works that used the same datasets. The performance of the proposed method is proved to be superior. The method presented in this paper can provide subset of genes leading to more accurate classification results while the number of selected genes is smaller. Additionally, the proposed modified Artificial Bee Colony Algorithm could conceivably be applied to problems in other areas as well.

Prevalence of phantom limb pain, stump pain, and phantom limb sensation among the amputated cancer patients in India: A prospective, observational study

Directory of Open Access Journals (Sweden)

Arif Ahmed

2017-01-01

Full Text Available Introduction: The phantom limb pain (PLP and phantom limb sensation (PLS are very common among amputated cancer patients, and they lead to considerable morbidity. In spite of this, there is a lack of epidemiological data of this phenomenon among the Asian population. This study was done to provide the data from Indian population. Methods: The prevalence of PLP, stump pain (SP, and PLS was prospectively analyzed from the amputated cancer patients over a period of 2 years in Dr. B.R.A. Institute Rotary Cancer Hospital, All India Institute of Medical Sciences, New Delhi. The risk factors and the impact of phantom phenomenon on patients were also noted. Results: The prevalence of PLP was 41% at 3 and 12 months and 45.3% at 6 months, whereas that of SP and PLS was 14.4% and 71.2% at 3 months, 18.75% and 37.1% at 6 months, 15.8% and 32.4% at 12 months, respectively. There was higher prevalence of PLP and PLS among the patients with history of preamputation pain, smoking with proximal level of amputation, receiving general anesthesia, receiving intravenous (IV opioid postoperative analgesia, and developing neuroma or infection. Conclusion: The prevalence of PLP and PLS was higher among the cancer amputees as compared to SP, and a few risk factors responsible for their higher prevalence were found in our study. The PLP and PLS lead to considerable morbidity in terms of sleep disturbance and depression.

Proposed International League Against Epilepsy Classification 2010: new insights.

Science.gov (United States)

Udani, Vrajesh; Desai, Neelu

2014-09-01

The International League Against Epilepsy (ILAE) Classification of Seizures in 1981 and the Classification of the Epilepsies, in 1989 have been widely accepted the world over for the last 3 decades. Since then, there has been an explosive growth in imaging, genetics and other fields in the epilepsies which have changed many of our concepts. It was felt that a revision was in order and hence the ILAE commissioned a group of experts who submitted the initial draft of this revised classification in 2010. This review focuses on what are the strengths and weaknesses of this new proposed classification, especially in the context of a developing country.

Early detection of lung cancer from CT images: nodule segmentation and classification using deep learning

Science.gov (United States)

Sharma, Manu; Bhatt, Jignesh S.; Joshi, Manjunath V.

2018-04-01

Lung cancer is one of the most abundant causes of the cancerous deaths worldwide. It has low survival rate mainly due to the late diagnosis. With the hardware advancements in computed tomography (CT) technology, it is now possible to capture the high resolution images of lung region. However, it needs to be augmented by efficient algorithms to detect the lung cancer in the earlier stages using the acquired CT images. To this end, we propose a two-step algorithm for early detection of lung cancer. Given the CT image, we first extract the patch from the center location of the nodule and segment the lung nodule region. We propose to use Otsu method followed by morphological operations for the segmentation. This step enables accurate segmentation due to the use of data-driven threshold. Unlike other methods, we perform the segmentation without using the complete contour information of the nodule. In the second step, a deep convolutional neural network (CNN) is used for the better classification (malignant or benign) of the nodule present in the segmented patch. Accurate segmentation of even a tiny nodule followed by better classification using deep CNN enables the early detection of lung cancer. Experiments have been conducted using 6306 CT images of LIDC-IDRI database. We achieved the test accuracy of 84.13%, with the sensitivity and specificity of 91.69% and 73.16%, respectively, clearly outperforming the state-of-the-art algorithms.

Cancer classification using the Immunoscore: a worldwide task force.

Science.gov (United States)

Galon, Jérôme; Pagès, Franck; Marincola, Francesco M; Angell, Helen K; Thurin, Magdalena; Lugli, Alessandro; Zlobec, Inti; Berger, Anne; Bifulco, Carlo; Botti, Gerardo; Tatangelo, Fabiana; Britten, Cedrik M; Kreiter, Sebastian; Chouchane, Lotfi; Delrio, Paolo; Arndt, Hartmann; Asslaber, Martin; Maio, Michele; Masucci, Giuseppe V; Mihm, Martin; Vidal-Vanaclocha, Fernando; Allison, James P; Gnjatic, Sacha; Hakansson, Leif; Huber, Christoph; Singh-Jasuja, Harpreet; Ottensmeier, Christian; Zwierzina, Heinz; Laghi, Luigi; Grizzi, Fabio; Ohashi, Pamela S; Shaw, Patricia A; Clarke, Blaise A; Wouters, Bradly G; Kawakami, Yutaka; Hazama, Shoichi; Okuno, Kiyotaka; Wang, Ena; O'Donnell-Tormey, Jill; Lagorce, Christine; Pawelec, Graham; Nishimura, Michael I; Hawkins, Robert; Lapointe, Réjean; Lundqvist, Andreas; Khleif, Samir N; Ogino, Shuji; Gibbs, Peter; Waring, Paul; Sato, Noriyuki; Torigoe, Toshihiko; Itoh, Kyogo; Patel, Prabhu S; Shukla, Shilin N; Palmqvist, Richard; Nagtegaal, Iris D; Wang, Yili; D'Arrigo, Corrado; Kopetz, Scott; Sinicrope, Frank A; Trinchieri, Giorgio; Gajewski, Thomas F; Ascierto, Paolo A; Fox, Bernard A

2012-10-03

Prediction of clinical outcome in cancer is usually achieved by histopathological evaluation of tissue samples obtained during surgical resection of the primary tumor. Traditional tumor staging (AJCC/UICC-TNM classification) summarizes data on tumor burden (T), presence of cancer cells in draining and regional lymph nodes (N) and evidence for metastases (M). However, it is now recognized that clinical outcome can significantly vary among patients within the same stage. The current classification provides limited prognostic information, and does not predict response to therapy. Recent literature has alluded to the importance of the host immune system in controlling tumor progression. Thus, evidence supports the notion to include immunological biomarkers, implemented as a tool for the prediction of prognosis and response to therapy. Accumulating data, collected from large cohorts of human cancers, has demonstrated the impact of immune-classification, which has a prognostic value that may add to the significance of the AJCC/UICC TNM-classification. It is therefore imperative to begin to incorporate the 'Immunoscore' into traditional classification, thus providing an essential prognostic and potentially predictive tool. Introduction of this parameter as a biomarker to classify cancers, as part of routine diagnostic and prognostic assessment of tumors, will facilitate clinical decision-making including rational stratification of patient treatment. Equally, the inherent complexity of quantitative immunohistochemistry, in conjunction with protocol variation across laboratories, analysis of different immune cell types, inconsistent region selection criteria, and variable ways to quantify immune infiltration, all underline the urgent requirement to reach assay harmonization. In an effort to promote the Immunoscore in routine clinical settings, an international task force was initiated. This review represents a follow-up of the announcement of this initiative, and of the J

Cancer classification using the Immunoscore: a worldwide task force

Directory of Open Access Journals (Sweden)

Galon Jérôme

2012-10-01

Full Text Available Abstract Prediction of clinical outcome in cancer is usually achieved by histopathological evaluation of tissue samples obtained during surgical resection of the primary tumor. Traditional tumor staging (AJCC/UICC-TNM classification summarizes data on tumor burden (T, presence of cancer cells in draining and regional lymph nodes (N and evidence for metastases (M. However, it is now recognized that clinical outcome can significantly vary among patients within the same stage. The current classification provides limited prognostic information, and does not predict response to therapy. Recent literature has alluded to the importance of the host immune system in controlling tumor progression. Thus, evidence supports the notion to include immunological biomarkers, implemented as a tool for the prediction of prognosis and response to therapy. Accumulating data, collected from large cohorts of human cancers, has demonstrated the impact of immune-classification, which has a prognostic value that may add to the significance of the AJCC/UICC TNM-classification. It is therefore imperative to begin to incorporate the ‘Immunoscore’ into traditional classification, thus providing an essential prognostic and potentially predictive tool. Introduction of this parameter as a biomarker to classify cancers, as part of routine diagnostic and prognostic assessment of tumors, will facilitate clinical decision-making including rational stratification of patient treatment. Equally, the inherent complexity of quantitative immunohistochemistry, in conjunction with protocol variation across laboratories, analysis of different immune cell types, inconsistent region selection criteria, and variable ways to quantify immune infiltration, all underline the urgent requirement to reach assay harmonization. In an effort to promote the Immunoscore in routine clinical settings, an international task force was initiated. This review represents a follow-up of the announcement of

Involvement of Machine Learning for Breast Cancer Image Classification: A Survey.

Science.gov (United States)

Nahid, Abdullah-Al; Kong, Yinan

2017-01-01

Breast cancer is one of the largest causes of women's death in the world today. Advance engineering of natural image classification techniques and Artificial Intelligence methods has largely been used for the breast-image classification task. The involvement of digital image classification allows the doctor and the physicians a second opinion, and it saves the doctors' and physicians' time. Despite the various publications on breast image classification, very few review papers are available which provide a detailed description of breast cancer image classification techniques, feature extraction and selection procedures, classification measuring parameterizations, and image classification findings. We have put a special emphasis on the Convolutional Neural Network (CNN) method for breast image classification. Along with the CNN method we have also described the involvement of the conventional Neural Network (NN), Logic Based classifiers such as the Random Forest (RF) algorithm, Support Vector Machines (SVM), Bayesian methods, and a few of the semisupervised and unsupervised methods which have been used for breast image classification.

Involvement of Machine Learning for Breast Cancer Image Classification: A Survey

Directory of Open Access Journals (Sweden)

Abdullah-Al Nahid

2017-01-01

Full Text Available Breast cancer is one of the largest causes of women’s death in the world today. Advance engineering of natural image classification techniques and Artificial Intelligence methods has largely been used for the breast-image classification task. The involvement of digital image classification allows the doctor and the physicians a second opinion, and it saves the doctors’ and physicians’ time. Despite the various publications on breast image classification, very few review papers are available which provide a detailed description of breast cancer image classification techniques, feature extraction and selection procedures, classification measuring parameterizations, and image classification findings. We have put a special emphasis on the Convolutional Neural Network (CNN method for breast image classification. Along with the CNN method we have also described the involvement of the conventional Neural Network (NN, Logic Based classifiers such as the Random Forest (RF algorithm, Support Vector Machines (SVM, Bayesian methods, and a few of the semisupervised and unsupervised methods which have been used for breast image classification.

Influence of tree provenance on biogenic VOC emissions of Scots pine (Pinus sylvestris) stumps

Science.gov (United States)

Kivimäenpää, Minna; Magsarjav, Narantsetseg; Ghimire, Rajendra; Markkanen, Juha-Matti; Heijari, Juha; Vuorinen, Martti; Holopainen, Jarmo K.

2012-12-01

Resin-storing plant species such as conifer trees can release substantial amounts of volatile organic compounds (VOCs) into the atmosphere under stress circumstances that cause resin flow. Wounding can be induced by animals, pathogens, wind or direct mechanical damage e.g. during harvesting. In atmospheric modelling of biogenic VOCs, actively growing vegetation has been mostly considered as the source of emissions. Root systems and stumps of resin-storing conifer trees could constitute a significant store of resin after tree cutting. Therefore, we assessed the VOC emission rates from the cut surface of Scots pine stumps and estimated the average emission rates for an area with a density of 2000 stumps per ha. The experiment was conducted with trees of one Estonian and three Finnish Scots pine provenances covering a 1200 km gradient at a common garden established in central Finland in 1991. VOC emissions were dominated by monoterpenes and less than 0.1% of the total emission was sesquiterpenes. α-Pinene (7-92% of the total emissions) and 3-carene (0-76% of the total emissions) were the dominant monoterpenes. Proportions of α-pinene and camphene were significantly lower and proportions of 3-carene, sabinene, γ-terpinene and terpinolene higher in the southernmost Saaremaa provenance compared to the other provenances. Total terpene emission rates (standardised to +20 °C) from stumps varied from 27 to 1582 mg h-1 m-2 when measured within 2-3 h after tree cutting. Emission rates decreased rapidly to between 2 and 79 mg h-1 m-2 at 50 days after cutting. The estimated daily terpene emission rates on a hectare basis from freshly cut stumps at a cut tree density of 2000 per ha varied depending on provenance. Estimated emission ranges were 100-710 g ha-1 d-1 and 137-970 g ha-1 d-1 in 40 and in 60 year-old forest stands, respectively. Our result suggests that emission directly from stump surfaces could be a significant source of monoterpene emissions for a few weeks after

A New Direction of Cancer Classification: Positive Effect of Low-Ranking MicroRNAs.

Science.gov (United States)

Li, Feifei; Piao, Minghao; Piao, Yongjun; Li, Meijing; Ryu, Keun Ho

2014-10-01

Many studies based on microRNA (miRNA) expression profiles showed a new aspect of cancer classification. Because one characteristic of miRNA expression data is the high dimensionality, feature selection methods have been used to facilitate dimensionality reduction. The feature selection methods have one shortcoming thus far: they just consider the problem of where feature to class is 1:1 or n:1. However, because one miRNA may influence more than one type of cancer, human miRNA is considered to be ranked low in traditional feature selection methods and are removed most of the time. In view of the limitation of the miRNA number, low-ranking miRNAs are also important to cancer classification. We considered both high- and low-ranking features to cover all problems (1:1, n:1, 1:n, and m:n) in cancer classification. First, we used the correlation-based feature selection method to select the high-ranking miRNAs, and chose the support vector machine, Bayes network, decision tree, k-nearest-neighbor, and logistic classifier to construct cancer classification. Then, we chose Chi-square test, information gain, gain ratio, and Pearson's correlation feature selection methods to build the m:n feature subset, and used the selected miRNAs to determine cancer classification. The low-ranking miRNA expression profiles achieved higher classification accuracy compared with just using high-ranking miRNAs in traditional feature selection methods. Our results demonstrate that the m:n feature subset made a positive impression of low-ranking miRNAs in cancer classification.

The newly proposed clinical and post-neoadjuvant treatment staging classifications for gastric adenocarcinoma for the American Joint Committee on Cancer (AJCC) staging.

Science.gov (United States)

In, Haejin; Ravetch, Ethan; Langdon-Embry, Marisa; Palis, Bryan; Ajani, Jaffer A; Hofstetter, Wayne L; Kelsen, David P; Sano, Takeshi

2018-01-01

New stage grouping classifications for clinical (cStage) and post-neoadjuvant treatment (ypStage) stage for gastric adenocarcinoma have been proposed for the eighth edition of the AJCC manual. This article summarizes the analysis for these stages. Gastric adenocarcinoma patients diagnosed in 2004-2009 were identified from the National Cancer Database (NCDB). The cStage cohort included both surgical and nonsurgical cases, and the ypStage cohort included only patients who had chemotherapy or radiation therapy before surgery. Survival differences between the stage groups were determined by the log-rank test and prognostic accuracy was assessed by concordance index. Analysis was performed using SAS 9.4 (SAS, Cary, NC, USA). Five strata for cStage and four strata for ypStage were developed. The 5-year survival rates for cStages were 56.77%, 47.39%, 33.1%, 25.9%, and 5.0% for stages I, IIa, IIb, III, and IV, respectively, and the rates for ypStage were 74.2%, 46.3%, 19.2%, and 11.6% for stages I, II, III, and IV, respectively. The log-rank test showed that survival differences were well stratified and stage groupings were ordered and distinct (p < 0.0001). The proposed cStage and ypStage classification was sensitive and specific and had high prognostic accuracy (cStage: c index = 0.81, 95% CI, 0.79-0.83; ypStage: c index = 0.80, 95% CI, 0.73-0.87). The proposed eighth edition establishes two new staging schemata that provide essential prognostic data for patients before treatment and for patients who have undergone surgery following neoadjuvant therapy. These additions are a significant advance to the AJCC staging manual and will provide critical guidance to clinicians in making informed decisions throughout the treatment course.

Stump entrapment of the anterior cruciate ligament in late childhood and adolescence

Energy Technology Data Exchange (ETDEWEB)

Meyers, Arthur B.; Laor, Tal; Zbojniewicz, Andrew M. [Cincinnati Children' s Hospital Medical Center, Department of Radiology, Cincinnati, OH (United States)

2011-08-15

Displacement of a portion of the torn anterior cruciate ligament (ACL) into the intercondylar notch can cause a focal fibrotic reaction similar to that seen following ACL reconstruction. This displacement, which can result in locking or limitation of knee extension, is termed stump entrapment and is described in adult MR imaging literature. We present a pictorial essay of the etiology and appearance of stump entrapment on MR imaging of the knee in an older child and adolescents and review the significance of this finding. (orig.)

Glenohumeral interposition of rotator cuff stumps: a rare complication of traumatic rotator cuff tear

Directory of Open Access Journals (Sweden)

Paulo Moraes Agnollitto

2016-02-01

Full Text Available Abstract The present report describes a case where typical findings of traumatic glenohumeral interposition of rotator cuff stumps were surgically confirmed. This condition is a rare complication of shoulder trauma. Generally, it occurs in high-energy trauma, frequently in association with glenohumeral joint dislocation. Radiography demonstrated increased joint space, internal rotation of the humerus and coracoid process fracture. In addition to the mentioned findings, magnetic resonance imaging showed massive rotator cuff tear with interposition of the supraspinatus, infraspinatus and subscapularis stumps within the glenohumeral joint. Surgical treatment was performed confirming the injury and the rotator cuff stumps interposition. It is important that radiologists and orthopedic surgeons become familiar with this entity which, because of its rarity, might be neglected in cases of shoulder trauma.

Rooting stem cuttings of northern red oak (Quercus rubra L.) utilizing hedged stump sprouts formed on recently felled trees

Science.gov (United States)

Matthew H. Gocke; Daniel J. Robinson

2010-01-01

The ability to root stem cuttings collected from hedged stump sprouts formed on recently felled trees was evaluated for 26 codominant northern red oak (Quercus rubra L.) trees growing in Durham County, NC. Sprouting occurred, the same year as felling, on 23 of the 26 tree stumps and sprout number was significantly and positively correlated with stump diameter. The...

Profitability of Precommericially Thinning Oak Stump Sprouts

Science.gov (United States)

John P. Dwyer; Daniel C. Dey; William B. Kurtz

1993-01-01

Thinning oak stump sprouts to a single stem at an early age will increase diameter growth of the released stem. However, percommercial thinning represents a substantial investment which must be carried for many years before any returns are realized. We estimated the incremental gains in yield and the present net worth for five crop-tree release treatments of 5-yr-old...

Profitability of precommercially thinning oak stump sprouts

Science.gov (United States)

John P. Dwyer; Daniel C. Dey; William B. Kurtz

1993-01-01

Thinning oak stump sprouts to a single stem at an early age will increase diameter growth of the released stem. However, precommercial thinning represents a substantial investment which must be carried for many years before any returns are realized. We estimated the incremental gains in yield and the present net worth for five crop-tree release treatments of 5-year-old...

Examining applying high performance genetic data feature selection and classification algorithms for colon cancer diagnosis.

Science.gov (United States)

Al-Rajab, Murad; Lu, Joan; Xu, Qiang

2017-07-01

This paper examines the accuracy and efficiency (time complexity) of high performance genetic data feature selection and classification algorithms for colon cancer diagnosis. The need for this research derives from the urgent and increasing need for accurate and efficient algorithms. Colon cancer is a leading cause of death worldwide, hence it is vitally important for the cancer tissues to be expertly identified and classified in a rapid and timely manner, to assure both a fast detection of the disease and to expedite the drug discovery process. In this research, a three-phase approach was proposed and implemented: Phases One and Two examined the feature selection algorithms and classification algorithms employed separately, and Phase Three examined the performance of the combination of these. It was found from Phase One that the Particle Swarm Optimization (PSO) algorithm performed best with the colon dataset as a feature selection (29 genes selected) and from Phase Two that the Support Vector Machine (SVM) algorithm outperformed other classifications, with an accuracy of almost 86%. It was also found from Phase Three that the combined use of PSO and SVM surpassed other algorithms in accuracy and performance, and was faster in terms of time analysis (94%). It is concluded that applying feature selection algorithms prior to classification algorithms results in better accuracy than when the latter are applied alone. This conclusion is important and significant to industry and society. Copyright © 2017 Elsevier B.V. All rights reserved.

Classification of prostate cancer grade using temporal ultrasound: in vivo feasibility study

Science.gov (United States)

Ghavidel, Sahar; Imani, Farhad; Khallaghi, Siavash; Gibson, Eli; Khojaste, Amir; Gaed, Mena; Moussa, Madeleine; Gomez, Jose A.; Siemens, D. Robert; Leveridge, Michael; Chang, Silvia; Fenster, Aaron; Ward, Aaron D.; Abolmaesumi, Purang; Mousavi, Parvin

2016-03-01

Temporal ultrasound has been shown to have high classification accuracy in differentiating cancer from benign tissue. In this paper, we extend the temporal ultrasound method to classify lower grade Prostate Cancer (PCa) from all other grades. We use a group of nine patients with mostly lower grade PCa, where cancerous regions are also limited. A critical challenge is to train a classifier with limited aggressive cancerous tissue compared to low grade cancerous tissue. To resolve the problem of imbalanced data, we use Synthetic Minority Oversampling Technique (SMOTE) to generate synthetic samples for the minority class. We calculate spectral features of temporal ultrasound data and perform feature selection using Random Forests. In leave-one-patient-out cross-validation strategy, an area under receiver operating characteristic curve (AUC) of 0.74 is achieved with overall sensitivity and specificity of 70%. Using an unsupervised learning approach prior to proposed method improves sensitivity and AUC to 80% and 0.79. This work represents promising results to classify lower and higher grade PCa with limited cancerous training samples, using temporal ultrasound.

Relationship of stump diameter to d.b.h. for white pine in the northeast

Science.gov (United States)

Jesse D. Diller

1954-01-01

A need to estimate the volume cut from a timber tract when only the stumps are left is often felt by foresters, timber operators, and landowners. This need arises in areas where timber sales are based on stump diameters, in timber trespass cases, in check cruises on marked timber sales (to determine volume cut from unmarked trees), and as an aid in piecing together the...

Effects of season and urea treatment on infection of stumps of Picea abies by Heterobasidion annosum in stands on former arable land

Energy Technology Data Exchange (ETDEWEB)

Brandtberg, P.O. [Swedish Univ. of Agricultural Sciences, Uppsala (Sweden). Dept. of Ecology and Environmental Research; Johansson, Martin [Swedish Univ. of Agricultural Sciences, Uppsala (Sweden). Dept. of Forest Mycology and Pathology; Seeger, P. [Swedish Univ. of Agricultural Sciences, Uppsala (Sweden). Dept. of Statistics

1996-09-01

Between 1986 and 1990, a series of thinnings were made in previously unthinned first rotation stands on former arable land located in the southern half of Sweden. The aim was to evaluate the effects of season and urea treatment on the frequency of infection of stumps of Norway spruce (Picea abies (L.) Karst.) by the root-rot fungus Heterobasidion annosum (Fr.) Bref. Untreated stumps, resulting from 60 thinnings (22-100 stumps each, altogether ca 3000 stumps) made at different times of year, were investigated 3-24 months after cutting to determine whether they were infected with H. annosum. On average only 2% of the stumps from thinnings made in November-February were infected, whereas the incidence of infection among stumps thinned in June-July was 34%. Two methods of treating stumps with urea to prevent stump infection by H. annosum after thinning were evaluated in terms of effectiveness. The freshly cut stumps were treated with a 20% urea solution, transformed to a gel by adding 0.2% carboxymethyl cellulose, or with a 30% urea solution. On average, the reduction in infection rate obtained was 62% with the first method and 85% with the latter. In a separate study involving a concentration series of urea, there was a considerable drop in protection efficiency, from 89% to 58%, when the concentration was decreased from 30% to 15%. 38 refs, 3 figs, 1 tab

[Clinical Study of 2014 ISUP New Grade Group Classification for Prostate Cancer Patients Treated by Androgen Deprivation Therapy].

Science.gov (United States)

Uno, Masahiro; Kawase, Makoto; Kato, Daiki; Ishida, Takashi; Kato, Seiichi; Fujimoto, Yoshinori

2018-01-01

The 2014 International Society of Urological Pathology (ISUP) has proposed a new grade group (GG) classification for Gleason scores (GS). The usefulness of the new GG classification was investigated with 518 prostate cancer patients who underwent androgen deprivation therapy. According to the new GG classification, Stages B‒D and the new GG classification relapse-free rate for each stage were calculated using the Kaplan‒Meier method. The new GG classification revealed a significant difference for the relapse-free rate only between some groups. Analysis using the Cox proportional hazards model indicated that the risk of relapse was higher in GGs 4 and 5 than in GG 1. The usefulness about the relapse-free rate in androgen deprivation therapy of the 2014 ISUP new grade group classification a waits future examination.

A proposal of classification for acute toxicity; Una scala di tossicita`

Energy Technology Data Exchange (ETDEWEB)

Oddo, N. [Ecotox srl, Pregnana Milanese (Italy)

1998-05-01

A classification for acute toxicity is proposed, including the effects to low level exposures (Hormesis). The criteria, the measurement units and the correlations to chronic and to genotoxicity of the proposed classification are discussed. [Italiano] Viene proposta una scala per la tossicita` acuta, comprendendovi gli effetti deboli (Ormesi). Vengono discussi i criteri di formulazione della scala, le unita` di misura adottate, e le relazioni con la tossicita` cronica e con la genotossicita`.

Phonosurgery of the vocal folds : a classification proposal

NARCIS (Netherlands)

Remacle, M; Friedrich, G; Dikkers, FG; de Jong, F

The Phonosurgery Committee of the European Laryngological Society (ELS) has examined the definition and technical description of phonosurgical procedures. Based on this review, the committee has proposed a working classification. The current presentation is restricted to vocal fold surgery (VFS)

Proposed ICDRG Classification of the Clinical Presentation of Contact Allergy

DEFF Research Database (Denmark)

Pongpairoj, Korbkarn; Ale, Iris; Andersen, Klaus Ejner

2016-01-01

The International Contact Dermatitis Research Group proposes a classification for the clinical presentation of contact allergy. The classification is based primarily on the mode of clinical presentation. The categories are direct exposure/contact dermatitis, mimicking or exacerbation of preexisting....../mucosal symptoms, oral contact dermatitis, erythroderma/exfoliative dermatitis, minor forms of presentation, and extracutaneous manifestations....

Gastric cancer arising from the remnant stomach after distal gastrectomy: a review.

Science.gov (United States)

Takeno, Shinsuke; Hashimoto, Tatsuya; Maki, Kenji; Shibata, Ryosuke; Shiwaku, Hironari; Yamana, Ippei; Yamashita, Risako; Yamashita, Yuichi

2014-10-14

Gastric stump carcinoma was initially reported by Balfore in 1922, and many reports of this disease have since been published. We herein review previous reports of gastric stump carcinoma with respect to epidemiology, carcinogenesis, Helicobacter pylori (H. pylori) infection, Epstein-Barr virus infection, clinicopathologic characteristics and endoscopic treatment. In particular, it is noteworthy that no prognostic differences are observed between gastric stump carcinoma and primary upper third gastric cancer. In addition, endoscopic submucosal dissection has recently been used to treat gastric stump carcinoma in the early stage. In contrast, many issues concerning gastric stump carcinoma remain to be clarified, including molecular biological characteristics and the carcinogenesis of H. pylori infection. We herein review the previous pertinent literature and summarize the characteristics of gastric stump carcinoma reported to date.

A proposal of criteria for the classification of systemic sclerosis.

Science.gov (United States)

Nadashkevich, Oleg; Davis, Paul; Fritzler, Marvin J

2004-11-01

Sensitive and specific criteria for the classification of systemic sclerosis are required by clinicians and investigators to achieve higher quality clinical studies and approaches to therapy. A clinical study of systemic sclerosis patients in Europe and Canada led to a set of criteria that achieve high sensitivity and specificity. Both clinical and laboratory investigations of patients with systemic sclerosis, related conditions and diseases with clinical features that can be mistaken as part of the systemic sclerosis spectrum were undertaken. Laboratory investigations included the detection of autoantibodies to centromere proteins, Scl-70 (topoisomerase I), and fibrillarin (U3-RNP). Based on the investigation of 269 systemic sclerosis patients and 720 patients presenting with related and confounding conditions, the following set of criteria for the classification of systemic sclerosis was proposed: 1) autoantibodies to: centromere proteins, Scl-70 (topo I), fibrillarin; 2) bibasilar pulmonary fibrosis; 3) contractures of the digital joints or prayer sign; 4) dermal thickening proximal to the wrists; 5) calcinosis cutis; 6) Raynaud's phenomenon; 7) esophageal distal hypomotility or reflux-esophagitis; 8) sclerodactyly or non-pitting digital edema; 9) teleangiectasias. The classification of definite SSc requires at least three of the above criteria. Criteria for the classification of systemic sclerosis have been proposed. Preliminary testing has defined the sensitivity and specificity of these criteria as high as 99% and 100%, respectively. Testing and validation of the proposed criteria by other clinical centers is required.

Stump appendicitis 10 years after appendectomy, a rare, but serious complication of appendectomy, a case report.

Science.gov (United States)

Van Paesschen, Carl; Haenen, Filip; Bestman, Raymond; Van Cleemput, Marc

2017-02-01

We describe a case of stump appendicitis with the formation of abdominal abscesses in a 41-year-old patient 10 years prior appendectomy. The patient consulted with fever (38.1 °C) and abdominal pain, located at the right iliac fossa. Imaging studies showed signs of abscesses, located at the right iliac fossa, without clear origin of these abscesses. The abscesses were drained through diagnostic laparoscopy, no bowel perforation or clear origin of the abscedation was found during laparoscopy. During postoperative stay, the inflammatory parameters rose and the abscesses reoccurred. Re-laparoscopy was performed, the abscesses were drained and on careful inspection and adhesiolysis, a perforated stump appendicitis was revealed, covered underneath layers of fibrous tissue. Stump appendicitis is a rare complication seen after appendectomy and is generally not considered a possible etiology in patients presenting with fever and right iliac fossa abdominal pain with a history of appendectomy. This often delays the correct diagnosis and results in an associated increased incidence of complications. We describe a case of stump appendicitis occurring 10 years after initial appendectomy.

Evolving cancer classification in the era of personalized medicine: A primer for radiologists

Energy Technology Data Exchange (ETDEWEB)

O' Neill, Alibhe C.; Jagannathan, Jyothi P.; Ramaiya, Nikhil H. [Dept. of of Imaging, Dana Farber Cancer Institute, Boston (United States)

2017-01-15

Traditionally tumors were classified based on anatomic location but now specific genetic mutations in cancers are leading to treatment of tumors with molecular targeted therapies. This has led to a paradigm shift in the classification and treatment of cancer. Tumors treated with molecular targeted therapies often show morphological changes rather than change in size and are associated with class specific and drug specific toxicities, different from those encountered with conventional chemotherapeutic agents. It is important for the radiologists to be familiar with the new cancer classification and the various treatment strategies employed, in order to effectively communicate and participate in the multi-disciplinary care. In this paper we will focus on lung cancer as a prototype of the new molecular classification.

mRMR-ABC: A Hybrid Gene Selection Algorithm for Cancer Classification Using Microarray Gene Expression Profiling

Directory of Open Access Journals (Sweden)

Hala Alshamlan

2015-01-01

Full Text Available An artificial bee colony (ABC is a relatively recent swarm intelligence optimization approach. In this paper, we propose the first attempt at applying ABC algorithm in analyzing a microarray gene expression profile. In addition, we propose an innovative feature selection algorithm, minimum redundancy maximum relevance (mRMR, and combine it with an ABC algorithm, mRMR-ABC, to select informative genes from microarray profile. The new approach is based on a support vector machine (SVM algorithm to measure the classification accuracy for selected genes. We evaluate the performance of the proposed mRMR-ABC algorithm by conducting extensive experiments on six binary and multiclass gene expression microarray datasets. Furthermore, we compare our proposed mRMR-ABC algorithm with previously known techniques. We reimplemented two of these techniques for the sake of a fair comparison using the same parameters. These two techniques are mRMR when combined with a genetic algorithm (mRMR-GA and mRMR when combined with a particle swarm optimization algorithm (mRMR-PSO. The experimental results prove that the proposed mRMR-ABC algorithm achieves accurate classification performance using small number of predictive genes when tested using both datasets and compared to previously suggested methods. This shows that mRMR-ABC is a promising approach for solving gene selection and cancer classification problems.

mRMR-ABC: A Hybrid Gene Selection Algorithm for Cancer Classification Using Microarray Gene Expression Profiling.

Science.gov (United States)

Alshamlan, Hala; Badr, Ghada; Alohali, Yousef

2015-01-01

An artificial bee colony (ABC) is a relatively recent swarm intelligence optimization approach. In this paper, we propose the first attempt at applying ABC algorithm in analyzing a microarray gene expression profile. In addition, we propose an innovative feature selection algorithm, minimum redundancy maximum relevance (mRMR), and combine it with an ABC algorithm, mRMR-ABC, to select informative genes from microarray profile. The new approach is based on a support vector machine (SVM) algorithm to measure the classification accuracy for selected genes. We evaluate the performance of the proposed mRMR-ABC algorithm by conducting extensive experiments on six binary and multiclass gene expression microarray datasets. Furthermore, we compare our proposed mRMR-ABC algorithm with previously known techniques. We reimplemented two of these techniques for the sake of a fair comparison using the same parameters. These two techniques are mRMR when combined with a genetic algorithm (mRMR-GA) and mRMR when combined with a particle swarm optimization algorithm (mRMR-PSO). The experimental results prove that the proposed mRMR-ABC algorithm achieves accurate classification performance using small number of predictive genes when tested using both datasets and compared to previously suggested methods. This shows that mRMR-ABC is a promising approach for solving gene selection and cancer classification problems.

Improved prognostic classification of breast cancer defined by antagonistic activation patterns of immune response pathway modules

International Nuclear Information System (INIS)

Teschendorff, Andrew E; Gomez, Sergio; Arenas, Alex; El-Ashry, Dorraya; Schmidt, Marcus; Gehrmann, Mathias; Caldas, Carlos

2010-01-01

Elucidating the activation pattern of molecular pathways across a given tumour type is a key challenge necessary for understanding the heterogeneity in clinical response and for developing novel more effective therapies. Gene expression signatures of molecular pathway activation derived from perturbation experiments in model systems as well as structural models of molecular interactions ('model signatures') constitute an important resource for estimating corresponding activation levels in tumours. However, relatively few strategies for estimating pathway activity from such model signatures exist and only few studies have used activation patterns of pathways to refine molecular classifications of cancer. Here we propose a novel network-based method for estimating pathway activation in tumours from model signatures. We find that although the pathway networks inferred from cancer expression data are highly consistent with the prior information contained in the model signatures, that they also exhibit a highly modular structure and that estimation of pathway activity is dependent on this modular structure. We apply our methodology to a panel of 438 estrogen receptor negative (ER-) and 785 estrogen receptor positive (ER+) breast cancers to infer activation patterns of important cancer related molecular pathways. We show that in ER negative basal and HER2+ breast cancer, gene expression modules reflecting T-cell helper-1 (Th1) and T-cell helper-2 (Th2) mediated immune responses play antagonistic roles as major risk factors for distant metastasis. Using Boolean interaction Cox-regression models to identify non-linear pathway combinations associated with clinical outcome, we show that simultaneous high activation of Th1 and low activation of a TGF-beta pathway module defines a subtype of particularly good prognosis and that this classification provides a better prognostic model than those based on the individual pathways. In ER+ breast cancer, we find that

Classification of cancerous cells based on the one-class problem approach

Science.gov (United States)

Murshed, Nabeel A.; Bortolozzi, Flavio; Sabourin, Robert

1996-03-01

One of the most important factors in reducing the effect of cancerous diseases is the early diagnosis, which requires a good and a robust method. With the advancement of computer technologies and digital image processing, the development of a computer-based system has become feasible. In this paper, we introduce a new approach for the detection of cancerous cells. This approach is based on the one-class problem approach, through which the classification system need only be trained with patterns of cancerous cells. This reduces the burden of the training task by about 50%. Based on this approach, a computer-based classification system is developed, based on the Fuzzy ARTMAP neural networks. Experimental results were performed using a set of 542 patterns taken from a sample of breast cancer. Results of the experiment show 98% correct identification of cancerous cells and 95% correct identification of non-cancerous cells.

Prognostic classifications of lymph node involvement in lung cancer and current International Association for the Study of Lung Cancer descriptive classification in zones.

Science.gov (United States)

Riquet, Marc; Arame, Alex; Foucault, Christophe; Le Pimpec Barthes, Françoise

2010-09-01

The lymphatic drainage of solid organ tumors crosses through the lymph nodes (LNs) whose tumoral involvement may still be considered as local disease. Concerning lung cancer, LN involvement may be intrapulmonary (N1), and mediastinal and/or extra-thoracic. More than 30 years ago, mediastinal involved LNs were all considered as N2, and outside the scope of surgery. In 1978, Naruke presented an original article entitled 'Lymph node mapping and curability at various levels of metastasis in resected lung cancer', demonstrating that N2 was not a contraindication to surgery in all patients. The map permitted to localize the favorable N2 on the lung cancer ipsilateral side of the mediastinum. Several maps ensued aiming to discriminate between right and left involvement (1983), and to distinguish N2 (ipsilateral) and N3 (contralateral) mediastinal LN involvement (1983, 1986). The last map (1997 regional LN classification) was recently replaced by a descriptive classification in anatomical zones. This new LN map of the TNM classification for lung cancer is a step toward using anatomical view points which might be the best way to better understand lung cancer lymphatic spread. Nowadays, the LNs are easily identified by current radiological imaging, and their resectability may be anticipated. Each LN chain may be removed by en-bloc lymphadenectomy performed during radical lung resection, a safe procedure which seems to be more oncological based than sampling, and which avoids the source of discrepancies pointed out during the labeling of LN stations by surgeons.

Management of the difficult duodenal stump in penetrating duodenal ulcer disease: a comparative analysis of duodenojejunostomy with "classical" stump closure (Nissen-Bsteh).

Science.gov (United States)

Vashist, Yogesh K; Yekebas, Emre F; Gebauer, Florian; Tachezy, Michael; Bachmann, Kai; König, Alexandra; Kutup, Asad; Izbicki, Jakob R

2012-12-01

Duodenal stump insufficiency after surgery for penetrating gastroduodenal ulcer is associated with substantial mortality. "Classical" technique of closing a difficult duodenal stump (Nissen-Bsteh) has, up to now, not been compared with duodenojejunostomy (DJ) in larger patient sets. This also refers to the potential benefit of a gastric and biliary diversion under such conditions. The aim of the present study was to compare classical duodenal closure (CC) with DJ and to evaluate the impact of gastric and biliary diversion on postoperative outcome after surgery for penetrating, high-risk duodenal ulcer in a matched control study. Out of 321 patients, treated for penetrating duodenal ulcer disease, the perioperative outcome of 62 DJ patients was compared with 62 patients undergoing CC matched for age, gender, biliary diversion, and the operating surgeon collective. A total of 70 patients, equally distributed between DJ and CC subsets, received temporary biliary diversion. Overall perioperative mortality was 10.5%. However, DJ significantly reduced the mortality rate (4.8%) associated with penetrating duodenal ulcer compared to CC (16.1%, P management of penetrating duodenal ulcer.

Involvement of Machine Learning for Breast Cancer Image Classification: A Survey

OpenAIRE

Nahid, Abdullah-Al; Kong, Yinan

2017-01-01

Breast cancer is one of the largest causes of women’s death in the world today. Advance engineering of natural image classification techniques and Artificial Intelligence methods has largely been used for the breast-image classification task. The involvement of digital image classification allows the doctor and the physicians a second opinion, and it saves the doctors’ and physicians’ time. Despite the various publications on breast image classification, very few review papers are available w...

Laser Raman detection for oral cancer based on an adaptive Gaussian process classification method with posterior probabilities

International Nuclear Information System (INIS)

Du, Zhanwei; Yang, Yongjian; Bai, Yuan; Wang, Lijun; Su, Le; Chen, Yong; Li, Xianchang; Zhou, Xiaodong; Shen, Aiguo; Hu, Jiming; Jia, Jun

2013-01-01

The existing methods for early and differential diagnosis of oral cancer are limited due to the unapparent early symptoms and the imperfect imaging examination methods. In this paper, the classification models of oral adenocarcinoma, carcinoma tissues and a control group with just four features are established by utilizing the hybrid Gaussian process (HGP) classification algorithm, with the introduction of the mechanisms of noise reduction and posterior probability. HGP shows much better performance in the experimental results. During the experimental process, oral tissues were divided into three groups, adenocarcinoma (n = 87), carcinoma (n = 100) and the control group (n = 134). The spectral data for these groups were collected. The prospective application of the proposed HGP classification method improved the diagnostic sensitivity to 56.35% and the specificity to about 70.00%, and resulted in a Matthews correlation coefficient (MCC) of 0.36. It is proved that the utilization of HGP in LRS detection analysis for the diagnosis of oral cancer gives accurate results. The prospect of application is also satisfactory. (paper)

Laser Raman detection for oral cancer based on an adaptive Gaussian process classification method with posterior probabilities

Science.gov (United States)

Du, Zhanwei; Yang, Yongjian; Bai, Yuan; Wang, Lijun; Su, Le; Chen, Yong; Li, Xianchang; Zhou, Xiaodong; Jia, Jun; Shen, Aiguo; Hu, Jiming

2013-03-01

The existing methods for early and differential diagnosis of oral cancer are limited due to the unapparent early symptoms and the imperfect imaging examination methods. In this paper, the classification models of oral adenocarcinoma, carcinoma tissues and a control group with just four features are established by utilizing the hybrid Gaussian process (HGP) classification algorithm, with the introduction of the mechanisms of noise reduction and posterior probability. HGP shows much better performance in the experimental results. During the experimental process, oral tissues were divided into three groups, adenocarcinoma (n = 87), carcinoma (n = 100) and the control group (n = 134). The spectral data for these groups were collected. The prospective application of the proposed HGP classification method improved the diagnostic sensitivity to 56.35% and the specificity to about 70.00%, and resulted in a Matthews correlation coefficient (MCC) of 0.36. It is proved that the utilization of HGP in LRS detection analysis for the diagnosis of oral cancer gives accurate results. The prospect of application is also satisfactory.

Preliminary test of two stump surface protectants against Fomes annosus.

Science.gov (United States)

E.E. Nelson; C.Y. Li

1980-01-01

Two materials, monolaurin (at two concentrations) and an unidentified species of the genus Streptomyces, were tested along with borax for ability to protect freshly cut stump surfaces of western hemlock (Tsuga heterophylla (Raf.) Sarg.) from colonization by Fomes annosus. Protectants were significantly (P...

A Discrete Wavelet Based Feature Extraction and Hybrid Classification Technique for Microarray Data Analysis

Directory of Open Access Journals (Sweden)

Jaison Bennet

2014-01-01

Full Text Available Cancer classification by doctors and radiologists was based on morphological and clinical features and had limited diagnostic ability in olden days. The recent arrival of DNA microarray technology has led to the concurrent monitoring of thousands of gene expressions in a single chip which stimulates the progress in cancer classification. In this paper, we have proposed a hybrid approach for microarray data classification based on nearest neighbor (KNN, naive Bayes, and support vector machine (SVM. Feature selection prior to classification plays a vital role and a feature selection technique which combines discrete wavelet transform (DWT and moving window technique (MWT is used. The performance of the proposed method is compared with the conventional classifiers like support vector machine, nearest neighbor, and naive Bayes. Experiments have been conducted on both real and benchmark datasets and the results indicate that the ensemble approach produces higher classification accuracy than conventional classifiers. This paper serves as an automated system for the classification of cancer and can be applied by doctors in real cases which serve as a boon to the medical community. This work further reduces the misclassification of cancers which is highly not allowed in cancer detection.

Lung cancer gene expression database analysis incorporating prior knowledge with support vector machine-based classification method

Directory of Open Access Journals (Sweden)

Huang Desheng

2009-07-01

Full Text Available Abstract Background A reliable and precise classification is essential for successful diagnosis and treatment of cancer. Gene expression microarrays have provided the high-throughput platform to discover genomic biomarkers for cancer diagnosis and prognosis. Rational use of the available bioinformation can not only effectively remove or suppress noise in gene chips, but also avoid one-sided results of separate experiment. However, only some studies have been aware of the importance of prior information in cancer classification. Methods Together with the application of support vector machine as the discriminant approach, we proposed one modified method that incorporated prior knowledge into cancer classification based on gene expression data to improve accuracy. A public well-known dataset, Malignant pleural mesothelioma and lung adenocarcinoma gene expression database, was used in this study. Prior knowledge is viewed here as a means of directing the classifier using known lung adenocarcinoma related genes. The procedures were performed by software R 2.80. Results The modified method performed better after incorporating prior knowledge. Accuracy of the modified method improved from 98.86% to 100% in training set and from 98.51% to 99.06% in test set. The standard deviations of the modified method decreased from 0.26% to 0 in training set and from 3.04% to 2.10% in test set. Conclusion The method that incorporates prior knowledge into discriminant analysis could effectively improve the capacity and reduce the impact of noise. This idea may have good future not only in practice but also in methodology.

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.

Surface-based GPR underestimates below-stump root biomass

Science.gov (United States)

John R. Butnor; Lisa J. Samuelson; Thomas A. Stokes; Kurt H. Johnsen; Peter H. Anderson; Carlos A. Gonzalez-Benecke

2016-01-01

Aims While lateral root mass is readily detectable with ground penetrating radar (GPR), the roots beneath a tree (below-stump) and overlapping lateral roots near large trees are problematic for surface-based antennas operated in reflection mode. We sought to determine if tree size (DBH) effects GPR root detection proximal to longleaf pine (Pinus palustris Mill) and if...

Safety cost management in construction companies: A proposal classification.

Science.gov (United States)

López-Alonso, M; Ibarrondo-Dávila, M P; Rubio, M C

2016-06-16

Estimating health and safety costs in the construction industry presents various difficulties, including the complexity of cost allocation, the inadequacy of data available to managers and the absence of an accounting model designed specifically for safety cost management. Very often, the costs arising from accidents in the workplace are not fully identifiable due to the hidden costs involved. This paper reviews some studies of occupational health and safety cost management and proposes a means of classifying these costs. We conducted an empirical study in which the health and safety costs of 40 construction worksites are estimated. A new classification of the health and safety cost and its categories is proposed: Safety and non-safety costs. The costs of the company's health and safety policy should be included in the information provided by the accounting system, as a starting point for analysis and control. From this perspective, a classification of health and safety costs and its categories is put forward.

Efficacy of the Kyoto Classification of Gastritis in Identifying Patients at High Risk for Gastric Cancer.

Science.gov (United States)

Sugimoto, Mitsushige; Ban, Hiromitsu; Ichikawa, Hitomi; Sahara, Shu; Otsuka, Taketo; Inatomi, Osamu; Bamba, Shigeki; Furuta, Takahisa; Andoh, Akira

2017-01-01

Objective The Kyoto gastritis classification categorizes the endoscopic characteristics of Helicobacter pylori (H. pylori) infection-associated gastritis and identifies patterns associated with a high risk of gastric cancer. We investigated its efficacy, comparing scores in patients with H. pylori-associated gastritis and with gastric cancer. Methods A total of 1,200 patients with H. pylori-positive gastritis alone (n=932), early-stage H. pylori-positive gastric cancer (n=189), and successfully treated H. pylori-negative cancer (n=79) were endoscopically graded according to the Kyoto gastritis classification for atrophy, intestinal metaplasia, fold hypertrophy, nodularity, and diffuse redness. Results The prevalence of O-II/O-III-type atrophy according to the Kimura-Takemoto classification in early-stage H. pylori-positive gastric cancer and successfully treated H. pylori-negative cancer groups was 45.1%, which was significantly higher than in subjects with gastritis alone (12.7%, pgastritis scores of atrophy and intestinal metaplasia in the H. pylori-positive cancer group were significantly higher than in subjects with gastritis alone (all pgastritis classification may thus be useful for detecting these patients.

Evaluation of home care management of umbilical cord stumps by ...

African Journals Online (AJOL)

Background: Umbilical cord care is an integral part of neonatal care in all communities and cultures and appropriate cord care reduces the risk of infection in the newborn infant. Objective: The present study assessed the home care management of the umbilical stump by the mothers at Ilesa, Southwestern Nigeria. Subjects ...

Contributions for classification of platelet rich plasma - proposal of a new classification: MARSPILL.

Science.gov (United States)

Lana, Jose Fabio Santos Duarte; Purita, Joseph; Paulus, Christian; Huber, Stephany Cares; Rodrigues, Bruno Lima; Rodrigues, Ana Amélia; Santana, Maria Helena; Madureira, João Lopo; Malheiros Luzo, Ângela Cristina; Belangero, William Dias; Annichino-Bizzacchi, Joyce Maria

2017-07-01

Platelet-rich plasma (PRP) has emerged as a significant therapy used in medical conditions with heterogeneous results. There are some important classifications to try to standardize the PRP procedure. The aim of this report is to describe PRP contents studying celular and molecular components, and also propose a new classification for PRP. The main focus is on mononuclear cells, which comprise progenitor cells and monocytes. In addition, there are important variables related to PRP application incorporated in this study, which are the harvest method, activation, red blood cells, number of spins, image guidance, leukocytes number and light activation. The other focus is the discussion about progenitor cells presence on peripherial blood which are interesting due to neovasculogenesis and proliferation. The function of monocytes (in tissue-macrophages) are discussed here and also its plasticity, a potential property for regenerative medicine treatments.

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

Science.gov (United States)

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

2018-04-01

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

Zone-specific logistic regression models improve classification of prostate cancer on multi-parametric MRI

Energy Technology Data Exchange (ETDEWEB)

Dikaios, Nikolaos; Halligan, Steve; Taylor, Stuart; Atkinson, David; Punwani, Shonit [University College London, Centre for Medical Imaging, London (United Kingdom); University College London Hospital, Departments of Radiology, London (United Kingdom); Alkalbani, Jokha; Sidhu, Harbir Singh [University College London, Centre for Medical Imaging, London (United Kingdom); Abd-Alazeez, Mohamed; Ahmed, Hashim U.; Emberton, Mark [University College London, Research Department of Urology, Division of Surgery and Interventional Science, London (United Kingdom); Kirkham, Alex [University College London Hospital, Departments of Radiology, London (United Kingdom); Freeman, Alex [University College London Hospital, Department of Histopathology, London (United Kingdom)

2015-09-15

To assess the interchangeability of zone-specific (peripheral-zone (PZ) and transition-zone (TZ)) multiparametric-MRI (mp-MRI) logistic-regression (LR) models for classification of prostate cancer. Two hundred and thirty-one patients (70 TZ training-cohort; 76 PZ training-cohort; 85 TZ temporal validation-cohort) underwent mp-MRI and transperineal-template-prostate-mapping biopsy. PZ and TZ uni/multi-variate mp-MRI LR-models for classification of significant cancer (any cancer-core-length (CCL) with Gleason > 3 + 3 or any grade with CCL ≥ 4 mm) were derived from the respective cohorts and validated within the same zone by leave-one-out analysis. Inter-zonal performance was tested by applying TZ models to the PZ training-cohort and vice-versa. Classification performance of TZ models for TZ cancer was further assessed in the TZ validation-cohort. ROC area-under-curve (ROC-AUC) analysis was used to compare models. The univariate parameters with the best classification performance were the normalised T2 signal (T2nSI) within the TZ (ROC-AUC = 0.77) and normalized early contrast-enhanced T1 signal (DCE-nSI) within the PZ (ROC-AUC = 0.79). Performance was not significantly improved by bi-variate/tri-variate modelling. PZ models that contained DCE-nSI performed poorly in classification of TZ cancer. The TZ model based solely on maximum-enhancement poorly classified PZ cancer. LR-models dependent on DCE-MRI parameters alone are not interchangeable between prostatic zones; however, models based exclusively on T2 and/or ADC are more robust for inter-zonal application. (orig.)

Ductal carcinoma in situ: a proposal for a new classification

NARCIS (Netherlands)

Holland, R.; Peterse, J. L.; Millis, R. R.; Eusebi, V.; Faverly, D.; van de Vijver, M. J.; Zafrani, B.

1994-01-01

Details of a proposed new classification for ductal carcinoma in situ (DCIS) are presented. This is based, primarily, on cytonuclear differentiation and, secondarily, on architectural differentiation (cellular polarisation). Three categories are defined. First is poorly differentiated DCIS composed

Identifying colon cancer risk modules with better classification performance based on human signaling network.

Science.gov (United States)

Qu, Xiaoli; Xie, Ruiqiang; Chen, Lina; Feng, Chenchen; Zhou, Yanyan; Li, Wan; Huang, Hao; Jia, Xu; Lv, Junjie; He, Yuehan; Du, Youwen; Li, Weiguo; Shi, Yuchen; He, Weiming

2014-10-01

Identifying differences between normal and tumor samples from a modular perspective may help to improve our understanding of the mechanisms responsible for colon cancer. Many cancer studies have shown that signaling transduction and biological pathways are disturbed in disease states, and expression profiles can distinguish variations in diseases. In this study, we integrated a weighted human signaling network and gene expression profiles to select risk modules associated with tumor conditions. Risk modules as classification features by our method had a better classification performance than other methods, and one risk module for colon cancer had a good classification performance for distinguishing between normal/tumor samples and between tumor stages. All genes in the module were annotated to the biological process of positive regulation of cell proliferation, and were highly associated with colon cancer. These results suggested that these genes might be the potential risk genes for colon cancer. Copyright © 2013. Published by Elsevier Inc.

Push-back technique facilitates ultra-low anterior resection without nerve injury in total mesorectal excision for rectal cancer.

Science.gov (United States)

Inoue, Yasuhiro; Hiro, Junichiro; Toiyama, Yuji; Tanaka, Koji; Uchida, Keiichi; Miki, Chikao; Kusunoki, Masato

2011-01-01

To describe our push-back approach to ultra-low anterior resection using the concept of the mucosal stump. We mobilize the rectum using an abdominal approach, and perform mucosal cutting circumferentially at the dentate line. The mucosal stump is closed, and the internal sphincteric muscle resected partially or totally according to tumor location. Perianal dissection is performed along the medial plane of the external sphincteric muscles, and the hiatal ligament is dissected posteriorly. To resect the entire rectum, the closed rectal stump is pushed back to the abdominal cavity using composed gauze. This prevents injury to the autonomic nerve. We performed colonic J-pouch anal anastomosis using our mucosal stump approach in 58 patients with rectal cancer located push-back approach for internal sphincter resection produces satisfactory functional and oncological results in ultra-low anterior rectal cancer. Copyright © 2011 S. Karger AG, Basel.

ParSel: Parallel Selection of Micro-RNAs for Survival Classification in Cancers.

Science.gov (United States)

Sinha, Debajyoti; Sengupta, Debarka; Bandyopadhyay, Sanghamitra

2017-07-01

It is known that tumor micro-RNAs (miRNA) can define patient survival and treatment response. We present a framework to identify miRNAs which are predictive of cancer survival. The framework attempts to rank the miRNAs by exploring their collaborative role in gene regulation. Our approach tests a significantly large number of combinatorial cases leveraging parallel computation. We carefully avoided parametric assumptions involved in evaluations of miRNA expressions but used rigorous statistical computation to assign an importance score to a miRNA. Experimental results on three cancer types namely, KIRC, OV and GBM verify that the top ranked miRNAs obtained using the proposed framework produce better classification accuracy as compared to some best practice variable selection methods. Some of these top ranked miRNA are also known to be associated with related diseases. © 2017 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim.

Concentrations of base cations, phosphorous and nitrogen in tree stumps in Sweden, Finland and Denmark; Halter av baskatjoner, fosfor och kvaeve i stubbar i Sverige, Finland och Danmark

Energy Technology Data Exchange (ETDEWEB)

Hellsten, Sofie; Waengberg, Ingvar (The Swedish Environmental Research Institute Ltd., Stockholm (Sweden)); Helmisaari, Heljae-Sisko; Kaakinen, Seija; Kukkola, Mikko; Saarsalmi, Anna (Metla, Vantaa (Finland)); Melin, Ylva; Petersson, Hans (Swedish Univ. of Agriculture, Umeaa (Sweden)); Skovsgaard, Jens Peter (Forest and Landscape Denmark, Univ. of Copenhagen, Hoersholm (Denmark)); Akselsson, Cecilia (Lunds Univ., Lund (Sweden))

2009-05-15

Stump removal is becoming increasingly important in as demand for renewable energy is increasing. Nutrient concentrations in stumps are applied when evaluating the environmental effect of stump removal on acidification and nutrient balances in forest soil. The objectives of this study was to evaluate concentrations of nutrients in stumps in Sweden, Finland and Denmark, and to evaluate how nutrient concentrations vary with site characteristics, stand age and deposition level. Concentrations of N, P, Ca, K, Mg and Na in spruce, pine and birch stumps were assessed in eight sites across Scandinavia. The results of this study indicate that the concentration of nutrients are higher in birch stumps compared with spruce and pine. In Sweden and Finland, the nutrient concentrations were generally higher in the southern sites compared with northern sites in the country, except for P. Nutrient concentrations were significantly higher in the bark of the stump and the roots compared to the wood for all nutrients. Furthermore nutrients concentration increased significantly with decreasing root diameter. In Jaedraaas, Sweden, nutrient concentration of N, K, Mg and P in pine decreased with age of the stump harvested tree, for stumps < 65 years. This relation was not evident for other age spans or sites. Further studies are needed to provide a broader picture of how the nutrient concentrations vary with site characteristics, stand age and forestry management to get a better foundation when setting up recommendations for stump removal

Classification of mitocans, anti-cancer drugs acting on mitochondria

Czech Academy of Sciences Publication Activity Database

Neužil, Jiří; Dong, L. F.; Rohlena, Jakub; Truksa, Jaroslav; Ralph, S. J.

2013-01-01

Roč. 13, č. 3 (2013), s. 199-208 ISSN 1567-7249 Institutional research plan: CEZ:AV0Z50520701 Keywords : Mitocans * Anti-cancer therapeutics * Classification Subject RIV: EB - Genetics ; Molecular Biology Impact factor: 3.524, year: 2013

Ultrasonographic characteristics and BI-RADS-US classification of BRCA1 mutation-associated breast cancer in Guangxi, China.

Science.gov (United States)

Li, Cheng; Liu, Junjie; Wang, Sida; Chen, Yuanyuan; Yuan, Zhigang; Zeng, Jian; Li, Zhixian

2015-01-01

To retrospectively analyze and compare the ultrasonographic characteristics and BI-RADS-US classification between patients with BRCA1 mutation-associated breast cancer and those without BRCA1 gene mutation in Guangxi, China. The study was performed in 36 lesions from 34 BRCA1 mutation-associated breast cancer patients. A total of 422 lesions from 422 breast cancer patients without BRCA1 mutations served as control group. The comparison of the ultrasonographic features and BI-RADS-US classification between two the groups were reviewed. More complex inner echo was disclosed in BRCA1 mutation-associated breast cancer patients (x(2) = 4.741, P = 0.029). The BI-RADS classification of BRCA1 mutation-associated breast cancer was lower (U = 6094.0, P = 0.022). BRCA1 mutation-associated breast cancer frequently displays as microlobulated margin and complex echo. It also shows more benign characteristics in morphology, and the BI-RADS classification is prone to be underestimated.

A Quantum Hybrid PSO Combined with Fuzzy k-NN Approach to Feature Selection and Cell Classification in Cervical Cancer Detection

Directory of Open Access Journals (Sweden)

Abdullah M. Iliyasu

2017-12-01

Full Text Available A quantum hybrid (QH intelligent approach that blends the adaptive search capability of the quantum-behaved particle swarm optimisation (QPSO method with the intuitionistic rationality of traditional fuzzy k-nearest neighbours (Fuzzy k-NN algorithm (known simply as the Q-Fuzzy approach is proposed for efficient feature selection and classification of cells in cervical smeared (CS images. From an initial multitude of 17 features describing the geometry, colour, and texture of the CS images, the QPSO stage of our proposed technique is used to select the best subset features (i.e., global best particles that represent a pruned down collection of seven features. Using a dataset of almost 1000 images, performance evaluation of our proposed Q-Fuzzy approach assesses the impact of our feature selection on classification accuracy by way of three experimental scenarios that are compared alongside two other approaches: the All-features (i.e., classification without prior feature selection and another hybrid technique combining the standard PSO algorithm with the Fuzzy k-NN technique (P-Fuzzy approach. In the first and second scenarios, we further divided the assessment criteria in terms of classification accuracy based on the choice of best features and those in terms of the different categories of the cervical cells. In the third scenario, we introduced new QH hybrid techniques, i.e., QPSO combined with other supervised learning methods, and compared the classification accuracy alongside our proposed Q-Fuzzy approach. Furthermore, we employed statistical approaches to establish qualitative agreement with regards to the feature selection in the experimental scenarios 1 and 3. The synergy between the QPSO and Fuzzy k-NN in the proposed Q-Fuzzy approach improves classification accuracy as manifest in the reduction in number cell features, which is crucial for effective cervical cancer detection and diagnosis.

Classification of mitocans, anti-cancer drugs acting on mitochondria

Czech Academy of Sciences Publication Activity Database

Neužil, Jiří; Dong, L. F.; Rohlena, Jakub; Truksa, Jaroslav; Ralph, S. J.

2013-01-01

Roč. 13, č. 3 (2013), s. 199-208 ISSN 1567-7249 Institutional research plan: CEZ:AV0Z50520701 Keywords : Mitocans * Anti-cancer therapeutics * Classification Subject RIV: EB - Gene tics ; Molecular Biology Impact factor: 3.524, year: 2013

Histopathological Breast Cancer Image Classification by Deep Neural Network Techniques Guided by Local Clustering.

Science.gov (United States)

Nahid, Abdullah-Al; Mehrabi, Mohamad Ali; Kong, Yinan

2018-01-01

Breast Cancer is a serious threat and one of the largest causes of death of women throughout the world. The identification of cancer largely depends on digital biomedical photography analysis such as histopathological images by doctors and physicians. Analyzing histopathological images is a nontrivial task, and decisions from investigation of these kinds of images always require specialised knowledge. However, Computer Aided Diagnosis (CAD) techniques can help the doctor make more reliable decisions. The state-of-the-art Deep Neural Network (DNN) has been recently introduced for biomedical image analysis. Normally each image contains structural and statistical information. This paper classifies a set of biomedical breast cancer images (BreakHis dataset) using novel DNN techniques guided by structural and statistical information derived from the images. Specifically a Convolutional Neural Network (CNN), a Long-Short-Term-Memory (LSTM), and a combination of CNN and LSTM are proposed for breast cancer image classification. Softmax and Support Vector Machine (SVM) layers have been used for the decision-making stage after extracting features utilising the proposed novel DNN models. In this experiment the best Accuracy value of 91.00% is achieved on the 200x dataset, the best Precision value 96.00% is achieved on the 40x dataset, and the best F -Measure value is achieved on both the 40x and 100x datasets.

Prediction and error of baldcypress stem volume from stump diameter

Science.gov (United States)

Bernard R. Parresol

1998-01-01

The need to estimate the volume of removals occurs for many reasons, such as in trespass cases, severance tax reports, and post-harvest assessments. A logarithmic model is presented for prediction of baldcypress total stem cubic foot volume using stump diameter as the independent variable. Because the error of prediction is as important as the volume estimate, the...

Classification of human cancers based on DNA copy number amplification modeling

Directory of Open Access Journals (Sweden)

Knuutila Sakari

2008-05-01

Full Text Available Abstract Background DNA amplifications alter gene dosage in cancer genomes by multiplying the gene copy number. Amplifications are quintessential in a considerable number of advanced cancers of various anatomical locations. The aims of this study were to classify human cancers based on their amplification patterns, explore the biological and clinical fundamentals behind their amplification-pattern based classification, and understand the characteristics in human genomic architecture that associate with amplification mechanisms. Methods We applied a machine learning approach to model DNA copy number amplifications using a data set of binary amplification records at chromosome sub-band resolution from 4400 cases that represent 82 cancer types. Amplification data was fused with background data: clinical, histological and biological classifications, and cytogenetic annotations. Statistical hypothesis testing was used to mine associations between the data sets. Results Probabilistic clustering of each chromosome identified 111 amplification models and divided the cancer cases into clusters. The distribution of classification terms in the amplification-model based clustering of cancer cases revealed cancer classes that were associated with specific DNA copy number amplification models. Amplification patterns – finite or bounded descriptions of the ranges of the amplifications in the chromosome – were extracted from the clustered data and expressed according to the original cytogenetic nomenclature. This was achieved by maximal frequent itemset mining using the cluster-specific data sets. The boundaries of amplification patterns were shown to be enriched with fragile sites, telomeres, centromeres, and light chromosome bands. Conclusions Our results demonstrate that amplifications are non-random chromosomal changes and specifically selected in tumor tissue microenvironment. Furthermore, statistical evidence showed that specific chromosomal features

Feature Extraction and Classification on Esophageal X-Ray Images of Xinjiang Kazak Nationality

Directory of Open Access Journals (Sweden)

Fang Yang

2017-01-01

Full Text Available Esophageal cancer is one of the fastest rising types of cancers in China. The Kazak nationality is the highest-risk group in Xinjiang. In this work, an effective computer-aided diagnostic system is developed to assist physicians in interpreting digital X-ray image features and improving the quality of diagnosis. The modules of the proposed system include image preprocessing, feature extraction, feature selection, image classification, and performance evaluation. 300 original esophageal X-ray images were resized to a region of interest and then enhanced by the median filter and histogram equalization method. 37 features from textural, frequency, and complexity domains were extracted. Both sequential forward selection and principal component analysis methods were employed to select the discriminative features for classification. Then, support vector machine and K-nearest neighbors were applied to classify the esophageal cancer images with respect to their specific types. The classification performance was evaluated in terms of the area under the receiver operating characteristic curve, accuracy, precision, and recall, respectively. Experimental results show that the classification performance of the proposed system outperforms the conventional visual inspection approaches in terms of diagnostic quality and processing time. Therefore, the proposed computer-aided diagnostic system is promising for the diagnostics of esophageal cancer.

A Proposal for Cardiac Arrhythmia Classification using Complexity Measures

Directory of Open Access Journals (Sweden)

AROTARITEI, D.

2017-08-01

Full Text Available Cardiovascular diseases are one of the major problems of humanity and therefore one of their component, arrhythmia detection and classification drawn an increased attention worldwide. The presence of randomness in discrete time series, like those arising in electrophysiology, is firmly connected with computational complexity measure. This connection can be used, for instance, in the analysis of RR-intervals of electrocardiographic (ECG signal, coded as binary string, to detect and classify arrhythmia. Our approach uses three algorithms (Lempel-Ziv, Sample Entropy and T-Code to compute the information complexity applied and a classification tree to detect 13 types of arrhythmia with encouraging results. To overcome the computational effort required for complexity calculus, a cloud computing solution with executable code deployment is also proposed.

78 FR 39765 - Notice of Proposed Classification of Public Lands/Minerals for State Indemnity Selection, Colorado

Science.gov (United States)

2013-07-02

... Proposed Classification of Public Lands/Minerals for State Indemnity Selection, Colorado AGENCY: Bureau of Land Management, Interior. ACTION: Notice of Proposed Classification. SUMMARY: The Colorado State Board... public lands and mineral estate in lieu of lands to which the State was entitled but did not receive...

Automatic Classification of Normal and Cancer Lung CT Images Using Multiscale AM-FM Features

Directory of Open Access Journals (Sweden)

Eman Magdy

2015-01-01

Full Text Available Computer-aided diagnostic (CAD systems provide fast and reliable diagnosis for medical images. In this paper, CAD system is proposed to analyze and automatically segment the lungs and classify each lung into normal or cancer. Using 70 different patients’ lung CT dataset, Wiener filtering on the original CT images is applied firstly as a preprocessing step. Secondly, we combine histogram analysis with thresholding and morphological operations to segment the lung regions and extract each lung separately. Amplitude-Modulation Frequency-Modulation (AM-FM method thirdly, has been used to extract features for ROIs. Then, the significant AM-FM features have been selected using Partial Least Squares Regression (PLSR for classification step. Finally, K-nearest neighbour (KNN, support vector machine (SVM, naïve Bayes, and linear classifiers have been used with the selected AM-FM features. The performance of each classifier in terms of accuracy, sensitivity, and specificity is evaluated. The results indicate that our proposed CAD system succeeded to differentiate between normal and cancer lungs and achieved 95% accuracy in case of the linear classifier.

An iterated Laplacian based semi-supervised dimensionality reduction for classification of breast cancer on ultrasound images.

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Liu, Xiao; Shi, Jun; Zhou, Shichong; Lu, Minhua

2014-01-01

The dimensionality reduction is an important step in ultrasound image based computer-aided diagnosis (CAD) for breast cancer. A newly proposed l2,1 regularized correntropy algorithm for robust feature selection (CRFS) has achieved good performance for noise corrupted data. Therefore, it has the potential to reduce the dimensions of ultrasound image features. However, in clinical practice, the collection of labeled instances is usually expensive and time costing, while it is relatively easy to acquire the unlabeled or undetermined instances. Therefore, the semi-supervised learning is very suitable for clinical CAD. The iterated Laplacian regularization (Iter-LR) is a new regularization method, which has been proved to outperform the traditional graph Laplacian regularization in semi-supervised classification and ranking. In this study, to augment the classification accuracy of the breast ultrasound CAD based on texture feature, we propose an Iter-LR-based semi-supervised CRFS (Iter-LR-CRFS) algorithm, and then apply it to reduce the feature dimensions of ultrasound images for breast CAD. We compared the Iter-LR-CRFS with LR-CRFS, original supervised CRFS, and principal component analysis. The experimental results indicate that the proposed Iter-LR-CRFS significantly outperforms all other algorithms.

Significance and Application of Digital Breast Tomosynthesis for the BI-RADS Classification of Breast Cancer.

Science.gov (United States)

Cai, Si-Qing; Yan, Jian-Xiang; Chen, Qing-Shi; Huang, Mei-Ling; Cai, Dong-Lu

2015-01-01

Full-field digital mammography (FFDM) with dense breasts has a high rate of missed diagnosis, and digital breast tomosynthesis (DBT) could reduce organization overlapping and provide more reliable images for BI-RADS classification. This study aims to explore application of COMBO (FFDM+DBT) for effect and significance of BI-RADS classification of breast cancer. In this study, we selected 832 patients who had been treated from May 2013 to November 2013. Classify FFDM and COMBO examination according to BI-RADS separately and compare the differences for glands in the image of the same patient in judgment, mass characteristics display and indirect signs. Employ Paired Wilcoxon rank sum test was used in 79 breast cancer patients to find differences between two examine methods. The results indicated that COMBO pattern is able to observe more details in distribution of glands when estimating content. Paired Wilcoxon rank sum test showed that overall classification level of COMBO is higher significantly compared to FFDM to BI-RADS diagnosis and classification of breast (PBI-RADS classification in breast cancer in clinical.

Comparative Study of Classification Techniques on Breast Cancer FNA Biopsy Data

Directory of Open Access Journals (Sweden)

George Rumbe

2010-12-01

Full Text Available Accurate diagnostic detection of the cancerous cells in a patient is critical and may alter the subsequent treatment and increase the chances of survival rate. Machine learning techniques have been instrumental in disease detection and are currently being used in various classification problems due to their accurate prediction performance. Various techniques may provide different desired accuracies and it is therefore imperative to use the most suitable method which provides the best desired results. This research seeks to provide comparative analysis of Support Vector Machine, Bayesian classifier and other Artificial neural network classifiers (Backpropagation, linear programming, Learning vector quantization, and K nearest neighborhood on the Wisconsin breast cancer classification problem.

Digital artery perforator (DAP) flaps: modifications for fingertip and finger stump reconstruction.

Science.gov (United States)

Mitsunaga, Narushima; Mihara, Makoto; Koshima, Isao; Gonda, Koichi; Takuya, Iida; Kato, Harunosuke; Araki, Jun; Yamamoto, Yushuke; Yuhei, Otaki; Todokoro, Takeshi; Ishikawa, Shoichi; Eri, Uehara; Mundinger, Gerhard S

2010-08-01

Various fingertip reconstructions have been reported for situations where microsurgical finger replantation is impossible. One method is the digital artery perforator (DAP) flap. Herein we report 13 DAP flaps for fingertip and finger stump reconstruction following traumatic finger amputations, highlighting modifications to the originally described DAP flap. From October 1998 to December 2007, a total of 13 fingers (11 patients) underwent fingertip and finger stump reconstruction with modified DAP flaps following traumatic finger amputations. We performed six adipocutaneous flaps, three adipose-only flaps, two supercharged flaps and two extended flaps. Flap size ranged from 1.44 to 8 cm(2) (average 3.25 cm(2)). All flaps survived completely with the exception of partial skin necrosis in two cases. One of these cases required debridement and skin grafting. Our initial three cases used donor-site skin grafting. The donor site was closed primarily in the 10 subsequent cases. No patients showed postoperative hypersensitivity of repaired fingertips. Semmes-Weinstein (SW) test result for flaps including a digital nerve branch did not differ from those without (average 4.07 vs. 3.92). Modified DAP flaps allow for preservation of digital length, volume and finger function. They can be raised as adiposal-only flaps or extended flaps and supercharged through perforator-to-perforator anastomoses. The donor defect on the lateral pulp can be closed primarily or by skin grafting. For traumatic fingertip and finger stump reconstructions, DAP flaps deliver consistent aesthetic and functional results. Copyright 2009 British Association of Plastic, Reconstructive and Aesthetic Surgeons. Published by Elsevier Ltd. All rights reserved.

Application of machine learning on brain cancer multiclass classification

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Panca, V.; Rustam, Z.

2017-07-01

Classification of brain cancer is a problem of multiclass classification. One approach to solve this problem is by first transforming it into several binary problems. The microarray gene expression dataset has the two main characteristics of medical data: extremely many features (genes) and only a few number of samples. The application of machine learning on microarray gene expression dataset mainly consists of two steps: feature selection and classification. In this paper, the features are selected using a method based on support vector machine recursive feature elimination (SVM-RFE) principle which is improved to solve multiclass classification, called multiple multiclass SVM-RFE. Instead of using only the selected features on a single classifier, this method combines the result of multiple classifiers. The features are divided into subsets and SVM-RFE is used on each subset. Then, the selected features on each subset are put on separate classifiers. This method enhances the feature selection ability of each single SVM-RFE. Twin support vector machine (TWSVM) is used as the method of the classifier to reduce computational complexity. While ordinary SVM finds single optimum hyperplane, the main objective Twin SVM is to find two non-parallel optimum hyperplanes. The experiment on the brain cancer microarray gene expression dataset shows this method could classify 71,4% of the overall test data correctly, using 100 and 1000 genes selected from multiple multiclass SVM-RFE feature selection method. Furthermore, the per class results show that this method could classify data of normal and MD class with 100% accuracy.

Aesthetics-based classification of geological structures in outcrops for geotourism purposes: a tentative proposal

Science.gov (United States)

Mikhailenko, Anna V.; Nazarenko, Olesya V.; Ruban, Dmitry A.; Zayats, Pavel P.

2017-03-01

The current growth in geotourism requires an urgent development of classifications of geological features on the basis of criteria that are relevant to tourist perceptions. It appears that structure-related patterns are especially attractive for geotourists. Consideration of the main criteria by which tourists judge beauty and observations made in the geodiversity hotspot of the Western Caucasus allow us to propose a tentative aesthetics-based classification of geological structures in outcrops, with two classes and four subclasses. It is possible to distinguish between regular and quasi-regular patterns (i.e., striped and lined and contorted patterns) and irregular and complex patterns (paysage and sculptured patterns). Typical examples of each case are found both in the study area and on a global scale. The application of the proposed classification permits to emphasise features of interest to a broad range of tourists. Aesthetics-based (i.e., non-geological) classifications are necessary to take into account visions and attitudes of visitors.

Bladder cancer: Analysis of the 2004 WHO classification in ...

African Journals Online (AJOL)

Objectives: Bladder cancer (BCA) is aworldwide disease and shows a wide range of geographical variation. The aim of this study is to analyze the prevalence of schistosomal and non-schistosomal associated BCA as well as compare our findings with the 2004 WHO consensus classification of urothelial neoplasms and ...

Can-CSC-GBE: Developing Cost-sensitive Classifier with Gentleboost Ensemble for breast cancer classification using protein amino acids and imbalanced data.

Science.gov (United States)

Ali, Safdar; Majid, Abdul; Javed, Syed Gibran; Sattar, Mohsin

2016-06-01

Early prediction of breast cancer is important for effective treatment and survival. We developed an effective Cost-Sensitive Classifier with GentleBoost Ensemble (Can-CSC-GBE) for the classification of breast cancer using protein amino acid features. In this work, first, discriminant information of the protein sequences related to breast tissue is extracted. Then, the physicochemical properties hydrophobicity and hydrophilicity of amino acids are employed to generate molecule descriptors in different feature spaces. For comparison, we obtained results by combining Cost-Sensitive learning with conventional ensemble of AdaBoostM1 and Bagging. The proposed Can-CSC-GBE system has effectively reduced the misclassification costs and thereby improved the overall classification performance. Our novel approach has highlighted promising results as compared to the state-of-the-art ensemble approaches. Copyright © 2016 Elsevier Ltd. All rights reserved.

Classification of samples into two or more ordered populations with application to a cancer trial.

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Conde, D; Fernández, M A; Rueda, C; Salvador, B

2012-12-10

In many applications, especially in cancer treatment and diagnosis, investigators are interested in classifying patients into various diagnosis groups on the basis of molecular data such as gene expression or proteomic data. Often, some of the diagnosis groups are known to be related to higher or lower values of some of the predictors. The standard methods of classifying patients into various groups do not take into account the underlying order. This could potentially result in high misclassification rates, especially when the number of groups is larger than two. In this article, we develop classification procedures that exploit the underlying order among the mean values of the predictor variables and the diagnostic groups by using ideas from order-restricted inference. We generalize the existing methodology on discrimination under restrictions and provide empirical evidence to demonstrate that the proposed methodology improves over the existing unrestricted methodology. The proposed methodology is applied to a bladder cancer data set where the researchers are interested in classifying patients into various groups. Copyright © 2012 John Wiley & Sons, Ltd.

SOUND VELOCITY and Other Data from USS STUMP DD-978) (NCEI Accession 9400069)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The sound velocity data in this accession were collected from USS STUMP DD-978 by US Navy. The sound velocity in water is analog profiles data that was recorded in...

New Models for Predicting Diameter at Breast Height from Stump Dimensions

Science.gov (United States)

James A. Westfall

2010-01-01

Models to predict dbh from stump dimensions are presented for 18 species groups. Data used to fit the models were collected across thirteen states in the northeastern United States. Primarily because of the presence of multiple measurements from each tree, a mixed-effects modeling approach was used to account for the lack of independence among observations. The...

Novelty detection for breast cancer image classification

Science.gov (United States)

Cichosz, Pawel; Jagodziński, Dariusz; Matysiewicz, Mateusz; Neumann, Łukasz; Nowak, Robert M.; Okuniewski, Rafał; Oleszkiewicz, Witold

2016-09-01

Using classification learning algorithms for medical applications may require not only refined model creation techniques and careful unbiased model evaluation, but also detecting the risk of misclassification at the time of model application. This is addressed by novelty detection, which identifies instances for which the training set is not sufficiently representative and for which it may be safer to restrain from classification and request a human expert diagnosis. The paper investigates two techniques for isolated instance identification, based on clustering and one-class support vector machines, which represent two different approaches to multidimensional outlier detection. The prediction quality for isolated instances in breast cancer image data is evaluated using the random forest algorithm and found to be substantially inferior to the prediction quality for non-isolated instances. Each of the two techniques is then used to create a novelty detection model which can be combined with a classification model and used at the time of prediction to detect instances for which the latter cannot be reliably applied. Novelty detection is demonstrated to improve random forest prediction quality and argued to deserve further investigation in medical applications.

Accessory cardiac bronchus: Proposed imaging classification on multidetector CT

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Kim, Kang Min; Kim, Young Tong; Han, Jong Kyu; Jou, Sung Shick [Dept. of Radiology, Soonchunhyang University College of Medicine, Cheonan Hospital, Cheonan (Korea, Republic of)

2016-02-15

To propose the classification of accessory cardiac bronchus (ACB) based on imaging using multidetector computed tomography (MDCT), and evaluate follow-up changes of ACB. This study included 58 patients diagnosed as ACB since 9 years, using MDCT. We analyzed the types, division locations and division directions of ACB, and also evaluated changes on follow-up. We identified two main types of ACB: blind-end (51.7%) and lobule (48.3%). The blind-end ACB was further classified into three subtypes: blunt (70%), pointy (23.3%) and saccular (6.7%). The lobule ACB was also further classified into three subtypes: complete (46.4%), incomplete (28.6%) and rudimentary (25%). Division location to the upper half bronchus intermedius (79.3%) and medial direction (60.3%) were the most common in all patients. The difference in division direction was statistically significant between the blind-end and lobule types (p = 0.019). Peribronchial soft tissue was found in five cases. One calcification case was identified in the lobule type. During follow-up, ACB had disappeared in two cases of the blind-end type and in one case of the rudimentary subtype. The proposed classification of ACB based on imaging, and the follow-up CT, helped us to understand the various imaging features of ACB.

Support vector machine and principal component analysis for microarray data classification

Science.gov (United States)

Astuti, Widi; Adiwijaya

2018-03-01

Cancer is a leading cause of death worldwide although a significant proportion of it can be cured if it is detected early. In recent decades, technology called microarray takes an important role in the diagnosis of cancer. By using data mining technique, microarray data classification can be performed to improve the accuracy of cancer diagnosis compared to traditional techniques. The characteristic of microarray data is small sample but it has huge dimension. Since that, there is a challenge for researcher to provide solutions for microarray data classification with high performance in both accuracy and running time. This research proposed the usage of Principal Component Analysis (PCA) as a dimension reduction method along with Support Vector Method (SVM) optimized by kernel functions as a classifier for microarray data classification. The proposed scheme was applied on seven data sets using 5-fold cross validation and then evaluation and analysis conducted on term of both accuracy and running time. The result showed that the scheme can obtained 100% accuracy for Ovarian and Lung Cancer data when Linear and Cubic kernel functions are used. In term of running time, PCA greatly reduced the running time for every data sets.

Classification of premalignant pancreatic cancer mass-spectrometry data using decision tree ensembles

Directory of Open Access Journals (Sweden)

Wong G William

2008-06-01

Full Text Available Abstract Background Pancreatic cancer is the fourth leading cause of cancer death in the United States. Consequently, identification of clinically relevant biomarkers for the early detection of this cancer type is urgently needed. In recent years, proteomics profiling techniques combined with various data analysis methods have been successfully used to gain critical insights into processes and mechanisms underlying pathologic conditions, particularly as they relate to cancer. However, the high dimensionality of proteomics data combined with their relatively small sample sizes poses a significant challenge to current data mining methodology where many of the standard methods cannot be applied directly. Here, we propose a novel methodological framework using machine learning method, in which decision tree based classifier ensembles coupled with feature selection methods, is applied to proteomics data generated from premalignant pancreatic cancer. Results This study explores the utility of three different feature selection schemas (Student t test, Wilcoxon rank sum test and genetic algorithm to reduce the high dimensionality of a pancreatic cancer proteomic dataset. Using the top features selected from each method, we compared the prediction performances of a single decision tree algorithm C4.5 with six different decision-tree based classifier ensembles (Random forest, Stacked generalization, Bagging, Adaboost, Logitboost and Multiboost. We show that ensemble classifiers always outperform single decision tree classifier in having greater accuracies and smaller prediction errors when applied to a pancreatic cancer proteomics dataset. Conclusion In our cross validation framework, classifier ensembles generally have better classification accuracies compared to that of a single decision tree when applied to a pancreatic cancer proteomic dataset, thus suggesting its utility in future proteomics data analysis. Additionally, the use of feature selection

The 2015 World Health Organization Classification of Lung Tumors: Impact of Genetic, Clinical and Radiologic Advances Since the 2004 Classification.

Science.gov (United States)

Travis, William D; Brambilla, Elisabeth; Nicholson, Andrew G; Yatabe, Yasushi; Austin, John H M; Beasley, Mary Beth; Chirieac, Lucian R; Dacic, Sanja; Duhig, Edwina; Flieder, Douglas B; Geisinger, Kim; Hirsch, Fred R; Ishikawa, Yuichi; Kerr, Keith M; Noguchi, Masayuki; Pelosi, Giuseppe; Powell, Charles A; Tsao, Ming Sound; Wistuba, Ignacio

2015-09-01

The 2015 World Health Organization (WHO) Classification of Tumors of the Lung, Pleura, Thymus and Heart has just been published with numerous important changes from the 2004 WHO classification. The most significant changes in this edition involve (1) use of immunohistochemistry throughout the classification, (2) a new emphasis on genetic studies, in particular, integration of molecular testing to help personalize treatment strategies for advanced lung cancer patients, (3) a new classification for small biopsies and cytology similar to that proposed in the 2011 Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society classification, (4) a completely different approach to lung adenocarcinoma as proposed by the 2011 Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society classification, (5) restricting the diagnosis of large cell carcinoma only to resected tumors that lack any clear morphologic or immunohistochemical differentiation with reclassification of the remaining former large cell carcinoma subtypes into different categories, (6) reclassifying squamous cell carcinomas into keratinizing, nonkeratinizing, and basaloid subtypes with the nonkeratinizing tumors requiring immunohistochemistry proof of squamous differentiation, (7) grouping of neuroendocrine tumors together in one category, (8) adding NUT carcinoma, (9) changing the term sclerosing hemangioma to sclerosing pneumocytoma, (10) changing the name hamartoma to "pulmonary hamartoma," (11) creating a group of PEComatous tumors that include (a) lymphangioleiomyomatosis, (b) PEComa, benign (with clear cell tumor as a variant) and (c) PEComa, malignant, (12) introducing the entity pulmonary myxoid sarcoma with an EWSR1-CREB1 translocation, (13) adding the entities myoepithelioma and myoepithelial carcinomas, which can show EWSR1 gene rearrangements, (14) recognition of usefulness of WWTR1-CAMTA1 fusions in diagnosis of epithelioid

Self-Expandable Stenting over a Stent Graft for the Exclusion of a Carotid Stump: Troubleshooting for Device Incompatibility

International Nuclear Information System (INIS)

Youn, Sung Won; Kim, Ho Kyun; Do, Jin Kook; Kim, Young Whan

2011-01-01

Carotid stump, the blind remnant of an occluded internal carotid artery, can be a potential source of microemboli, and warrants its exclusion from the vascular lumen to prevent the recurrence of a microembolism. In a 69-year-old male with a symptomatic carotid stump and acute angle between left common carotid artery and aortic arch, a 7-Fr. shuttle sheath was scarcely placed into the left carotid artery but the 7-mm-diameter stent-graft-loading balloon could not be inserted into the 7-Fr. shuttle sheath. With the mounting a stent graft over a 5-mm balloon, the balloon-expandable stent graft was unfolded. The self-expandable stent was placed over the stent graft, and an 8-mm balloon was subsequently expanded. Self-expanding stenting can be useful for troubleshooting in a case of device incompatibility coming from the different calibers of the external and common carotid arteries for the successful exclusion of a symptomatic carotid stump.

Self-Expandable Stenting over a Stent Graft for the Exclusion of a Carotid Stump: Troubleshooting for Device Incompatibility

Energy Technology Data Exchange (ETDEWEB)

Youn, Sung Won; Kim, Ho Kyun [Dept. of Radiology, Catholic University of Daegu School of Medicine, Daegu (Korea, Republic of); Do, Jin Kook [Dept. of Neurology, Catholic University of Daegu School of Medicine, Daegu (Korea, Republic of); Kim, Young Whan [Dept. of Radiology, University College of Medicine, Daegu (Korea, Republic of)

2011-12-15

Carotid stump, the blind remnant of an occluded internal carotid artery, can be a potential source of microemboli, and warrants its exclusion from the vascular lumen to prevent the recurrence of a microembolism. In a 69-year-old male with a symptomatic carotid stump and acute angle between left common carotid artery and aortic arch, a 7-Fr. shuttle sheath was scarcely placed into the left carotid artery but the 7-mm-diameter stent-graft-loading balloon could not be inserted into the 7-Fr. shuttle sheath. With the mounting a stent graft over a 5-mm balloon, the balloon-expandable stent graft was unfolded. The self-expandable stent was placed over the stent graft, and an 8-mm balloon was subsequently expanded. Self-expanding stenting can be useful for troubleshooting in a case of device incompatibility coming from the different calibers of the external and common carotid arteries for the successful exclusion of a symptomatic carotid stump.

The capability of fiber Bragg grating sensors to measure amputees' trans-tibial stump/socket interface pressures.

Science.gov (United States)

Al-Fakih, Ebrahim A; Osman, Noor Azuan Abu; Eshraghi, Arezoo; Adikan, Faisal Rafiq Mahamd

2013-08-12

This study presents the first investigation into the capability of fiber Bragg grating (FBG) sensors to measure interface pressure between the stump and the prosthetic sockets of a trans-tibial amputee. FBG element(s) were recoated with and embedded in a thin layer of epoxy material to form a sensing pad, which was in turn embedded in a silicone polymer material to form a pressure sensor. The sensor was tested in real time by inserting a heavy-duty balloon into the socket and inflating it by using an air compressor. This test was conducted to examine the sensitivity and repeatability of the sensor when subjected to pressure from the stump of the trans-tibial amputee and to mimic the actual environment of the amputee's Patellar Tendon (PT) bar. The sensor exhibited a sensitivity of 127 pm/N and a maximum FSO hysteresis of around ~0.09 in real-time operation. Very good reliability was achieved when the sensor was utilized for in situ measurements. This study may lead to smart FBG-based amputee stump/socket structures for pressure monitoring in amputee socket systems, which will result in better-designed prosthetic sockets that ensure improved patient satisfaction.

Deep learning based classification for head and neck cancer detection with hyperspectral imaging in an animal model

Science.gov (United States)

Ma, Ling; Lu, Guolan; Wang, Dongsheng; Wang, Xu; Chen, Zhuo Georgia; Muller, Susan; Chen, Amy; Fei, Baowei

2017-03-01

Hyperspectral imaging (HSI) is an emerging imaging modality that can provide a noninvasive tool for cancer detection and image-guided surgery. HSI acquires high-resolution images at hundreds of spectral bands, providing big data to differentiating different types of tissue. We proposed a deep learning based method for the detection of head and neck cancer with hyperspectral images. Since the deep learning algorithm can learn the feature hierarchically, the learned features are more discriminative and concise than the handcrafted features. In this study, we adopt convolutional neural networks (CNN) to learn the deep feature of pixels for classifying each pixel into tumor or normal tissue. We evaluated our proposed classification method on the dataset containing hyperspectral images from 12 tumor-bearing mice. Experimental results show that our method achieved an average accuracy of 91.36%. The preliminary study demonstrated that our deep learning method can be applied to hyperspectral images for detecting head and neck tumors in animal models.

MO-DE-207B-03: Improved Cancer Classification Using Patient-Specific Biological Pathway Information Via Gene Expression Data

Energy Technology Data Exchange (ETDEWEB)

Young, M; Craft, D [Massachusetts General Hospital and Harvard Medical School, Boston, MA (United States)

2016-06-15

Purpose: To develop an efficient, pathway-based classification system using network biology statistics to assist in patient-specific response predictions to radiation and drug therapies across multiple cancer types. Methods: We developed PICS (Pathway Informed Classification System), a novel two-step cancer classification algorithm. In PICS, a matrix m of mRNA expression values for a patient cohort is collapsed into a matrix p of biological pathways. The entries of p, which we term pathway scores, are obtained from either principal component analysis (PCA), normal tissue centroid (NTC), or gene expression deviation (GED). The pathway score matrix is clustered using both k-means and hierarchical clustering, and a clustering is judged by how well it groups patients into distinct survival classes. The most effective pathway scoring/clustering combination, per clustering p-value, thus generates various ‘signatures’ for conventional and functional cancer classification. Results: PICS successfully regularized large dimension gene data, separated normal and cancerous tissues, and clustered a large patient cohort spanning six cancer types. Furthermore, PICS clustered patient cohorts into distinct, statistically-significant survival groups. For a suboptimally-debulked ovarian cancer set, the pathway-classified Kaplan-Meier survival curve (p = .00127) showed significant improvement over that of a prior gene expression-classified study (p = .0179). For a pancreatic cancer set, the pathway-classified Kaplan-Meier survival curve (p = .00141) showed significant improvement over that of a prior gene expression-classified study (p = .04). Pathway-based classification confirmed biomarkers for the pyrimidine, WNT-signaling, glycerophosphoglycerol, beta-alanine, and panthothenic acid pathways for ovarian cancer. Despite its robust nature, PICS requires significantly less run time than current pathway scoring methods. Conclusion: This work validates the PICS method to improve

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

International Nuclear Information System (INIS)

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

2014-01-01

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

Organizational change in quality management aspects: a quantitative proposal for classification

Directory of Open Access Journals (Sweden)

André Tavares de Aquino

Full Text Available Abstract Periodically, organizations need to change the quality management aspects of processes and products in order to suit the demands of their internal and external (consumer and competitor market environments. In the context of the present study, quality management changes involve tools, programs, methods, standards and procedures that can be applied. The purpose of this study is to help senior management to identify types of change and, consequently, determine how it should be correctly conducted within an organization. The methodology involves a classification model, with multicriteria support, and three organizational change ratings were adopted (the extremes, type I and type II, as confirmed in the literature, and the intermediary, proposed herein. The multicriteria method used was ELECTRE TRI and the model was applied to two companies of the Textile Local Productive Arrangement in Pernambuco, Brazil. The results are interesting and show the consistency and coherence of the proposed classification model.

Stratification and Prognostic Relevance of Jass’s Molecular Classification of Colorectal Cancer

International Nuclear Information System (INIS)

Zlobec, Inti; Bihl, Michel P.; Foerster, Anja; Rufle, Alex; Terracciano, Luigi; Lugli, Alessandro

2012-01-01

Background: The current proposed model of colorectal tumorigenesis is based primarily on CpG island methylator phenotype (CIMP), microsatellite instability (MSI), KRAS, BRAF, and methylation status of 0-6-Methylguanine DNA Methyltransferase (MGMT) and classifies tumors into five subgroups. The aim of this study is to validate this molecular classification and test its prognostic relevance. Methods: Three hundred two patients were included in this study. Molecular analysis was performed for five CIMP-related promoters (CRABP1, MLH1, p16INK4a, CACNA1G, NEUROG1), MGMT, MSI, KRAS, and BRAF. Methylation in at least 4 promoters or in one to three promoters was considered CIMP-high and CIMP-low (CIMP-H/L), respectively. Results: CIMP-H, CIMP-L, and CIMP-negative were found in 7.1, 43, and 49.9% cases, respectively. One hundred twenty-three tumors (41%) could not be classified into any one of the proposed molecular subgroups, including 107 CIMP-L, 14 CIMP-H, and two CIMP-negative cases. The 10 year survival rate for CIMP-high patients [22.6% (95%CI: 7–43)] was significantly lower than for CIMP-L or CIMP-negative (p = 0.0295). Only the combined analysis of BRAF and CIMP (negative versus L/H) led to distinct prognostic subgroups. Conclusion: Although CIMP status has an effect on outcome, our results underline the need for standardized definitions of low- and high-level CIMP, which clearly hinders an effective prognostic and molecular classification of colorectal cancer.

Stratification and Prognostic Relevance of Jass’s Molecular Classification of Colorectal Cancer

Energy Technology Data Exchange (ETDEWEB)

Zlobec, Inti [Institute of Pathology, University of Bern, Bern (Switzerland); Institute for Pathology, University Hospital Basel, Basel (Switzerland); Bihl, Michel P.; Foerster, Anja; Rufle, Alex; Terracciano, Luigi [Institute for Pathology, University Hospital Basel, Basel (Switzerland); Lugli, Alessandro, E-mail: inti.zlobec@pathology.unibe.ch [Institute of Pathology, University of Bern, Bern (Switzerland); Institute for Pathology, University Hospital Basel, Basel (Switzerland)

2012-02-27

Background: The current proposed model of colorectal tumorigenesis is based primarily on CpG island methylator phenotype (CIMP), microsatellite instability (MSI), KRAS, BRAF, and methylation status of 0-6-Methylguanine DNA Methyltransferase (MGMT) and classifies tumors into five subgroups. The aim of this study is to validate this molecular classification and test its prognostic relevance. Methods: Three hundred two patients were included in this study. Molecular analysis was performed for five CIMP-related promoters (CRABP1, MLH1, p16INK4a, CACNA1G, NEUROG1), MGMT, MSI, KRAS, and BRAF. Methylation in at least 4 promoters or in one to three promoters was considered CIMP-high and CIMP-low (CIMP-H/L), respectively. Results: CIMP-H, CIMP-L, and CIMP-negative were found in 7.1, 43, and 49.9% cases, respectively. One hundred twenty-three tumors (41%) could not be classified into any one of the proposed molecular subgroups, including 107 CIMP-L, 14 CIMP-H, and two CIMP-negative cases. The 10 year survival rate for CIMP-high patients [22.6% (95%CI: 7–43)] was significantly lower than for CIMP-L or CIMP-negative (p = 0.0295). Only the combined analysis of BRAF and CIMP (negative versus L/H) led to distinct prognostic subgroups. Conclusion: Although CIMP status has an effect on outcome, our results underline the need for standardized definitions of low- and high-level CIMP, which clearly hinders an effective prognostic and molecular classification of colorectal cancer.

Stratification and prognostic relevance of Jass’s molecular classification of colorectal cancer

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Inti eZlobec

2012-02-01

Full Text Available Background: The current proposed model of colorectal tumorigenesis is based primarily on CpG island methylator phenotype (CIMP, microsatellite instability (MSI, KRAS, BRAF, and methylation status of 0-6-Methylguanine DNA Methyltransferase (MGMT and classifies tumors into 5 subgroups. The aim of this study is to validate this molecular classification and test its prognostic relevance. Methods: 302 patients were included in this study. Molecular analysis was performed for 5 CIMP-related promoters (CRABP1, MLH1, p16INK4a, CACNA1G, NEUROG1, MGMT, MSI, KRAS and BRAF. Tumors were CIMP-high or CIMP-low if ≥4 and 1-3 promoters were methylated, respectively. Results: CIMP-high, CIMP-low and CIMP–negative were found in 7.1%, 43% and 49.9% cases, respectively. 123 tumors (41% could not be classified into any one of the proposed molecular subgroups, including 107 CIMP-low, 14 CIMP-high and 2 CIMP-negative cases. The 10-year survival rate for CIMP-high patients (22.6% (95%CI: 7-43 was significantly lower than for CIMP-low or CIMP-negative (p=0.0295. Only the combined analysis of BRAF and CIMP (negative versus low/high led to distinct prognostic subgroups. Conclusion: Although CIMP status has an effect on outcome, our results underline the need for standardized definitions of low- and high-level CIMP, which clearly hinders an effective prognostic and molecular classification of colorectal cancer.

A Proposed Functional Abilities Classification Tool for Developmental Disorders Affecting Learning and Behaviour

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Benjamin Klein

2018-02-01

Full Text Available Children with developmental disorders affecting learning and behaviour (DDALB (e.g., attention, social communication, language, and learning disabilities, etc. require individualized support across multiple environments to promote participation, quality of life, and developmental outcomes. Support to enhance participation is based largely on individual profiles of functioning (e.g., communication, cognitive, social skills, executive functioning, etc., which are highly heterogeneous within medical diagnoses. Currently educators, clinicians, and parents encounter widespread difficulties in meeting children’s needs as there is lack of universal classification of functioning and disability for use in school environments. Objective: a practical tool for functional classification broadly applicable for children with DDALB could facilitate the collaboration, identification of points of entry of support, individual program planning, and reassessment in a transparent, equitable process based on functional need and context. We propose such a tool, the Functional Abilities Classification Tool (FACT based on the concepts of the ICF (International Classification of Functioning, Disability and Health. FACT is intended to provide ability and participation classification that is complementary to medical diagnosis. For children presenting with difficulties, the proposed tool initially classifies participation over several environments. Then, functional abilities are classified and personal factors and environment are described. Points of entry for support are identified given an analysis of functional ability profile, personal factors, environmental features, and pattern of participation. Conclusion: case examples, use of the tool and implications for children, agencies, and the system are described.

Classification of breast cancer patients using somatic mutation profiles and machine learning approaches.

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Vural, Suleyman; Wang, Xiaosheng; Guda, Chittibabu

2016-08-26

The high degree of heterogeneity observed in breast cancers makes it very difficult to classify the cancer patients into distinct clinical subgroups and consequently limits the ability to devise effective therapeutic strategies. Several classification strategies based on ER/PR/HER2 expression or the expression profiles of a panel of genes have helped, but such methods often produce misleading results due to their dynamic nature. In contrast, somatic DNA mutations are relatively stable and lead to initiation and progression of many sporadic cancers. Hence in this study, we explore the use of gene mutation profiles to classify, characterize and predict the subgroups of breast cancers. We analyzed the whole exome sequencing data from 358 ethnically similar breast cancer patients in The Cancer Genome Atlas (TCGA) project. Somatic and non-synonymous single nucleotide variants identified from each patient were assigned a quantitative score (C-score) that represents the extent of negative impact on the gene function. Using these scores with non-negative matrix factorization method, we clustered the patients into three subgroups. By comparing the clinical stage of patients, we identified an early-stage-enriched and a late-stage-enriched subgroup. Comparison of the mutation scores of early and late-stage-enriched subgroups identified 358 genes that carry significantly higher mutations rates in the late stage subgroup. Functional characterization of these genes revealed important functional gene families that carry a heavy mutational load in the late state rich subgroup of patients. Finally, using the identified subgroups, we also developed a supervised classification model to predict the stage of the patients. This study demonstrates that gene mutation profiles can be effectively used with unsupervised machine-learning methods to identify clinically distinguishable breast cancer subgroups. The classification model developed in this method could provide a reasonable

Low Dimensional Representation of Fisher Vectors for Microscopy Image Classification.

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Song, Yang; Li, Qing; Huang, Heng; Feng, Dagan; Chen, Mei; Cai, Weidong

2017-08-01

Microscopy image classification is important in various biomedical applications, such as cancer subtype identification, and protein localization for high content screening. To achieve automated and effective microscopy image classification, the representative and discriminative capability of image feature descriptors is essential. To this end, in this paper, we propose a new feature representation algorithm to facilitate automated microscopy image classification. In particular, we incorporate Fisher vector (FV) encoding with multiple types of local features that are handcrafted or learned, and we design a separation-guided dimension reduction method to reduce the descriptor dimension while increasing its discriminative capability. Our method is evaluated on four publicly available microscopy image data sets of different imaging types and applications, including the UCSB breast cancer data set, MICCAI 2015 CBTC challenge data set, and IICBU malignant lymphoma, and RNAi data sets. Our experimental results demonstrate the advantage of the proposed low-dimensional FV representation, showing consistent performance improvement over the existing state of the art and the commonly used dimension reduction techniques.

What should an ideal spinal injury classification system consist of? A methodological review and conceptual proposal for future classifications.

NARCIS (Netherlands)

Middendorp, J.J. van; Audige, L.; Hanson, B.; Chapman, J.R.; Hosman, A.J.F.

2010-01-01

Since Bohler published the first categorization of spinal injuries based on plain radiographic examinations in 1929, numerous classifications have been proposed. Despite all these efforts, however, only a few have been tested for reliability and validity. This methodological, conceptual review

Cross-platform analysis of cancer microarray data improves gene expression based classification of phenotypes

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Eils Roland

2005-11-01

Full Text Available Abstract Background The extensive use of DNA microarray technology in the characterization of the cell transcriptome is leading to an ever increasing amount of microarray data from cancer studies. Although similar questions for the same type of cancer are addressed in these different studies, a comparative analysis of their results is hampered by the use of heterogeneous microarray platforms and analysis methods. Results In contrast to a meta-analysis approach where results of different studies are combined on an interpretative level, we investigate here how to directly integrate raw microarray data from different studies for the purpose of supervised classification analysis. We use median rank scores and quantile discretization to derive numerically comparable measures of gene expression from different platforms. These transformed data are then used for training of classifiers based on support vector machines. We apply this approach to six publicly available cancer microarray gene expression data sets, which consist of three pairs of studies, each examining the same type of cancer, i.e. breast cancer, prostate cancer or acute myeloid leukemia. For each pair, one study was performed by means of cDNA microarrays and the other by means of oligonucleotide microarrays. In each pair, high classification accuracies (> 85% were achieved with training and testing on data instances randomly chosen from both data sets in a cross-validation analysis. To exemplify the potential of this cross-platform classification analysis, we use two leukemia microarray data sets to show that important genes with regard to the biology of leukemia are selected in an integrated analysis, which are missed in either single-set analysis. Conclusion Cross-platform classification of multiple cancer microarray data sets yields discriminative gene expression signatures that are found and validated on a large number of microarray samples, generated by different laboratories and

Actionable gene-based classification toward precision medicine in gastric cancer

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Hiroshi Ichikawa

2017-10-01

Full Text Available Abstract Background Intertumoral heterogeneity represents a significant hurdle to identifying optimized targeted therapies in gastric cancer (GC. To realize precision medicine for GC patients, an actionable gene alteration-based molecular classification that directly associates GCs with targeted therapies is needed. Methods A total of 207 Japanese patients with GC were included in this study. Formalin-fixed, paraffin-embedded (FFPE tumor tissues were obtained from surgical or biopsy specimens and were subjected to DNA extraction. We generated comprehensive genomic profiling data using a 435-gene panel including 69 actionable genes paired with US Food and Drug Administration-approved targeted therapies, and the evaluation of Epstein-Barr virus (EBV infection and microsatellite instability (MSI status. Results Comprehensive genomic sequencing detected at least one alteration of 435 cancer-related genes in 194 GCs (93.7% and of 69 actionable genes in 141 GCs (68.1%. We classified the 207 GCs into four The Cancer Genome Atlas (TCGA subtypes using the genomic profiling data; EBV (N = 9, MSI (N = 17, chromosomal instability (N = 119, and genomically stable subtype (N = 62. Actionable gene alterations were not specific and were widely observed throughout all TCGA subtypes. To discover a novel classification which more precisely selects candidates for targeted therapies, 207 GCs were classified using hypermutated phenotype and the mutation profile of 69 actionable genes. We identified a hypermutated group (N = 32, while the others (N = 175 were sub-divided into six clusters including five with actionable gene alterations: ERBB2 (N = 25, CDKN2A, and CDKN2B (N = 10, KRAS (N = 10, BRCA2 (N = 9, and ATM cluster (N = 12. The clinical utility of this classification was demonstrated by a case of unresectable GC with a remarkable response to anti-HER2 therapy in the ERBB2 cluster. Conclusions This actionable gene

Recursive Partitioning Analysis for New Classification of Patients With Esophageal Cancer Treated by Chemoradiotherapy

International Nuclear Information System (INIS)

Nomura, Motoo; Shitara, Kohei; Kodaira, Takeshi; Kondoh, Chihiro; Takahari, Daisuke; Ura, Takashi; Kojima, Hiroyuki; Kamata, Minoru; Muro, Kei; Sawada, Satoshi

2012-01-01

Background: The 7th edition of the American Joint Committee on Cancer staging system does not include lymph node size in the guidelines for staging patients with esophageal cancer. The objectives of this study were to determine the prognostic impact of the maximum metastatic lymph node diameter (ND) on survival and to develop and validate a new staging system for patients with esophageal squamous cell cancer who were treated with definitive chemoradiotherapy (CRT). Methods: Information on 402 patients with esophageal cancer undergoing CRT at two institutions was reviewed. Univariate and multivariate analyses of data from one institution were used to assess the impact of clinical factors on survival, and recursive partitioning analysis was performed to develop the new staging classification. To assess its clinical utility, the new classification was validated using data from the second institution. Results: By multivariate analysis, gender, T, N, and ND stages were independently and significantly associated with survival (p < 0.05). The resulting new staging classification was based on the T and ND. The four new stages led to good separation of survival curves in both the developmental and validation datasets (p < 0.05). Conclusions: Our results showed that lymph node size is a strong independent prognostic factor and that the new staging system, which incorporated lymph node size, provided good prognostic power, and discriminated effectively for patients with esophageal cancer undergoing CRT.

False-positive reduction in CAD mass detection using a competitive classification strategy

International Nuclear Information System (INIS)

Li Lihua; Zheng Yang; Zhang Lei; Clark, Robert A.

2001-01-01

High false-positive (FP) rate remains to be one of the major problems to be solved in CAD study because too many false-positively cued signals will potentially degrade the performance of detecting true-positive regions and increase the call-back rate in CAD environment. In this paper, we proposed a novel classification method for FP reduction, where the conventional 'hard' decision classifier is cascaded with a 'soft' decision classification with the objective to reduce false-positives in the cases with multiple FPs retained after the 'hard' decision classification. The 'soft' classification takes a competitive classification strategy in which only the 'best' ones are selected from the pre-classified suspicious regions as the true mass in each case. A neural network structure is designed to implement the proposed competitive classification. Comparative studies of FP reduction on a database of 79 images by a 'hard' decision classification and a combined 'hard'-'soft' classification method demonstrated the efficiency of the proposed classification strategy. For example, for the high FP sub-database which has only 31.7% of total images but accounts for 63.5% of whole FPs generated in single 'hard' classification, the FPs can be reduced for 56% (from 8.36 to 3.72 per image) by using the proposed method at the cost of 1% TP loss (from 69% to 68%) in whole database, while it can only be reduced for 27% (from 8.36 to 6.08 per image) by simply increasing the threshold of 'hard' classifier with a cost of TP loss as high as 14% (from 69% to 55%). On the average in whole database, the FP reduction by hybrid 'hard'-'soft' classification is 1.58 per image as compared to 1.11 by 'hard' classification at the TP costs described above. Because the cases with high dense tissue are of higher risk of cancer incidence and false-negative detection in mammogram screening, and usually generate more FPs in CAD detection, the method proposed in this paper will be very helpful in improving

The Capability of Fiber Bragg Grating Sensors to Measure Amputees’ Trans-Tibial Stump/Socket Interface Pressures

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Faisal Rafiq Mahamd Adikan

2013-08-01

Full Text Available This study presents the first investigation into the capability of fiber Bragg grating (FBG sensors to measure interface pressure between the stump and the prosthetic sockets of a trans-tibial amputee. FBG element(s were recoated with and embedded in a thin layer of epoxy material to form a sensing pad, which was in turn embedded in a silicone polymer material to form a pressure sensor. The sensor was tested in real time by inserting a heavy-duty balloon into the socket and inflating it by using an air compressor. This test was conducted to examine the sensitivity and repeatability of the sensor when subjected to pressure from the stump of the trans-tibial amputee and to mimic the actual environment of the amputee’s Patellar Tendon (PT bar. The sensor exhibited a sensitivity of 127 pm/N and a maximum FSO hysteresis of around ~0.09 in real-time operation. Very good reliability was achieved when the sensor was utilized for in situ measurements. This study may lead to smart FBG-based amputee stump/socket structures for pressure monitoring in amputee socket systems, which will result in better-designed prosthetic sockets that ensure improved patient satisfaction.

Long-term Prostate-specific Antigen Velocity in Improved Classification of Prostate Cancer Risk and Mortality

DEFF Research Database (Denmark)

Ørsted, David Dynnes; Bojesen, Stig E; Kamstrup, Pia R

2013-01-01

BACKGROUND: It remains unclear whether adding long-term prostate-specific antigen velocity (PSAV) to baseline PSA values improves classification of prostate cancer (PCa) risk and mortality in the general population. OBJECTIVE: To determine whether long-term PSAV improves classification of PCa risk...

A Proposal to Develop Interactive Classification Technology

Science.gov (United States)

deBessonet, Cary

1998-01-01

Research for the first year was oriented towards: 1) the design of an interactive classification tool (ICT); and 2) the development of an appropriate theory of inference for use in ICT technology. The general objective was to develop a theory of classification that could accommodate a diverse array of objects, including events and their constituent objects. Throughout this report, the term "object" is to be interpreted in a broad sense to cover any kind of object, including living beings, non-living physical things, events, even ideas and concepts. The idea was to produce a theory that could serve as the uniting fabric of a base technology capable of being implemented in a variety of automated systems. The decision was made to employ two technologies under development by the principal investigator, namely, SMS (Symbolic Manipulation System) and SL (Symbolic Language) [see debessonet, 1991, for detailed descriptions of SMS and SL]. The plan was to enhance and modify these technologies for use in an ICT environment. As a means of giving focus and direction to the proposed research, the investigators decided to design an interactive, classificatory tool for use in building accessible knowledge bases for selected domains. Accordingly, the proposed research was divisible into tasks that included: 1) the design of technology for classifying domain objects and for building knowledge bases from the results automatically; 2) the development of a scheme of inference capable of drawing upon previously processed classificatory schemes and knowledge bases; and 3) the design of a query/ search module for accessing the knowledge bases built by the inclusive system. The interactive tool for classifying domain objects was to be designed initially for textual corpora with a view to having the technology eventually be used in robots to build sentential knowledge bases that would be supported by inference engines specially designed for the natural or man-made environments in which the

Cross-Disciplinary Analysis of Lymph Node Classification in Lung Cancer on CT Scanning.

Science.gov (United States)

El-Sherief, Ahmed H; Lau, Charles T; Obuchowski, Nancy A; Mehta, Atul C; Rice, Thomas W; Blackstone, Eugene H

2017-04-01

Accurate and consistent regional lymph node classification is an important element in the staging and multidisciplinary management of lung cancer. Regional lymph node definition sets-lymph node maps-have been created to standardize regional lymph node classification. In 2009, the International Association for the Study of Lung Cancer (IASLC) introduced a lymph node map to supersede all preexisting lymph node maps. Our aim was to study if and how lung cancer specialists apply the IASLC lymph node map when classifying thoracic lymph nodes encountered on CT scans during lung cancer staging. From April 2013 through July 2013, invitations were distributed to all members of the Fleischner Society, Society of Thoracic Radiology, General Thoracic Surgical Club, and the American Association of Bronchology and Interventional Pulmonology to participate in an anonymous online image-based and text-based 20-question survey regarding lymph node classification for lung cancer staging on CT imaging. Three hundred thirty-seven people responded (approximately 25% participation). Respondents consisted of self-reported thoracic radiologists (n = 158), thoracic surgeons (n = 102), and pulmonologists who perform endobronchial ultrasonography (n = 77). Half of the respondents (50%; 95% CI, 44%-55%) reported using the IASLC lymph node map in daily practice, with no significant differences between subspecialties. A disparity was observed between the IASLC definition sets and their interpretation and application on CT scans, in particular for lymph nodes near the thoracic inlet, anterior to the trachea, anterior to the tracheal bifurcation, near the ligamentum arteriosum, between the bronchus intermedius and esophagus, in the internal mammary space, and adjacent to the heart. Use of older lymph node maps and inconsistencies in interpretation and application of definitions in the IASLC lymph node map may potentially lead to misclassification of stage and suboptimal management of lung

Proposal of an ISO Standard: Classification of Transients and Accidents for Pressurized Water Reactors

Energy Technology Data Exchange (ETDEWEB)

Jo, Jong Chull [Korea Institute of Nuclear Safety, Daejeon (Korea, Republic of); Chung, Bub Dong; Lee, Doo-Jeong; Kim, Jong In; Yoon, Ju Hyun [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of); Jeong, Jae Jun [Pusan National Univ., Busan (Korea, Republic of); Kim, An Sup; Lee, Sang Yoon [Korea Electric Association, Seoul (Korea, Republic of)

2016-05-15

Classification of the events for a nuclear power plant is a fundamental basis for defining nuclear safety functions, safety systems performing those functions, and specific acceptance criteria for safety analyses. Presently, the approaches for the event classification adopted by the nuclear suppliers are different, which makes a nuclear technology trade barrier. The IAEA and WENRA are making efforts to establish general requirements or guidelines on the classification of either plant states or defence-in-depth levels for the design of nuclear power plants. However, the requirements and guidelines do not provide the details for practical application to various types of commercial PWRs. Recently, Korea proposed a new ISO standardisation project to develop a harmonized or consolidated international standard for classifying the events in PWRs and for defining (or imposing) the acceptance criteria for reactor design and/or radiation protection corresponding to each event class. This paper briefs the method with strategies for developing the standard, the current various practices of the PWR event classification and acceptance criteria developed or adopted by several organizations in USA and Europe, and a draft of the proposed standard. The proposed standard will affect all the relevant stakeholders such as reactor designers, vendors, suppliers, utilities, regulatory bodies, and publics of the leading countries in the area of nuclear industry as well as utilities, regulatory bodies, and publics of the newly entering (starting) countries. It is expected that all of the stakeholders will benefit from the proposed deliverable which provides an internationally harmonized standard for classifying the PWR events as follows: The reactor design bases for assuring safety and related technical information can be effectively communicated and shared among them resulting in enhancement of the global nuclear safety and fosterage of the global nuclear trade. The countries starting

On the International Agency for Research on Cancer classification of glyphosate as a probable human carcinogen.

Science.gov (United States)

Tarone, Robert E

2018-01-01

The recent classification by International Agency for Research on Cancer (IARC) of the herbicide glyphosate as a probable human carcinogen has generated considerable discussion. The classification is at variance with evaluations of the carcinogenic potential of glyphosate by several national and international regulatory bodies. The basis for the IARC classification is examined under the assumptions that the IARC criteria are reasonable and that the body of scientific studies determined by IARC staff to be relevant to the evaluation of glyphosate by the Monograph Working Group is sufficiently complete. It is shown that the classification of glyphosate as a probable human carcinogen was the result of a flawed and incomplete summary of the experimental evidence evaluated by the Working Group. Rational and effective cancer prevention activities depend on scientifically sound and unbiased assessments of the carcinogenic potential of suspected agents. Implications of the erroneous classification of glyphosate with respect to the IARC Monograph Working Group deliberative process are discussed.

Stump-to-mill timber production cost equations for cable logging eastern hardwoods

Science.gov (United States)

Chris B. LeDoux; Chris B. LeDoux

1985-01-01

Logging cost simulators and data from logging cost studies have been assembled and converted into a series of equations that can be used to estimate the stump-to-mill cost of cable logging in mountainous terrain in the Eastern United States. These equations include the use of two small and four mediumsize cable yarders and are appropriate for harvested trees ranging in...

Proposal plan of classification faceted for federal universities

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Renata Santos Brandão

2017-09-01

Full Text Available This study aims to present a faceted classification plan for the archival management of documents in the federal universities of Brazil. For this, was done a literature review on the archival management in Brazil, the types of classification plans and the theory of the Ranganathan faceted classification, through searches in databases in the areas of Librarianship and Archivology. It was identified the classification plan used in the Federal Institutions of Higher Education to represent the functional facet and created the structural classification plan to represent the structural facet. The two classification plans were inserted into a digital repository management system to give rise to the faceted classification plan. The system used was Tainacan, free software wordpress-based used in digital document management. The developed faceted classification plan allows the user to choose and even combine the way to look for the information that guarantees agreater efficiency in the information retrieval.

Molecular classification of gastric cancer: a new paradigm.

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Shah, Manish A; Khanin, Raya; Tang, Laura; Janjigian, Yelena Y; Klimstra, David S; Gerdes, Hans; Kelsen, David P

2011-05-01

Gastric cancer may be subdivided into 3 distinct subtypes--proximal, diffuse, and distal gastric cancer--based on histopathologic and anatomic criteria. Each subtype is associated with unique epidemiology. Our aim is to test the hypothesis that these distinct gastric cancer subtypes may also be distinguished by gene expression analysis. Patients with localized gastric adenocarcinoma being screened for a phase II preoperative clinical trial (National Cancer Institute, NCI #5917) underwent endoscopic biopsy for fresh tumor procurement. Four to 6 targeted biopsies of the primary tumor were obtained. Macrodissection was carried out to ensure more than 80% carcinoma in the sample. HG-U133A GeneChip (Affymetrix) was used for cDNA expression analysis, and all arrays were processed and analyzed using the Bioconductor R-package. Between November 2003 and January 2006, 57 patients were screened to identify 36 patients with localized gastric cancer who had adequate RNA for expression analysis. Using supervised analysis, we built a classifier to distinguish the 3 gastric cancer subtypes, successfully classifying each into tightly grouped clusters. Leave-one-out cross-validation error was 0.14, suggesting that more than 85% of samples were classified correctly. Gene set analysis with the false discovery rate set at 0.25 identified several pathways that were differentially regulated when comparing each gastric cancer subtype to adjacent normal stomach. Subtypes of gastric cancer that have epidemiologic and histologic distinctions are also distinguished by gene expression data. These preliminary data suggest a new classification of gastric cancer with implications for improving our understanding of disease biology and identification of unique molecular drivers for each gastric cancer subtype. ©2011 AACR.

Pathological Bases for a Robust Application of Cancer Molecular Classification

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Salvador J. Diaz-Cano

2015-04-01

Full Text Available Any robust classification system depends on its purpose and must refer to accepted standards, its strength relying on predictive values and a careful consideration of known factors that can affect its reliability. In this context, a molecular classification of human cancer must refer to the current gold standard (histological classification and try to improve it with key prognosticators for metastatic potential, staging and grading. Although organ-specific examples have been published based on proteomics, transcriptomics and genomics evaluations, the most popular approach uses gene expression analysis as a direct correlate of cellular differentiation, which represents the key feature of the histological classification. RNA is a labile molecule that varies significantly according with the preservation protocol, its transcription reflect the adaptation of the tumor cells to the microenvironment, it can be passed through mechanisms of intercellular transference of genetic information (exosomes, and it is exposed to epigenetic modifications. More robust classifications should be based on stable molecules, at the genetic level represented by DNA to improve reliability, and its analysis must deal with the concept of intratumoral heterogeneity, which is at the origin of tumor progression and is the byproduct of the selection process during the clonal expansion and progression of neoplasms. The simultaneous analysis of multiple DNA targets and next generation sequencing offer the best practical approach for an analytical genomic classification of tumors.

The quest for methods to identify longleaf pine stump relicts in Southeastern Virginia

Science.gov (United States)

Thomas L. Eberhardt; Philip M. Sheridan; Chi-Leung So; Arvind A.R. Bhuta; Karen G. Reed

2015-01-01

The discovery of lightwood and turpentine stumps in southeastern Virginia raised questions about the true historical range for longleaf pine (Pinus palustris Mill.). Several investigative studies were therefore carried out to develop a method to determine the taxa of these relicts. Chemical approaches included the use of near infrared (NIR) spectroscopy coupled with...

The history of female genital tract malformation classifications and proposal of an updated system.

Science.gov (United States)

Acién, Pedro; Acién, Maribel I

2011-01-01

A correct classification of malformations of the female genital tract is essential to prevent unnecessary and inadequate surgical operations and to compare reproductive results. An ideal classification system should be based on aetiopathogenesis and should suggest the appropriate therapeutic strategy. We conducted a systematic review of relevant articles found in PubMed, Scopus, Scirus and ISI webknowledge, and analysis of historical collections of 'female genital malformations' and 'classifications'. Of 124 full-text articles assessed for eligibility, 64 were included because they contained original general, partial or modified classifications. All the existing classifications were analysed and grouped. The unification of terms and concepts was also analysed. Traditionally, malformations of the female genital tract have been catalogued and classified as Müllerian malformations due to agenesis, lack of fusion, the absence of resorption and lack of posterior development of the Müllerian ducts. The American Fertility Society classification of the late 1980s included seven basic groups of malformations also considering the Müllerian development and the relationship of the malformations to fertility. Other classifications are based on different aspects: functional, defects in vertical fusion, embryological or anatomical (Vagina, Cervix, Uterus, Adnex and Associated Malformation: VCUAM classification). However, an embryological-clinical classification system seems to be the most appropriate. Accepting the need for a new classification system of genitourinary malformations that considers the experience gained from the application of the current classification systems, the aetiopathogenesis and that also suggests the appropriate treatment, we proposed an update of our embryological-clinical classification as a new system with six groups of female genitourinary anomalies.

Classification of Breast Cancer Subtypes by combining Gene Expression and DNA Methylation Data

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List Markus

2014-06-01

Full Text Available Selecting the most promising treatment strategy for breast cancer crucially depends on determining the correct subtype. In recent years, gene expression profiling has been investigated as an alternative to histochemical methods. Since databases like TCGA provide easy and unrestricted access to gene expression data for hundreds of patients, the challenge is to extract a minimal optimal set of genes with good prognostic properties from a large bulk of genes making a moderate contribution to classification. Several studies have successfully applied machine learning algorithms to solve this so-called gene selection problem. However, more diverse data from other OMICS technologies are available, including methylation. We hypothesize that combining methylation and gene expression data could already lead to a largely improved classification model, since the resulting model will reflect differences not only on the transcriptomic, but also on an epigenetic level. We compared so-called random forest derived classification models based on gene expression and methylation data alone, to a model based on the combined features and to a model based on the gold standard PAM50. We obtained bootstrap errors of 10-20% and classification error of 1-50%, depending on breast cancer subtype and model. The gene expression model was clearly superior to the methylation model, which was also reflected in the combined model, which mainly selected features from gene expression data. However, the methylation model was able to identify unique features not considered as relevant by the gene expression model, which might provide deeper insights into breast cancer subtype differentiation on an epigenetic level.

Detection and classification of Breast Cancer in Wavelet Sub-bands of Fractal Segmented Cancerous Zones.

Science.gov (United States)

Shirazinodeh, Alireza; Noubari, Hossein Ahmadi; Rabbani, Hossein; Dehnavi, Alireza Mehri

2015-01-01

Recent studies on wavelet transform and fractal modeling applied on mammograms for the detection of cancerous tissues indicate that microcalcifications and masses can be utilized for the study of the morphology and diagnosis of cancerous cases. It is shown that the use of fractal modeling, as applied to a given image, can clearly discern cancerous zones from noncancerous areas. In this paper, for fractal modeling, the original image is first segmented into appropriate fractal boxes followed by identifying the fractal dimension of each windowed section using a computationally efficient two-dimensional box-counting algorithm. Furthermore, using appropriate wavelet sub-bands and image Reconstruction based on modified wavelet coefficients, it is shown that it is possible to arrive at enhanced features for detection of cancerous zones. In this paper, we have attempted to benefit from the advantages of both fractals and wavelets by introducing a new algorithm. By using a new algorithm named F1W2, the original image is first segmented into appropriate fractal boxes, and the fractal dimension of each windowed section is extracted. Following from that, by applying a maximum level threshold on fractal dimensions matrix, the best-segmented boxes are selected. In the next step, the segmented Cancerous zones which are candidates are then decomposed by utilizing standard orthogonal wavelet transform and db2 wavelet in three different resolution levels, and after nullifying wavelet coefficients of the image at the first scale and low frequency band of the third scale, the modified reconstructed image is successfully utilized for detection of breast cancer regions by applying an appropriate threshold. For detection of cancerous zones, our simulations indicate the accuracy of 90.9% for masses and 88.99% for microcalcifications detection results using the F1W2 method. For classification of detected mictocalcification into benign and malignant cases, eight features are identified and

Proposal of new classification of femoral trochanteric fracture by three-dimensional computed tomography and relationship to usual plain X-ray classification.

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Shoda, Etsuo; Kitada, Shimpei; Sasaki, Yu; Hirase, Hitoshi; Niikura, Takahiro; Lee, Sang Yang; Sakurai, Atsushi; Oe, Keisuke; Sasaki, Takeharu

2017-01-01

Classification of femoral trochanteric fractures is usually based on plain X-ray findings using the Evans, Jensen, or AO/OTA classification. However, complications such as nonunion and cut out of the lag screw or blade are seen even in stable fracture. This may be due to the difficulty of exact diagnosis of fracture pattern in plain X-ray. Computed tomography (CT) may provide more information about the fracture pattern, but such data are scarce. In the present study, it was performed to propose a classification system for femoral trochanteric fractures using three-dimensional CT (3D-CT) and investigate the relationship between this classification and conventional plain X-ray classification. Using three-dimensional (3D)-CT, fractures were classified as two, three, or four parts using combinations of the head, greater trochanter, lesser trochanter, and shaft. We identified five subgroups of three-part fractures according to the fracture pattern involving the greater and lesser trochanters. In total, 239 femoral trochanteric fractures (45 men, 194 women; average age, 84.4 years) treated in four hospitals were classified using our 3D-CT classification. The relationship between this 3D-CT classification and the AO/OTA, Evans, and Jensen X-ray classifications was investigated. In the 3D-CT classification, many fractures exhibited a large oblique fragment of the greater trochanter including the lesser trochanter. This fracture type was recognized as unstable in the 3D-CT classification but was often classified as stable in each X-ray classification. It is difficult to evaluate fracture patterns involving the greater trochanter, especially large oblique fragments including the lesser trochanter, using plain X-rays. The 3D-CT shows the fracture line very clearly, making it easy to classify the fracture pattern.

[Lower limb stump reconstruction with a functional calcaneo-plantar unit free flap. A series of 16 cases].

Science.gov (United States)

Malikov, S; Dubert, T; Koupatadze, D; Nabokov, V; Polosov, R

1999-04-01

The main objective of surgery, once amputation is inevitable, is to preserve a functional stump. This report describes the immediate reconstruction of 16 leg stumps in children by transfer of a functional calcaneo-plantar unit. Of these, 3 were thigh and 13 were lower leg reconstructions. Amputation was performed for tumor in 4 cases, and was due to accidents in the remaining twelve. The main technical features of flap preparation are preservation of the calcaneum branch and attachment of the heel skin to the greater tuberosity of the calcaneum. One case resulted in failure due to vascular thrombosis. The other 15 cases resulted in bone consolidation after an average of 45 days, sensitive protection by 70 days, and very good trophic and protective results. The provision of good distal pressure area encourages overall development of the child. There was no morbidity at the donor site, and because there is no major muscle mass in the distal fragment, the overall risk is very low compared to that of total proximal leg replantation. The transfer of functional calcaneo-plantar tissue as a single unit is the best strategy for one-step restoration of good distal support area for the stump. All surgeons liable to perform leg amputations should be aware of this technical approach.

Evaluation Methodology between Globalization and Localization Features Approaches for Skin Cancer Lesions Classification

Science.gov (United States)

Ahmed, H. M.; Al-azawi, R. J.; Abdulhameed, A. A.

2018-05-01

Huge efforts have been put in the developing of diagnostic methods to skin cancer disease. In this paper, two different approaches have been addressed for detection the skin cancer in dermoscopy images. The first approach uses a global method that uses global features for classifying skin lesions, whereas the second approach uses a local method that uses local features for classifying skin lesions. The aim of this paper is selecting the best approach for skin lesion classification. The dataset has been used in this paper consist of 200 dermoscopy images from Pedro Hispano Hospital (PH2). The achieved results are; sensitivity about 96%, specificity about 100%, precision about 100%, and accuracy about 97% for globalization approach while, sensitivity about 100%, specificity about 100%, precision about 100%, and accuracy about 100% for Localization Approach, these results showed that the localization approach achieved acceptable accuracy and better than globalization approach for skin cancer lesions classification.

Electromyographic Pattern Analysis and Classification for a Robotic Prosthetic Arm

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M. José H. Erazo Macias

2006-01-01

Full Text Available This paper deals with the statistical analysis and pattern classification of electromyographic signals from the biceps of a person with amputation below the humerus. Such signals collected from an amputation simulator are synergistically generated to produce discrete elbow movements. The purpose of this study is to utilise these signals to control an electrically driven prosthetic or orthotic elbow with minimum extra mental effort on the part of the subject. The results show very good separability of classes of movements when a learning pattern classification scheme is used, and a superposition of any composite motion to the three basic primitive motions—humeral rotation in and out, flexion and extension, and pronation and supination. Since no synergy was detected for the wrist movement, different inputs have to be provided for a grip. In addition, the method described is not limited by the location of the electrodes. For amputees with shorter stumps, synergistic signals could be obtained from the shoulder muscles. However, the presentation in this paper is limited to biceps signal classification only.

A proposed United States resource classification system

International Nuclear Information System (INIS)

Masters, C.D.

1980-01-01

Energy is a world-wide problem calling for world-wide communication to resolve the many supply and distribution problems. Essential to a communication problem are a definition and comparability of elements being communicated. The US Geological Survey, with the co-operation of the US Bureau of Mines and the US Department of Energy, has devised a classification system for all mineral resources, the principles of which, it is felt, offer the possibility of world communication. At present several other systems, extant or under development (Potential Gas Committee of the USA, United Nations Resource Committee, and the American Society of Testing and Materials) are internally consistent and provide easy communication linkage. The system in use by the uranium community in the United States of America, however, ties resource quantities to forward-cost dollar values rendering them inconsistent with other classifications and therefore not comparable. This paper develops the rationale for the new USGS resource classification and notes its benefits relative to a forward-cost classification and its relationship specifically to other current classifications. (author)

Predicting stump sprouting and competitive success of five oak species in southern Indiana

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Dale R. Weigel; Chao-Ying Joanne Peng

2002-01-01

We measured 2188 oak trees (Quercus spp.) on the Hoosier National Forest in southern Indiana before and 1, 5, and 10 years after clear-cutting to determine the influence of parent tree age, diameter breast height, and site index on the probability that there was one or more living sprouts per stump: (i) 1 year after clear-cutting (sprouting...

Reverse Anterolateral Thigh Flap to Revise a Below-knee Amputation Stump at the Mid-tibial Level

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Parviz Lionel Sadigh, MB ChB

2013-12-01

Full Text Available Summary: The reconstruction of defects around the knee often poses a challenge due to the limited availability of local soft tissues. Indeed, this same problem is encountered when attempting to revise a below-knee amputation stump. Moreover, due to a paucity of recipient vessels in those who have undergone previous amputation secondary to trauma, free-flap reconstruction is often challenging and not always successful. We report a case of a reverse anterolateral thigh (ALT flap used to revise a long below-knee amputation stump. Previous reports in the literature attest to the versatility of the reverse ALT to cover defects around the knee and proximal tibia, but to our knowledge, this is the first report of a reverse ALT reaching to the mid-tibial level.

Some regularities in invertebrate succession in different microhabitats on pine stumps

OpenAIRE

Franch, Joan

1989-01-01

Sixty eight pine stumps felled on known dates from one to sixteen years before the moment of sampling have been studied in the San Juan de la Peña woodland (province of Huesca). Four microhabitats were distinguished: bark, subcortical space, sapwood and heartwood. The object of the study is to compare the invertebrate macrofauna succession of the different microhabitats in order to find regularities among them. The biocenosis has not been completely studied: ipidae, diptera and annelidae are ...

Does the use of the 2009 FIGO classification of endometrial cancer impact on indications of the sentinel node biopsy?

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Ballester Marcos

2010-08-01

Full Text Available Abstract Background Lymphadenectomy is debated in early stages endometrial cancer. Moreover, a new FIGO classification of endometrial cancer, merging stages IA and IB has been recently published. Therefore, the aims of the present study was to evaluate the relevance of the sentinel node (SN procedure in women with endometrial cancer and to discuss whether the use of the 2009 FIGO classification could modify the indications for SN procedure. Methods Eighty-five patients with endometrial cancer underwent the SN procedure followed by pelvic lymphadenectomy. SNs were detected with a dual or single labelling method in 74 and 11 cases, respectively. All SNs were analysed by both H&E staining and immunohistochemistry. Presumed stage before surgery was assessed for all patients based on MR imaging features using the 1988 FIGO classification and the 2009 FIGO classification. Results An SN was detected in 88.2% of cases (75/85 women. Among the fourteen patients with lymph node metastases one-half were detected by serial sectioning and immunohistochemical analysis. There were no false negative case. Using the 1988 FIGO classification and the 2009 FIGO classification, the correlation between preoperative MRI staging and final histology was moderate with Kappa = 0.24 and Kappa = 0.45, respectively. None of the patients with grade 1 endometrioid carcinoma on biopsy and IA 2009 FIGO stage on MR imaging exhibited positive SN. In patients with grade 2-3 endometrioid carcinoma and stage IA on MR imaging, the rate of positive SN reached 16.6% with an incidence of micrometastases of 50%. Conclusions The present study suggests that sentinel node biopsy is an adequate technique to evaluate lymph node status. The use of the 2009 FIGO classification increases the accuracy of MR imaging to stage patients with early stages of endometrial cancer and contributes to clarify the indication of SN biopsy according to tumour grade and histological type.

Does the use of the 2009 FIGO classification of endometrial cancer impact on indications of the sentinel node biopsy?

International Nuclear Information System (INIS)

Ballester, Marcos; Koskas, Martin; Coutant, Charles; Chéreau, Elisabeth; Seror, Jeremy; Rouzier, Roman; Daraï, Emile

2010-01-01

Lymphadenectomy is debated in early stages endometrial cancer. Moreover, a new FIGO classification of endometrial cancer, merging stages IA and IB has been recently published. Therefore, the aims of the present study was to evaluate the relevance of the sentinel node (SN) procedure in women with endometrial cancer and to discuss whether the use of the 2009 FIGO classification could modify the indications for SN procedure. Eighty-five patients with endometrial cancer underwent the SN procedure followed by pelvic lymphadenectomy. SNs were detected with a dual or single labelling method in 74 and 11 cases, respectively. All SNs were analysed by both H&E staining and immunohistochemistry. Presumed stage before surgery was assessed for all patients based on MR imaging features using the 1988 FIGO classification and the 2009 FIGO classification. An SN was detected in 88.2% of cases (75/85 women). Among the fourteen patients with lymph node metastases one-half were detected by serial sectioning and immunohistochemical analysis. There were no false negative case. Using the 1988 FIGO classification and the 2009 FIGO classification, the correlation between preoperative MRI staging and final histology was moderate with Kappa = 0.24 and Kappa = 0.45, respectively. None of the patients with grade 1 endometrioid carcinoma on biopsy and IA 2009 FIGO stage on MR imaging exhibited positive SN. In patients with grade 2-3 endometrioid carcinoma and stage IA on MR imaging, the rate of positive SN reached 16.6% with an incidence of micrometastases of 50%. The present study suggests that sentinel node biopsy is an adequate technique to evaluate lymph node status. The use of the 2009 FIGO classification increases the accuracy of MR imaging to stage patients with early stages of endometrial cancer and contributes to clarify the indication of SN biopsy according to tumour grade and histological type

An NRG Oncology/GOG study of molecular classification for risk prediction in endometrioid endometrial cancer.

Science.gov (United States)

Cosgrove, Casey M; Tritchler, David L; Cohn, David E; Mutch, David G; Rush, Craig M; Lankes, Heather A; Creasman, William T; Miller, David S; Ramirez, Nilsa C; Geller, Melissa A; Powell, Matthew A; Backes, Floor J; Landrum, Lisa M; Timmers, Cynthia; Suarez, Adrian A; Zaino, Richard J; Pearl, Michael L; DiSilvestro, Paul A; Lele, Shashikant B; Goodfellow, Paul J

2018-01-01

The purpose of this study was to assess the prognostic significance of a simplified, clinically accessible classification system for endometrioid endometrial cancers combining Lynch syndrome screening and molecular risk stratification. Tumors from NRG/GOG GOG210 were evaluated for mismatch repair defects (MSI, MMR IHC, and MLH1 methylation), POLE mutations, and loss of heterozygosity. TP53 was evaluated in a subset of cases. Tumors were assigned to four molecular classes. Relationships between molecular classes and clinicopathologic variables were assessed using contingency tests and Cox proportional methods. Molecular classification was successful for 982 tumors. Based on the NCI consensus MSI panel assessing MSI and loss of heterozygosity combined with POLE testing, 49% of tumors were classified copy number stable (CNS), 39% MMR deficient, 8% copy number altered (CNA) and 4% POLE mutant. Cancer-specific mortality occurred in 5% of patients with CNS tumors; 2.6% with POLE tumors; 7.6% with MMR deficient tumors and 19% with CNA tumors. The CNA group had worse progression-free (HR 2.31, 95%CI 1.53-3.49) and cancer-specific survival (HR 3.95; 95%CI 2.10-7.44). The POLE group had improved outcomes, but the differences were not statistically significant. CNA class remained significant for cancer-specific survival (HR 2.11; 95%CI 1.04-4.26) in multivariable analysis. The CNA molecular class was associated with TP53 mutation and expression status. A simple molecular classification for endometrioid endometrial cancers that can be easily combined with Lynch syndrome screening provides important prognostic information. These findings support prospective clinical validation and further studies on the predictive value of a simplified molecular classification system. Copyright © 2017 Elsevier Inc. All rights reserved.

Thermographic image analysis for classification of ACL rupture disease, bone cancer, and feline hyperthyroid, with Gabor filters

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Alvandipour, Mehrdad; Umbaugh, Scott E.; Mishra, Deependra K.; Dahal, Rohini; Lama, Norsang; Marino, Dominic J.; Sackman, Joseph

2017-05-01

Thermography and pattern classification techniques are used to classify three different pathologies in veterinary images. Thermographic images of both normal and diseased animals were provided by the Long Island Veterinary Specialists (LIVS). The three pathologies are ACL rupture disease, bone cancer, and feline hyperthyroid. The diagnosis of these diseases usually involves radiology and laboratory tests while the method that we propose uses thermographic images and image analysis techniques and is intended for use as a prescreening tool. Images in each category of pathologies are first filtered by Gabor filters and then various features are extracted and used for classification into normal and abnormal classes. Gabor filters are linear filters that can be characterized by the two parameters wavelength λ and orientation θ. With two different wavelength and five different orientations, a total of ten different filters were studied. Different combinations of camera views, filters, feature vectors, normalization methods, and classification methods, produce different tests that were examined and the sensitivity, specificity and success rate for each test were produced. Using the Gabor features alone, sensitivity, specificity, and overall success rates of 85% for each of the pathologies was achieved.

CDX2 prognostic value in stage II/III resected colon cancer is related to CMS classification.

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Pilati, C; Taieb, J; Balogoun, R; Marisa, L; de Reyniès, A; Laurent-Puig, P

2017-05-01

Caudal-type homeobox transcription factor 2 (CDX2) is involved in colon cancer (CC) oncogenesis and has been proposed as a prognostic biomarker in patients with stage II or III CC. We analyzed CDX2 expression in a series of 469 CC typed for the new international consensus molecular subtype (CMS) classification, and we confirmed results in a series of 90 CC. Here, we show that lack of CDX2 expression is only present in the mesenchymal subgroup (CMS4) and in MSI-immune tumors (CMS1) and not in CMS2 and CMS3 colon cancer. Although CDX2 expression was a globally independent prognostic factor, loss of CDX2 expression is not associated with a worse prognosis in the CMS1 group, but is highly prognostic in CMS4 patients for both relapse free and overall survival. Similarly, lack of CDX2 expression was a bad prognostic factor in MSS patients, but not in MSI. Our work suggests that combination of the consensual CMS classification and lack of CDX2 expression could be a useful marker to identify CMS4/CDX2-negative patients with a very poor prognosis. © The Author 2017. Published by Oxford University Press on behalf of the European Society for Medical Oncology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Deep convolutional neural networks for automatic classification of gastric carcinoma using whole slide images in digital histopathology.

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Sharma, Harshita; Zerbe, Norman; Klempert, Iris; Hellwich, Olaf; Hufnagl, Peter

2017-11-01

Deep learning using convolutional neural networks is an actively emerging field in histological image analysis. This study explores deep learning methods for computer-aided classification in H&E stained histopathological whole slide images of gastric carcinoma. An introductory convolutional neural network architecture is proposed for two computerized applications, namely, cancer classification based on immunohistochemical response and necrosis detection based on the existence of tumor necrosis in the tissue. Classification performance of the developed deep learning approach is quantitatively compared with traditional image analysis methods in digital histopathology requiring prior computation of handcrafted features, such as statistical measures using gray level co-occurrence matrix, Gabor filter-bank responses, LBP histograms, gray histograms, HSV histograms and RGB histograms, followed by random forest machine learning. Additionally, the widely known AlexNet deep convolutional framework is comparatively analyzed for the corresponding classification problems. The proposed convolutional neural network architecture reports favorable results, with an overall classification accuracy of 0.6990 for cancer classification and 0.8144 for necrosis detection. Copyright © 2017 Elsevier Ltd. All rights reserved.

In vivo subsite classification and diagnosis of oral cancers using Raman spectroscopy

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Aditi Sahu

2016-09-01

Full Text Available Oral cancers suffer from poor disease-free survival rates due to delayed diagnosis. Noninvasive, rapid, objective approaches as adjuncts to visual inspection can help in better management of oral cancers. Raman spectroscopy (RS has shown potential in identification of oral premalignant and malignant conditions and also in the detection of early cancer changes like cancer-field-effects (CFE at buccal mucosa subsite. Anatomic differences between different oral subsites have also been reported using RS. In this study, anatomical differences between subsites and their possible influence on healthy vs pathological classification were evaluated on 85 oral cancer and 72 healthy subjects. Spectra were acquired from buccal mucosa, lip and tongue in healthy, contralateral (internal healthy control, premalignant and cancer conditions using fiber-optic Raman spectrometer. Mean spectra indicate predominance of lipids in healthy buccal mucosa, contribution of both lipids and proteins in lip while major dominance of protein in tongue spectra. From healthy to tumor, changes in protein secondary-structure, DNA and heme-related features were observed. Principal component linear discriminant analysis (PC-LDA followed by leave-one-out-cross-validation (LOOCV was used for data analysis. Findings indicate buccal mucosa and tongue are distinct entities, while lip misclassifies with both these subsites. Additionally, the diagnostic algorithm for individual subsites gave improved classification efficiencies with respect to the pooled subsites model. However, as the pooled subsites model yielded 98% specificity and 100% sensitivity, this model may be more useful for preliminary screening applications. Large-scale validation studies are a pre-requisite before envisaging future clinical applications.

A comprehensive sensitivity analysis of microarray breast cancer classification under feature variability

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Reinders Marcel JT

2009-11-01

Full Text Available Abstract Background Large discrepancies in signature composition and outcome concordance have been observed between different microarray breast cancer expression profiling studies. This is often ascribed to differences in array platform as well as biological variability. We conjecture that other reasons for the observed discrepancies are the measurement error associated with each feature and the choice of preprocessing method. Microarray data are known to be subject to technical variation and the confidence intervals around individual point estimates of expression levels can be wide. Furthermore, the estimated expression values also vary depending on the selected preprocessing scheme. In microarray breast cancer classification studies, however, these two forms of feature variability are almost always ignored and hence their exact role is unclear. Results We have performed a comprehensive sensitivity analysis of microarray breast cancer classification under the two types of feature variability mentioned above. We used data from six state of the art preprocessing methods, using a compendium consisting of eight diferent datasets, involving 1131 hybridizations, containing data from both one and two-color array technology. For a wide range of classifiers, we performed a joint study on performance, concordance and stability. In the stability analysis we explicitly tested classifiers for their noise tolerance by using perturbed expression profiles that are based on uncertainty information directly related to the preprocessing methods. Our results indicate that signature composition is strongly influenced by feature variability, even if the array platform and the stratification of patient samples are identical. In addition, we show that there is often a high level of discordance between individual class assignments for signatures constructed on data coming from different preprocessing schemes, even if the actual signature composition is identical

Automatic classification of ovarian cancer types from cytological images using deep convolutional neural networks.

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Wu, Miao; Yan, Chuanbo; Liu, Huiqiang; Liu, Qian

2018-06-29

Ovarian cancer is one of the most common gynecologic malignancies. Accurate classification of ovarian cancer types (serous carcinoma, mucous carcinoma, endometrioid carcinoma, transparent cell carcinoma) is an essential part in the different diagnosis. Computer-aided diagnosis (CADx) can provide useful advice for pathologists to determine the diagnosis correctly. In our study, we employed a Deep Convolutional Neural Networks (DCNN) based on AlexNet to automatically classify the different types of ovarian cancers from cytological images. The DCNN consists of five convolutional layers, three max pooling layers, and two full reconnect layers. Then we trained the model by two group input data separately, one was original image data and the other one was augmented image data including image enhancement and image rotation. The testing results are obtained by the method of 10-fold cross-validation, showing that the accuracy of classification models has been improved from 72.76 to 78.20% by using augmented images as training data. The developed scheme was useful for classifying ovarian cancers from cytological images. © 2018 The Author(s).

hemaClass.org: Online One-By-One Microarray Normalization and Classification of Hematological Cancers for Precision Medicine.

Science.gov (United States)

Falgreen, Steffen; Ellern Bilgrau, Anders; Brøndum, Rasmus Froberg; Hjort Jakobsen, Lasse; Have, Jonas; Lindblad Nielsen, Kasper; El-Galaly, Tarec Christoffer; Bødker, Julie Støve; Schmitz, Alexander; H Young, Ken; Johnsen, Hans Erik; Dybkær, Karen; Bøgsted, Martin

2016-01-01

Dozens of omics based cancer classification systems have been introduced with prognostic, diagnostic, and predictive capabilities. However, they often employ complex algorithms and are only applicable on whole cohorts of patients, making them difficult to apply in a personalized clinical setting. This prompted us to create hemaClass.org, an online web application providing an easy interface to one-by-one RMA normalization of microarrays and subsequent risk classifications of diffuse large B-cell lymphoma (DLBCL) into cell-of-origin and chemotherapeutic sensitivity classes. Classification results for one-by-one array pre-processing with and without a laboratory specific RMA reference dataset were compared to cohort based classifiers in 4 publicly available datasets. Classifications showed high agreement between one-by-one and whole cohort pre-processsed data when a laboratory specific reference set was supplied. The website is essentially the R-package hemaClass accompanied by a Shiny web application. The well-documented package can be used to run the website locally or to use the developed methods programmatically. The website and R-package is relevant for biological and clinical lymphoma researchers using affymetrix U-133 Plus 2 arrays, as it provides reliable and swift methods for calculation of disease subclasses. The proposed one-by-one pre-processing method is relevant for all researchers using microarrays.

Quantum Cascade Laser-Based Infrared Microscopy for Label-Free and Automated Cancer Classification in Tissue Sections.

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Kuepper, Claus; Kallenbach-Thieltges, Angela; Juette, Hendrik; Tannapfel, Andrea; Großerueschkamp, Frederik; Gerwert, Klaus

2018-05-16

A feasibility study using a quantum cascade laser-based infrared microscope for the rapid and label-free classification of colorectal cancer tissues is presented. Infrared imaging is a reliable, robust, automated, and operator-independent tissue classification method that has been used for differential classification of tissue thin sections identifying tumorous regions. However, long acquisition time by the so far used FT-IR-based microscopes hampered the clinical translation of this technique. Here, the used quantum cascade laser-based microscope provides now infrared images for precise tissue classification within few minutes. We analyzed 110 patients with UICC-Stage II and III colorectal cancer, showing 96% sensitivity and 100% specificity of this label-free method as compared to histopathology, the gold standard in routine clinical diagnostics. The main hurdle for the clinical translation of IR-Imaging is overcome now by the short acquisition time for high quality diagnostic images, which is in the same time range as frozen sections by pathologists.

Comparison and Efficacy of LigaSure and Rubber Band Ligature in Closing the Inflamed Cecal Stump in a Rat Model of Acute Appendicitis

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Chun-Chieh Yeh

2015-01-01

Full Text Available Safety of either LigaSure or rubber band in closing inflamed appendiceal stump in acute appendicitis has been less investigated. In this study, cecal ligation followed by resecting inflamed cecum was performed to mimic appendectomy in a rat model of acute appendicitis. Rats were sacrificed immediately (Group A and 7 days (Group B after cecal resection, respectively. The cecal stumps were closed by silk ligature (S, 5 mm LigaSure (L, or rubber band (R. Seven days after cecal resection, the LigaSure (BL and silk subgroups (BS had significantly less intra-abdominal adhesion and better laparotomy wound healing than rubber band subgroup (BR. The initial bursting pressure at cecal stump was comparable among the three methods; along with tissue healing process, both BL and BS provided a higher bursting pressure than BR 7 days after appendectomy. BL subgroup had more abundant hydroxyproline deposition than BS and BR subgroup. Furthermore, serum TNF-α in BR group kept persistently increasing along with time after cecal resection. Thus, the finding that LigaSure but not rubber band is safe in sealing off the inflamed cecal stump in rat model of acute appendicitis suggests the possibility of applying LigaSure for appendectomy via single port procedure or natural orifice transluminal endoscopic surgery (NOTES.

Characterization of sulfur deposition over the period of industrialization in Japan using sulfur isotope ratio in Japanese cedar tree rings taken from stumps.

Science.gov (United States)

Ishida, Takuya; Tayasu, Ichiro; Takenaka, Chisato

2015-07-01

We characterized the sulfur deposition history over the period of industrialization in Japan based on the sulfur isotope ratio (δ(34)S) in tree rings of Japanese cedar (Cryptomeria japonica D. Don) stumps. We analyzed and compared δ(34)S values in the rings from two types of disk samples from 170-year-old stumps that had been cut 5 years earlier (older forest stand) and from 40-year-old living trees (younger forest stand) in order to confirm the validity of using stump disks for δ(34)S analysis. No differences in δ(34)S values by age were found between the sample types, indicating that stump disks can be used for δ(34)S analysis. The δ(34)S profile in tree rings was significantly correlated with anthropogenic SO2 emissions in Japan (r = -0.76, p tree rings serve as a record of anthropogenic sulfur emissions. In addition, the values did not change largely from pre-industrialization to the 1940s (+4.2 to +6.1‰). The values before the 1940s are expected to reflect the background sulfur conditions in Japan and, thus, disks containing rings formed before the 1940s contain information about the natural environmental sulfur, which is useful for biogeochemical studies.

Effects of covering highland banana stumps with soil on banana weevil Cosmopolites sordidus (Coleoptera: Curculionidae) oviposition

NARCIS (Netherlands)

Masanza, M.; Gold, C.S.; Huis, van A.; Ragama, P.E.

2005-01-01

The effect of covering post-harvest banana stumps with soil on banana weevil Cosmopolites sordidus (Germar) oviposition levels was investigated at three locations, Sendusu, Kawanda Agricultural Research Institute (KARI) and Ntungamo district of southwestern Uganda. In the first experiment

The classification of lung cancers and their degree of malignancy by FTIR, PCA-LDA analysis, and a physics-based computational model.

Science.gov (United States)

Kaznowska, E; Depciuch, J; Łach, K; Kołodziej, M; Koziorowska, A; Vongsvivut, J; Zawlik, I; Cholewa, M; Cebulski, J

2018-08-15

Lung cancer has the highest mortality rate of all malignant tumours. The current effects of cancer treatment, as well as its diagnostics, are unsatisfactory. Therefore it is very important to introduce modern diagnostic tools, which will allow for rapid classification of lung cancers and their degree of malignancy. For this purpose, the authors propose the use of Fourier Transform InfraRed (FTIR) spectroscopy combined with Principal Component Analysis-Linear Discriminant Analysis (PCA-LDA) and a physics-based computational model. The results obtained for lung cancer tissues, adenocarcinoma and squamous cell carcinoma FTIR spectra, show a shift in wavenumbers compared to control tissue FTIR spectra. Furthermore, in the FTIR spectra of adenocarcinoma there are no peaks corresponding to glutamate or phospholipid functional groups. Moreover, in the case of G2 and G3 malignancy of adenocarcinoma lung cancer, the absence of an OH groups peak was noticed. Thus, it seems that FTIR spectroscopy is a valuable tool to classify lung cancer and to determine the degree of its malignancy. Copyright © 2018 Elsevier B.V. All rights reserved.

K-ras mutations in gastric stump carcinomas and in carcinomas from the non-operated stomach

NARCIS (Netherlands)

van Rees, B. P.; Musler, A.; Caspers, E.; Drillenburg, P.; Craanen, M. E.; Polkowski, W.; Chibowski, D.; Offerhaus, G. J.

1999-01-01

Partial gastrectomy is a well-established pre-malignant condition. It is postulated that in the gastric stump an accelerated neoplastic process takes place, similar to that of (intestinal type) adenocarcinoma from the non-operated stomach. K-ras codon 12 mutation is one of the most frequent

Multiclass classification for skin cancer profiling based on the integration of heterogeneous gene expression series.

Science.gov (United States)

Gálvez, Juan Manuel; Castillo, Daniel; Herrera, Luis Javier; San Román, Belén; Valenzuela, Olga; Ortuño, Francisco Manuel; Rojas, Ignacio

2018-01-01

)-based classification including feature ranking was performed. The accuracy attained exceeded the 92% in overall recognition of the 7 different cancer-related skin states. The proposed integration scheme is expected to allow the co-integration with other state-of-the-art technologies such as RNA-seq.

Dysfunctional breathing: a review of the literature and proposal for classification

Directory of Open Access Journals (Sweden)

Richard Boulding

2016-09-01

Full Text Available Dysfunctional breathing is a term describing breathing disorders where chronic changes in breathing pattern result in dyspnoea and other symptoms in the absence or in excess of the magnitude of physiological respiratory or cardiac disease. We reviewed the literature and propose a classification system for the common dysfunctional breathing patterns described. The literature was searched using the terms: dysfunctional breathing, hyperventilation, Nijmegen questionnaire and thoraco-abdominal asynchrony. We have summarised the presentation, assessment and treatment of dysfunctional breathing, and propose that the following system be used for classification. 1 Hyperventilation syndrome: associated with symptoms both related to respiratory alkalosis and independent of hypocapnia. 2 Periodic deep sighing: frequent sighing with an irregular breathing pattern. 3 Thoracic dominant breathing: can often manifest in somatic disease, if occurring without disease it may be considered dysfunctional and results in dyspnoea. 4 Forced abdominal expiration: these patients utilise inappropriate and excessive abdominal muscle contraction to aid expiration. 5 Thoraco-abdominal asynchrony: where there is delay between rib cage and abdominal contraction resulting in ineffective breathing mechanics. This review highlights the common abnormalities, current diagnostic methods and therapeutic implications in dysfunctional breathing. Future work should aim to further investigate the prevalence, clinical associations and treatment of these presentations.

Side effects of cancer therapies. International classification and documentation systems

International Nuclear Information System (INIS)

Seegenschmiedt, M.H.

1998-01-01

The publication presents and explains verified, international classification and documentation systems for side effects induced by cancer treatments, applicable in general and clinical practice and clinical research, and covers in a clearly arranged manner the whole range of treatments, including acute and chronic side effects of chemotherapy and radiotherapy, surgery, or combined therapies. The book fills a long-felt need in tumor documentation and is a major contribution to quality assurance in clinical oncology in German-speaking countries. As most parts of the book are bilingual, presenting German and English texts and terminology, it satisfies the principles of interdisciplinarity and internationality. The tabulated form chosen for presentation of classification systems and criteria facilitate the user's approach as well as application in daily work. (orig./CB) [de

Median Filter Noise Reduction of Image and Backpropagation Neural Network Model for Cervical Cancer Classification

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Wutsqa, D. U.; Marwah, M.

2017-06-01

In this paper, we consider spatial operation median filter to reduce the noise in the cervical images yielded by colposcopy tool. The backpropagation neural network (BPNN) model is applied to the colposcopy images to classify cervical cancer. The classification process requires an image extraction by using a gray level co-occurrence matrix (GLCM) method to obtain image features that are used as inputs of BPNN model. The advantage of noise reduction is evaluated by comparing the performances of BPNN models with and without spatial operation median filter. The experimental result shows that the spatial operation median filter can improve the accuracy of the BPNN model for cervical cancer classification.

Vessel-guided airway segmentation based on voxel classification

DEFF Research Database (Denmark)

Lo, Pechin Chien Pau; Sporring, Jon; Ashraf, Haseem

2008-01-01

This paper presents a method for improving airway tree segmentation using vessel orientation information. We use the fact that an airway branch is always accompanied by an artery, with both structures having similar orientations. This work is based on a  voxel classification airway segmentation...... method proposed previously. The probability of a voxel belonging to the airway, from the voxel classification method, is augmented with an orientation similarity measure as a criterion for region growing. The orientation similarity measure of a voxel indicates how similar is the orientation...... of the surroundings of a voxel, estimated based on a tube model, is to that of a neighboring vessel. The proposed method is tested on 20 CT images from different subjects selected randomly from a lung cancer screening study. Length of the airway branches from the results of the proposed method are significantly...

Visualization and tissue classification of human breast cancer images using ultrahigh-resolution OCT (Conference Presentation)

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Yao, Xinwen; Gan, Yu; Chang, Ernest W.; Hibshoosh, Hanina; Feldman, Sheldon; Hendon, Christine P.

2017-02-01

We employed a home-built ultrahigh resolution (UHR) OCT system at 800nm to image human breast cancer sample ex vivo. The system has an axial resolution of 2.72µm and a lateral resolution of 5.52µm with an extended imaging range of 1.78mm. Over 900 UHR OCT volumes were generated on specimens from 23 breast cancer cases. With better spatial resolution, detailed structures in the breast tissue were better defined. Different types of breast cancer as well as healthy breast tissue can be well delineated from the UHR OCT images. To quantitatively evaluate the advantages of UHR OCT imaging of breast cancer, features derived from OCT intensity images were used as inputs to a machine learning model, the relevance vector machine. A trained machine learning model was employed to evaluate the performance of tissue classification based on UHR OCT images for differentiating tissue types in the breast samples, including adipose tissue, healthy stroma and cancerous region. For adipose tissue, grid-based local features were extracted from OCT intensity data, including standard deviation, entropy, and homogeneity. We showed that it was possible to enhance the classification performance on distinguishing fat tissue from non-fat tissue by using the UHR images when compared with the results based on OCT images from a commercial 1300 nm OCT system. For invasive ductal carcinoma (IDC) and normal stroma differentiation, the classification was based on frame-based features that portray signal penetration depth and tissue reflectivity. The confusing matrix indicated a sensitivity of 97.5% and a sensitivity of 77.8%.

Bronchial stump closure with amniotic membrane in animal model

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Gholamreza Mohajeri

2014-01-01

Full Text Available Background: Coverage of the bronchial stumps (BSs with adjacent tissues can improve healing and reduce bronchial complications in complex thoracic surgery. There is no evidence for the application of human amnion allograft for prevention of air leak from the BS. The comparison of the amniotic membrane (AM and pleural patch for BS healing after lobectomy in dogs was our aim in this study. Materials and Methods: A total of eight males and females 12-24-month-old dogs between 17 and 22 kg body-weight were used in this study in 2010, Isfahan University of Medical Sciences. Animals were separated into two groups: group A (n = 4; amniotic membrane and group P (n = 4; pleural patch according to the BS closure technique performed. After lobectomy of the right middle lobe, the BS was closed, while a small bronchopleural fistula (BPF was created by inserting a catheter via edges of closed stump. Then, it was covered with a piece of AM3 × 3 cm in group A and with a pedicle graft of pleura in group P. Rethoracotomy was performed after 15 days of observation, and the BS was removed for histological examination. Histological healing was classified as complete or incomplete healing. Neoangiogenesis was measured by Von Willebrand expression using immunohistochemistry (IHC. Data were analyzed by SPSS version 15 using Fisher′s exact test, Mann-Whitney test, and T tests. Results: BPF complications were not seen during observation period. There was no significant difference in histological healing between two groups. Similarly, no significant difference was observed between the groups in terms of neoangiogenesis based on IHC examination (P value = 0.69. Conclusion: Human amnion allograft could be as effective as pleural patch for BS wrapping following pulmonary resections.

Classification of breast cancer cytological specimen using convolutional neural network

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Żejmo, Michał; Kowal, Marek; Korbicz, Józef; Monczak, Roman

2017-01-01

The paper presents a deep learning approach for automatic classification of breast tumors based on fine needle cytology. The main aim of the system is to distinguish benign from malignant cases based on microscopic images. Experiment was carried out on cytological samples derived from 50 patients (25 benign cases + 25 malignant cases) diagnosed in Regional Hospital in Zielona Góra. To classify microscopic images, we used convolutional neural networks (CNN) of two types: GoogLeNet and AlexNet. Due to the very large size of images of cytological specimen (on average 200000 × 100000 pixels), they were divided into smaller patches of size 256 × 256 pixels. Breast cancer classification usually is based on morphometric features of nuclei. Therefore, training and validation patches were selected using Support Vector Machine (SVM) so that suitable amount of cell material was depicted. Neural classifiers were tuned using GPU accelerated implementation of gradient descent algorithm. Training error was defined as a cross-entropy classification loss. Classification accuracy was defined as the percentage ratio of successfully classified validation patches to the total number of validation patches. The best accuracy rate of 83% was obtained by GoogLeNet model. We observed that more misclassified patches belong to malignant cases.

Immunogenomic Classification of Colorectal Cancer and Therapeutic Implications

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Jessica Roelands

2017-10-01

Full Text Available The immune system has a substantial effect on colorectal cancer (CRC progression. Additionally, the response to immunotherapeutics and conventional treatment options (e.g., chemotherapy, radiotherapy and targeted therapies is influenced by the immune system. The molecular characterization of colorectal cancer (CRC has led to the identification of favorable and unfavorable immunological attributes linked to clinical outcome. With the definition of consensus molecular subtypes (CMSs based on transcriptomic profiles, multiple characteristics have been proposed to be responsible for the development of the tumor immune microenvironment and corresponding mechanisms of immune escape. In this review, a detailed description of proposed immune phenotypes as well as their interaction with different therapeutic modalities will be provided. Finally, possible strategies to shift the CRC immune phenotype towards a reactive, anti-tumor orientation are proposed per CMS.

Susceptibility to breast cancer Cuban families and intervention strategy proposal

International Nuclear Information System (INIS)

Robaina, Martha S.; Menendez, Ibis; Valdes, Zodilina; Diaz, Milania

2009-01-01

In breast cancer, as in most cancers, mutations usually occur in somatic cells, but sometimes occur in germ cells. The carriers of these mutations germ have up to 80% risk of having the disease course of their lives and pass it on to their offspring, they are called hereditary cancers. In this work studied 50 tested history relatives of this neoplasm from consulting advice genetic hereditary breast cancer. The tree was made pedigree of the family of each test and been classified risk using the criteria of Hampel et al. Other malignancies were identified through the analysis of pedigrees and performed syndromic classification of families. It develops an algorithm for the care of breast cancer families hereditary and plotted strategies identified by risk taking that each category implies a different intervention. It recommended to continue studying the value of marking lesions subclinical and train staff to perform this technique for its widespread use in the country. (Author)

Gene Expression Profiles for Predicting Metastasis in Breast Cancer: A Cross-Study Comparison of Classification Methods

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Mark Burton

2012-01-01

Full Text Available Machine learning has increasingly been used with microarray gene expression data and for the development of classifiers using a variety of methods. However, method comparisons in cross-study datasets are very scarce. This study compares the performance of seven classification methods and the effect of voting for predicting metastasis outcome in breast cancer patients, in three situations: within the same dataset or across datasets on similar or dissimilar microarray platforms. Combining classification results from seven classifiers into one voting decision performed significantly better during internal validation as well as external validation in similar microarray platforms than the underlying classification methods. When validating between different microarray platforms, random forest, another voting-based method, proved to be the best performing method. We conclude that voting based classifiers provided an advantage with respect to classifying metastasis outcome in breast cancer patients.

Efficacy of hidden markov model over support vector machine on multiclass classification of healthy and cancerous cervical tissues

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Mukhopadhyay, Sabyasachi; Kurmi, Indrajit; Pratiher, Sawon; Mukherjee, Sukanya; Barman, Ritwik; Ghosh, Nirmalya; Panigrahi, Prasanta K.

2018-02-01

In this paper, a comparative study between SVM and HMM has been carried out for multiclass classification of cervical healthy and cancerous tissues. In our study, the HMM methodology is more promising to produce higher accuracy in classification.

The Value of Ensari’s Proposal in Evaluating the Mucosal Pathology of Childhood Celiac Disease: Old Classification versus New Version

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Gülçin Güler Şimşek

2012-09-01

Full Text Available Objective: Small intestinal biopsy remains the gold standard in diagnosing celiac disease (CD; however, the wide spectrum of histopathological states and differential diagnosis of CD is still a diagnostic problem for pathologists. Recently, Ensari reviewed the literature and proposed an update of the histopathological diagnosis and classification for CD. Materials and Methods: In this study, the histopathological materials of 54 children in whom CD was diagnosed at our hospital were reviewed to compare the previous Marsh and Modified Marsh-Oberhuber classifications with this new proposal. Results: In this study, we show that the Ensari classification is as accurate as the Marsh and Modified Marsh classifications in describing the consecutive states of mucosal damage seen in CD.Conclusions: Ensari’s classification is simple, practical and facilitative in diagnosing and subtyping of mucosal pathology of CD.

Setting a generalized functional linear model (GFLM for the classification of different types of cancer

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Miguel Flores

2016-11-01

Full Text Available This work aims to classify the DNA sequences of healthy and malignant cancer respectively. For this, supervised and unsupervised classification methods from a functional context are used; i.e. each strand of DNA is an observation. The observations are discretized, for that reason different ways to represent these observations with functions are evaluated. In addition, an exploratory study is done: estimating the mean and variance of each functional type of cancer. For the unsupervised classification method, hierarchical clustering with different measures of functional distance is used. On the other hand, for the supervised classification method, a functional generalized linear model is used. For this model the first and second derivatives are used which are included as discriminating variables. It has been verified that one of the advantages of working in the functional context is to obtain a model to correctly classify cancers by 100%. For the implementation of the methods it has been used the fda.usc R package that includes all the techniques of functional data analysis used in this work. In addition, some that have been developed in recent decades. For more details of these techniques can be consulted Ramsay, J. O. and Silverman (2005 and Ferraty et al. (2006.

Classification between normal and tumor tissues based on the pair-wise gene expression ratio

International Nuclear Information System (INIS)

Yap, YeeLeng; Zhang, XueWu; Ling, MT; Wang, XiangHong; Wong, YC; Danchin, Antoine

2004-01-01

Precise classification of cancer types is critically important for early cancer diagnosis and treatment. Numerous efforts have been made to use gene expression profiles to improve precision of tumor classification. However, reliable cancer-related signals are generally lacking. Using recent datasets on colon and prostate cancer, a data transformation procedure from single gene expression to pair-wise gene expression ratio is proposed. Making use of the internal consistency of each expression profiling dataset this transformation improves the signal to noise ratio of the dataset and uncovers new relevant cancer-related signals (features). The efficiency in using the transformed dataset to perform normal/tumor classification was investigated using feature partitioning with informative features (gene annotation) as discriminating axes (single gene expression or pair-wise gene expression ratio). Classification results were compared to the original datasets for up to 10-feature model classifiers. 82 and 262 genes that have high correlation to tissue phenotype were selected from the colon and prostate datasets respectively. Remarkably, data transformation of the highly noisy expression data successfully led to lower the coefficient of variation (CV) for the within-class samples as well as improved the correlation with tissue phenotypes. The transformed dataset exhibited lower CV when compared to that of single gene expression. In the colon cancer set, the minimum CV decreased from 45.3% to 16.5%. In prostate cancer, comparable CV was achieved with and without transformation. This improvement in CV, coupled with the improved correlation between the pair-wise gene expression ratio and tissue phenotypes, yielded higher classification efficiency, especially with the colon dataset – from 87.1% to 93.5%. Over 90% of the top ten discriminating axes in both datasets showed significant improvement after data transformation. The high classification efficiency achieved suggested

Secure hemostasis in transhiatal esophagectomy for esophageal cancer with gauze packing

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Hirahara Noriyuki

2012-12-01

Full Text Available Abstract Background Transhiatal esophagectomy for esophageal cancer implies blind manipulation of the intrathoracic esophagus. We report a secure hemostatic method with gauze packing in transhiatal esophagectomy. Methods The gauze-packing technique is utilized for hemostasis just after removal of the thoracic esophagus during transhiatal esophagectomy. After confirming cancer-free margins, the abdominal esophagus and cervical esophagus are transected. A vein stripper is inserted into the oral-side stump of the esophagus and led to exit from the abdominal-side stump of the esophagus. The vein stripper and the oral stump of the esophagus are affixed by silk thread. A polyester tape is then affixed to the vein stripper, as the polyester tape is left in the posterior mediastinum after removal of the esophagus toward the abdominal side. The polyester tape on the cervical side is ligated with gauze and the polyester tape is removed toward the abdominal side. The oral stump of gauze and new additional gauze are affixed. As the first gauze is pulled out from the abdominal side, the second gauze gets drawn from the cervical wound into the mediastinum. The posterior mediastinum is finally packed with gauze and possible bleeding at this site undergoes a complete astriction. The status of hemostasis with the gauze packing is checked by an observation of color and bloodstain on the gauze. Results Between January 2005 and February 2012, 13 consecutive patients with esophageal cancer underwent a transhiatal esophagectomy with the gauze-packing hemostatic technique. Hemostasis at the posterior mediastinum was performed successfully and quickly in all cases with this method, requiring up to four pieces of gauze for a complete hemostasis. Median required time for hemostasis was 1219 (range 1896 to 1293 seconds and estimated blood loss was 20.4 (range 15 to 25 ml during gauze packing. Conclusions Our technique could minimize bleeding after the removal of the

An Entropy-based gene selection method for cancer classification using microarray data

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Krishnan Arun

2005-03-01

Full Text Available Abstract Background Accurate diagnosis of cancer subtypes remains a challenging problem. Building classifiers based on gene expression data is a promising approach; yet the selection of non-redundant but relevant genes is difficult. The selected gene set should be small enough to allow diagnosis even in regular clinical laboratories and ideally identify genes involved in cancer-specific regulatory pathways. Here an entropy-based method is proposed that selects genes related to the different cancer classes while at the same time reducing the redundancy among the genes. Results The present study identifies a subset of features by maximizing the relevance and minimizing the redundancy of the selected genes. A merit called normalized mutual information is employed to measure the relevance and the redundancy of the genes. In order to find a more representative subset of features, an iterative procedure is adopted that incorporates an initial clustering followed by data partitioning and the application of the algorithm to each of the partitions. A leave-one-out approach then selects the most commonly selected genes across all the different runs and the gene selection algorithm is applied again to pare down the list of selected genes until a minimal subset is obtained that gives a satisfactory accuracy of classification. The algorithm was applied to three different data sets and the results obtained were compared to work done by others using the same data sets Conclusion This study presents an entropy-based iterative algorithm for selecting genes from microarray data that are able to classify various cancer sub-types with high accuracy. In addition, the feature set obtained is very compact, that is, the redundancy between genes is reduced to a large extent. This implies that classifiers can be built with a smaller subset of genes.

Classification of Dukes' B and C colorectal cancers using expression arrays

DEFF Research Database (Denmark)

Frederiksen, C.M.; Knudsen, Steen; Laurberg, S.

2003-01-01

Purpose. Colorectal cancer is one of the most common malignancies. Substaging of the cancer is of importance not only to prognosis but also to treatment. Classification of substages based on DNA microarray technology is currently the most promising approach. We therefore investigated if gene...... expression microarrays could be used to classify colorectal tumors. Methods. We used the Affymetrix oligonucleotide arrays to analyze the expression of more than 5,000 genes in samples from the sigmoid and upper rectum of the left colon. Five samples were from normal mucosa and five samples from each...... expression of one of the most common malignancies, colorectal cancer, now seems to be within reach. The data indicates that it is possible at least to classify Dukes' B and C colorectal tumors with microarrays....

An Efficient Ensemble Learning Method for Gene Microarray Classification

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Alireza Osareh

2013-01-01

Full Text Available The gene microarray analysis and classification have demonstrated an effective way for the effective diagnosis of diseases and cancers. However, it has been also revealed that the basic classification techniques have intrinsic drawbacks in achieving accurate gene classification and cancer diagnosis. On the other hand, classifier ensembles have received increasing attention in various applications. Here, we address the gene classification issue using RotBoost ensemble methodology. This method is a combination of Rotation Forest and AdaBoost techniques which in turn preserve both desirable features of an ensemble architecture, that is, accuracy and diversity. To select a concise subset of informative genes, 5 different feature selection algorithms are considered. To assess the efficiency of the RotBoost, other nonensemble/ensemble techniques including Decision Trees, Support Vector Machines, Rotation Forest, AdaBoost, and Bagging are also deployed. Experimental results have revealed that the combination of the fast correlation-based feature selection method with ICA-based RotBoost ensemble is highly effective for gene classification. In fact, the proposed method can create ensemble classifiers which outperform not only the classifiers produced by the conventional machine learning but also the classifiers generated by two widely used conventional ensemble learning methods, that is, Bagging and AdaBoost.

Sparse Representation Based Multi-Instance Learning for Breast Ultrasound Image Classification

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Lu Bing

2017-01-01

Full Text Available We propose a novel method based on sparse representation for breast ultrasound image classification under the framework of multi-instance learning (MIL. After image enhancement and segmentation, concentric circle is used to extract the global and local features for improving the accuracy in diagnosis and prediction. The classification problem of ultrasound image is converted to sparse representation based MIL problem. Each instance of a bag is represented as a sparse linear combination of all basis vectors in the dictionary, and then the bag is represented by one feature vector which is obtained via sparse representations of all instances within the bag. The sparse and MIL problem is further converted to a conventional learning problem that is solved by relevance vector machine (RVM. Results of single classifiers are combined to be used for classification. Experimental results on the breast cancer datasets demonstrate the superiority of the proposed method in terms of classification accuracy as compared with state-of-the-art MIL methods.

Sparse Representation Based Multi-Instance Learning for Breast Ultrasound Image Classification.

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Bing, Lu; Wang, Wei

2017-01-01

We propose a novel method based on sparse representation for breast ultrasound image classification under the framework of multi-instance learning (MIL). After image enhancement and segmentation, concentric circle is used to extract the global and local features for improving the accuracy in diagnosis and prediction. The classification problem of ultrasound image is converted to sparse representation based MIL problem. Each instance of a bag is represented as a sparse linear combination of all basis vectors in the dictionary, and then the bag is represented by one feature vector which is obtained via sparse representations of all instances within the bag. The sparse and MIL problem is further converted to a conventional learning problem that is solved by relevance vector machine (RVM). Results of single classifiers are combined to be used for classification. Experimental results on the breast cancer datasets demonstrate the superiority of the proposed method in terms of classification accuracy as compared with state-of-the-art MIL methods.

Gene masking - a technique to improve accuracy for cancer classification with high dimensionality in microarray data.

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Saini, Harsh; Lal, Sunil Pranit; Naidu, Vimal Vikash; Pickering, Vincel Wince; Singh, Gurmeet; Tsunoda, Tatsuhiko; Sharma, Alok

2016-12-05

High dimensional feature space generally degrades classification in several applications. In this paper, we propose a strategy called gene masking, in which non-contributing dimensions are heuristically removed from the data to improve classification accuracy. Gene masking is implemented via a binary encoded genetic algorithm that can be integrated seamlessly with classifiers during the training phase of classification to perform feature selection. It can also be used to discriminate between features that contribute most to the classification, thereby, allowing researchers to isolate features that may have special significance. This technique was applied on publicly available datasets whereby it substantially reduced the number of features used for classification while maintaining high accuracies. The proposed technique can be extremely useful in feature selection as it heuristically removes non-contributing features to improve the performance of classifiers.

Single-tree harvesting reduces survival and growth of oak stump sprouts in the Missouri Ozark Highlands

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Daniel C. Dey; Randy G. Jensen; Michael J. Wallendorf

2008-01-01

Regeneration and recruitment into the overstory is critical to the success of using uneven-aged systems to sustain oak forests. We evaluated survival and growth of white oak (Quercus alba L.), black oak (Q. velutina Lam.), and scarlet oak (Q. coccinea Muenchh.) stump sprouts 10 years after harvesting Ozark...

Proposal of a new classification scheme for periocular injuries

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Devi Prasad Mohapatra

2017-01-01

Full Text Available Background: Eyelids are important structures and play a role in protecting the globe from trauma, brightness, in maintaining the integrity of tear films and moving the tears towards the lacrimal drainage system and contribute to aesthetic appearance of the face. Ophthalmic trauma is an important cause of morbidity among individuals and has also been responsible for additional cost of healthcare. Periocular trauma involving eyelids and adjacent structures has been found to have increased recently probably due to increased pace of life and increased dependence on machinery. A comprehensive classification of periocular trauma would help in stratifying these injuries as well as study outcomes. Material and Methods: This study was carried out at our institute from June 2015 to Dec 2015. We searched multiple English language databases for existing classification systems for periocular trauma. We designed a system of classification of periocular soft tissue injuries based on clinico-anatomical presentations. This classification was applied prospectively to patients presenting with periocular soft tissue injuries to our department. Results: A comprehensive classification scheme was designed consisting of five types of periocular injuries. A total of 38 eyelid injuries in 34 patients were evaluated in this study. According to the System for Peri-Ocular Trauma (SPOT classification, Type V injuries were most common. SPOT Type II injuries were more common isolated injuries among all zones. Discussion: Classification systems are necessary in order to provide a framework in which to scientifically study the etiology, pathogenesis, and treatment of diseases in an orderly fashion. The SPOT classification has taken into account the periocular soft tissue injuries i.e., upper eyelid, lower eyelid, medial and lateral canthus injuries., based on observed clinico-anatomical patterns of eyelid injuries. Conclusion: The SPOT classification seems to be a reliable

Hybrid analysis for indicating patients with breast cancer using temperature time series.

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Silva, Lincoln F; Santos, Alair Augusto S M D; Bravo, Renato S; Silva, Aristófanes C; Muchaluat-Saade, Débora C; Conci, Aura

2016-07-01

Breast cancer is the most common cancer among women worldwide. Diagnosis and treatment in early stages increase cure chances. The temperature of cancerous tissue is generally higher than that of healthy surrounding tissues, making thermography an option to be considered in screening strategies of this cancer type. This paper proposes a hybrid methodology for analyzing dynamic infrared thermography in order to indicate patients with risk of breast cancer, using unsupervised and supervised machine learning techniques, which characterizes the methodology as hybrid. The dynamic infrared thermography monitors or quantitatively measures temperature changes on the examined surface, after a thermal stress. In the dynamic infrared thermography execution, a sequence of breast thermograms is generated. In the proposed methodology, this sequence is processed and analyzed by several techniques. First, the region of the breasts is segmented and the thermograms of the sequence are registered. Then, temperature time series are built and the k-means algorithm is applied on these series using various values of k. Clustering formed by k-means algorithm, for each k value, is evaluated using clustering validation indices, generating values treated as features in the classification model construction step. A data mining tool was used to solve the combined algorithm selection and hyperparameter optimization (CASH) problem in classification tasks. Besides the classification algorithm recommended by the data mining tool, classifiers based on Bayesian networks, neural networks, decision rules and decision tree were executed on the data set used for evaluation. Test results support that the proposed analysis methodology is able to indicate patients with breast cancer. Among 39 tested classification algorithms, K-Star and Bayes Net presented 100% classification accuracy. Furthermore, among the Bayes Net, multi-layer perceptron, decision table and random forest classification algorithms, an

[Vacuum sealing drainage combined with free skin graft in repairing cutaneous deficiency of traumatic shank amputation stump].

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Zhao, Xiao-fei; Li, Chun-you; Jin, Guo-qiang; Ming, Xiao-feng; Wang, Guo-jie

2014-12-01

To observe clinical efficacy in treating cutaneous deficiency of traumatic shank amputation stump with full-thickness skin graft combined with vacuum sealing drainage. From September 2009 to December 2012, 15 patients with cutaneous deficiency of traumatic shank amputation stump were treated with full-thickness skin graft combined with vacuum sealing drainage. Among patients, there were 11 males and 4 females with an average age of 41.5 (ranged from 25 to 62) years old. Ten cases were caused by traffic accident and 5 cases were caused by heavy object, 9 cases on left and 6 cases on right. Six patients with smashed wound were treated with debridement and amputation, combined with vacuum aspiration in-emergency; 9 patients caused by infection and necrosis were treated with debridement and amputation, combined with vacuum aspiration, and full-thickness skin graft were performed at stage II. The skin defect area of residual limbs ranged from 40 cm x 20 cm to 25 cm x 15 cm. All patients were followed up from 3 months to 1 year. Full-thickness skin graft of residual limbs were survived,and obtained satisfactory walking function with prosthetic. Residual skin increased thicken, wearproof without rupture and pain. Full-thickness skin graft combined with vacuum sealing drainage in treating cutaneous deficiency of traumatic shank amputation stump could reserve the length of residual limbs, increase survival rate of skin graft with less scar of survival skin, get good wearability and it is conducive to prosthetic wear. It is a simple and easy treatment method.

Pancreatic stump closure using only stapler is associated with high postoperative fistula rate after minimal invasive surgery.

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Yüksel, Adem; Bostancı, Erdal Birol; Çolakoğlu, Muhammet Kadri; Ulaş, Murat; Özer, İlter; Karaman, Kerem; Akoğlu, Musa

2018-03-01

Postoperative pancreatic fistula (POPF) is the most common cause of morbidity and mortality after distal pancreatectomy (DP). The aim of the present study is to determine the risk factors that can lead to POPF. The study was conducted between January 2008 and December 2012. A total of 96 patients who underwent DP were retrospectively analyzed. Overall, 24 patients (25%) underwent laparoscopic distal pancreatectomy (LDP) and 72 patients (75%) open surgery. The overall morbidity rate was 51% (49/96). POPF (32/96, 33.3%) was the most common postoperative complication. Grade B fistula (18/32, 56.2%) was the most common fistula type according to the International Study Group on Pancreatic Fistula definition. POPF rate was significantly higher in the minimally invasive surgery group (50%, p=0.046). POPF rate was 58.6% (17/29) in patients whose pancreatic stump closure was performed with only stapler, whereas POPF rate was 3.6% (1/28) in the group where the stump was closed with stapler plus oversewing sutures. Both minimally invasive surgery (OR: 0.286, 95% CI: 0.106-0.776, p=0.014) and intraoperative blood transfusion (OR: 4.210, 95% CI: 1.155-15.354, p=0.029) were detected as independent risk factors for POPF in multi-variety analysis. LDP is associated with a higher risk of POPF when stump closure is performed with only staplers. Intraoperative blood transfusion is another risk factor for POPF. On the other hand, oversewing sutures to the stapler line reduces the risk of POPF.

A simple working classification proposed for the latrogenic lesions of teeth and associated structures in the oral cavity.

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Shamim, Thorakkal

2013-09-01

Iatrogenic lesions can affect both hard and soft tissues in the oral cavity, induced by the dentist's activity, manner or therapy. There is no approved simple working classification for the iatrogenic lesions of teeth and associated structures in the oral cavity in the literature. A simple working classification is proposed here for iatrogenic lesions of teeth and associated structures in the oral cavity based on its relation with dental specialities. The dental specialities considered in this classification are conservative dentistry and endodontics, orthodontics, oral and maxillofacial surgery and prosthodontics. This classification will be useful for the dental clinician who is dealing with diseases of oral cavity.

Rough set soft computing cancer classification and network: one stone, two birds.

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Zhang, Yue

2010-07-15

Gene expression profiling provides tremendous information to help unravel the complexity of cancer. The selection of the most informative genes from huge noise for cancer classification has taken centre stage, along with predicting the function of such identified genes and the construction of direct gene regulatory networks at different system levels with a tuneable parameter. A new study by Wang and Gotoh described a novel Variable Precision Rough Sets-rooted robust soft computing method to successfully address these problems and has yielded some new insights. The significance of this progress and its perspectives will be discussed in this article.

North American Magazine Coverage of Skin Cancer and Recreational Tanning Before and After the WHO/IARC 2009 Classification of Indoor Tanning Devices as Carcinogenic.

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McWhirter, Jennifer E; Hoffman-Goetz, Laurie

2015-09-01

The mass media is an influential source of skin cancer information for the public. In 2009, the World Health Organization's International Agency for Research on Cancer classified UV radiation from tanning devices as carcinogenic. Our objective was to determine if media coverage of skin cancer and recreational tanning increased in volume or changed in nature after this classification. We conducted a directed content analysis on 29 North American popular magazines (2007-2012) to investigate the overall volume of articles on skin cancer and recreational tanning and, more specifically, the presence of skin cancer risk factors, UV behaviors, and early detection information in article text (n = 410) and images (n = 714). The volume of coverage on skin cancer and recreational tanning did not increase significantly after the 2009 classification of tanning beds as carcinogenic. Key-related messages, including that UV exposure is a risk factor for skin cancer and that indoor tanning should be avoided, were not reported more frequently after the classification, but the promotion of the tanned look as attractive was conveyed more often in images afterwards (p skin cancer risk factors, other UV behaviors, or early detection information over time. The classification of indoor tanning beds as carcinogenic had no significant impact on the volume or nature of skin cancer and recreational tanning coverage in magazines.

Colorectal cancer complicating Crohn's disease.

Science.gov (United States)

Freeman, H J

2001-04-01

Some earlier studies have indicated that patients with inflammatory bowel disease, especially those with long-standing and extensive ulcerative colitis, have an increased risk of colorectal cancer. Moreover, others in tertiary care centres have suggested that patients with Crohn's disease also have a higher risk of colorectal cancer. Canadian data on colorectal cancer in Crohn's disease appear to be limited. For this investigation, a single clinician database of 877 patients with Crohn's disease was used. Altogether, there were six patients with colorectal cancer (ie, overall rate of 0.7%). All of these patients were men with an initial diagnosis of Crohn's disease established at a mean age of approximately 28 years, with either ileocolonic disease or colonic disease alone, but not with ileal disease alone. Although there was a predominance of women in the overall study population (ie, 56.1%), no women developed colorectal cancer. The clinical behaviour of Crohn's disease was classified as nonstricturing in all six patients with colorectal cancer, but in two patients, Crohn's disease was complicated by a perirectal abscess or a fistula. All cancers were located in the rectum and were diagnosed 30 years, 22 years, seven years, 18 years, 20 years and 40 years after Crohn's disease was initially diagnosed. In three patients, the cancer was detected in a residual rectal stump after a partial colon resection at least 10 years earlier. In five patients, localized extension of disease through the serosa, nodal or distant metastases (ie, liver, lung) was found at the time of cancer diagnosis; two patients have since died. The present study confirms that Crohn's disease involving the colon may be a possible risk factor for the development of colorectal cancer, at least in younger men, but, in this study, not in women. However, part of this increased risk in men may have been related to the presence of a rectal stump, rather than to Crohn's disease per se.

Colorectal Cancer Complicating Crohn's Disease

Directory of Open Access Journals (Sweden)

Hugh J Freeman

2001-01-01

Full Text Available Some earlier studies have indicated that patients with inflammatory bowel disease, especially those with long-standing and extensive ulcerative colitis, have an increased risk of colorectal cancer. Moreover, others in tertiary care centres have suggested that patients with Crohn's disease also have a higher risk of colorectal cancer. Canadian data on colorectal cancer in Crohn's disease appear to be limited. For this investigation, a single clinician database of 877 patients with Crohn's disease was used. Altogether, there were six patients with colorectal cancer (ie, overall rate of 0.7%. All of these patients were men with an initial diagnosis of Crohn's disease established at a mean age of approximately 28 years, with either ileocolonic disease or colonic disease alone, but not with ileal disease alone. Although there was a predominance of women in the overall study population (ie, 56.1%, no women developed colorectal cancer. The clinical behaviour of Crohn's disease was classified as nonstricturing in all six patients with colorectal cancer, but in two patients, Crohn's disease was complicated by a perirectal abscess or a fistula. All cancers were located in the rectum and were diagnosed 30 years, 22 years, seven years, 18 years, 20 years and 40 years after Crohn's disease was initially diagnosed. In three patients, the cancer was detected in a residual rectal stump after a partial colon resection at least 10 years earlier. In five patients, localized extension of disease through the serosa, nodal or distant metastases (ie, liver, lung was found at the time of cancer diagnosis; two patients have since died. The present study confirms that Crohn's disease involving the colon may be a possible risk factor for the development of colorectal cancer, at least in younger men, but, in this study, not in women. However, part of this increased risk in men may have been related to the presence of a rectal stump, rather than to Crohn's disease per se.

Reflecting on the structure of soil classification systems: insights from a proposal for integrating subsoil data into soil information systems

Science.gov (United States)

Dondeyne, Stefaan; Juilleret, Jérôme; Vancampenhout, Karen; Deckers, Jozef; Hissler, Christophe

2017-04-01

Classification of soils in both World Reference Base for soil resources (WRB) and Soil Taxonomy hinges on the identification of diagnostic horizons and characteristics. However as these features often occur within the first 100 cm, these classification systems convey little information on subsoil characteristics. An integrated knowledge of the soil, soil-to-substratum and deeper substratum continuum is required when dealing with environmental issues such as vegetation ecology, water quality or the Critical Zone in general. Therefore, we recently proposed a classification system of the subsolum complementing current soil classification systems. By reflecting on the structure of the subsoil classification system which is inspired by WRB, we aim at fostering a discussion on some potential future developments of WRB. For classifying the subsolum we define Regolite, Saprolite, Saprock and Bedrock as four Subsolum Reference Groups each corresponding to different weathering stages of the subsoil. Principal qualifiers can be used to categorize intergrades of these Subsoil Reference Groups while morphologic and lithologic characteristics can be presented with supplementary qualifiers. We argue that adopting a low hierarchical structure - akin to WRB and in contrast to a strong hierarchical structure as in Soil Taxonomy - offers the advantage of having an open classification system avoiding the need for a priori knowledge of all possible combinations which may be encountered in the field. Just as in WRB we also propose to use principal and supplementary qualifiers as a second level of classification. However, in contrast to WRB we propose to reserve the principal qualifiers for intergrades and to regroup the supplementary qualifiers into thematic categories (morphologic or lithologic). Structuring the qualifiers in this manner should facilitate the integration and handling of both soil and subsoil classification units into soil information systems and calls for paying

Genetic Fuzzy System (GFS based wavelet co-occurrence feature selection in mammogram classification for breast cancer diagnosis

Directory of Open Access Journals (Sweden)

Meenakshi M. Pawar

2016-09-01

Full Text Available Breast cancer is significant health problem diagnosed mostly in women worldwide. Therefore, early detection of breast cancer is performed with the help of digital mammography, which can reduce mortality rate. This paper presents wrapper based feature selection approach for wavelet co-occurrence feature (WCF using Genetic Fuzzy System (GFS in mammogram classification problem. The performance of GFS algorithm is explained using mini-MIAS database. WCF features are obtained from detail wavelet coefficients at each level of decomposition of mammogram image. At first level of decomposition, 18 features are applied to GFS algorithm, which selects 5 features with an average classification success rate of 39.64%. Subsequently, at second level it selects 9 features from 36 features and the classification success rate is improved to 56.75%. For third level, 16 features are selected from 54 features and average success rate is improved to 64.98%. Lastly, at fourth level 72 features are applied to GFS, which selects 16 features and thereby increasing average success rate to 89.47%. Hence, GFS algorithm is the effective way of obtaining optimal set of feature in breast cancer diagnosis.

78 FR 2447 - Proposed Information Collection Request (ICR) for the Worker Classification Survey; Comment Request

Science.gov (United States)

2013-01-11

... minimum wage and/or overtime, as well as programs like unemployment insurance and workers' compensation... DEPARTMENT OF LABOR Wage and Hour Division Proposed Information Collection Request (ICR) for the Worker Classification Survey; Comment Request AGENCY: Wage and Hour Division, Labor. ACTION: Notice...

Can the Ni classification of vessels predict neoplasia?

DEFF Research Database (Denmark)

Mehlum, Camilla Slot; Rosenberg, Tine; Dyrvig, Anne-Kirstine

2018-01-01

OBJECTIVES: The Ni classification of vascular change from 2011 is well documented for evaluating pharyngeal and laryngeal lesions, primarily focusing on cancer. In the planning of surgery it may be more relevant to differentiate neoplasia from non-neoplasia. We aimed to evaluate the ability...... of the Ni classification to predict laryngeal or hypopharyngeal neoplasia and to investigate if a changed cutoff value would support the recent European Laryngological Society (ELS) proposal of perpendicular vascular changes as indicative of neoplasia. DATA SOURCES: PubMed, Embase, Cochrane, and Scopus....... The pooled sensitivity and specificity of the Ni classification with two different cutoffs were calculated, and bubble and summary receiver operating characteristics plots were created. RESULTS: The combined sensitivity of five studies (n = 687) with Ni type IV-V defined as test-positive was 0.89 (95...

Risk factors and classifications of hilar cholangiocarcinoma.

Science.gov (United States)

Suarez-Munoz, Miguel Angel; Fernandez-Aguilar, Jose Luis; Sanchez-Perez, Belinda; Perez-Daga, Jose Antonio; Garcia-Albiach, Beatriz; Pulido-Roa, Ysabel; Marin-Camero, Naiara; Santoyo-Santoyo, Julio

2013-07-15

Cholangiocarcinoma is the second most common primary malignant tumor of the liver. Perihilar cholangiocarcinoma or Klatskin tumor represents more than 50% of all biliary tract cholangiocarcinomas. A wide range of risk factors have been identified among patients with Perihilar cholangiocarcinoma including advanced age, male gender, primary sclerosing cholangitis, choledochal cysts, cholelithiasis, cholecystitis, parasitic infection (Opisthorchis viverrini and Clonorchis sinensis), inflammatory bowel disease, alcoholic cirrhosis, nonalcoholic cirrhosis, chronic pancreatitis and metabolic syndrome. Various classifications have been used to describe the pathologic and radiologic appearance of cholangiocarcinoma. The three systems most commonly used to evaluate Perihilar cholangiocarcinoma are the Bismuth-Corlette (BC) system, the Memorial Sloan-Kettering Cancer Center and the TNM classification. The BC classification provides preoperative assessment of local spread. The Memorial Sloan-Kettering cancer center proposes a staging system according to three factors related to local tumor extent: the location and extent of bile duct involvement, the presence or absence of portal venous invasion, and the presence or absence of hepatic lobar atrophy. The TNM classification, besides the usual descriptors, tumor, node and metastases, provides additional information concerning the possibility for the residual tumor (R) and the histological grade (G). Recently, in 2011, a new consensus classification for the Perihilar cholangiocarcinoma had been published. The consensus was organised by the European Hepato-Pancreato-Biliary Association which identified the need for a new staging system for this type of tumors. The classification includes information concerning biliary or vascular (portal or arterial) involvement, lymph node status or metastases, but also other essential aspects related to the surgical risk, such as remnant hepatic volume or the possibility of underlying disease.

Classification tree analysis of second neoplasms in survivors of childhood cancer

International Nuclear Information System (INIS)

Jazbec, Janez; Todorovski, Ljupčo; Jereb, Berta

2007-01-01

Reports on childhood cancer survivors estimated cumulative probability of developing secondary neoplasms vary from 3,3% to 25% at 25 years from diagnosis, and the risk of developing another cancer to several times greater than in the general population. In our retrospective study, we have used the classification tree multivariate method on a group of 849 first cancer survivors, to identify childhood cancer patients with the greatest risk for development of secondary neoplasms. In observed group of patients, 34 develop secondary neoplasm after treatment of primary cancer. Analysis of parameters present at the treatment of first cancer, exposed two groups of patients at the special risk for secondary neoplasm. First are female patients treated for Hodgkin's disease at the age between 10 and 15 years, whose treatment included radiotherapy. Second group at special risk were male patients with acute lymphoblastic leukemia who were treated at the age between 4,6 and 6,6 years of age. The risk groups identified in our study are similar to the results of studies that used more conventional approaches. Usefulness of our approach in study of occurrence of second neoplasms should be confirmed in larger sample study, but user friendly presentation of results makes it attractive for further studies

Arterial Stump Thrombosis after Lung Resection Surgery: Clinical Presentation, Treatment and Progress.

Science.gov (United States)

López-Padilla, Daniel; Peghini Gavilanes, Esteban; Revilla Ostolaza, Teresa Yolanda; Trujillo, María Dolores; Martínez Serna, Iván; Arenas Valls, Nuria; Girón Matute, Walther Iván; Larrosa-Barrero, Roberto; Manrique Mutiozabal, Adriana; Pérez Gallán, Marta; Zevallos, Annette; Sayas Catalán, Javier

2016-10-01

To determine the prevalence of arterial stump thrombosis (AST) after pulmonary resection surgery for lung cancer and to describe subsequent radiological follow-up and treatment. Observational, descriptive study of AST detected by computerized tomography angiography (CT) using intravenous contrast. Clinical and radiological variables were compared and a survival analysis using Kaplan-Meier curves was performed after dividing patients into 3 groups: patients with AST, patients with pulmonary embolism (PE), and patients without AST or PE. Nine cases of AST were detected after a total of 473 surgeries (1.9%), 6 of them in right-sided surgeries (67% of AST cases). Median time to detection after surgery was 11.3 months (interquartile range 2.7-42.2 months), and range 67.5 months (1.4-69.0 months). Statistically significant differences were found only in the number of CTs performed in AST patients compared to those without AST or PE, and in tumor recurrence in PE patients compared to the other 2 groups. No differences were found in baseline or oncological characteristics, nor in the survival analysis. In this series, AST prevalence was low and tended to occur in right-sided surgeries. Detection over time was variable, and unrelated to risk factors previous to surgery, histopathology, and tumor stage or recurrence. AST had no impact on patient survival. Copyright © 2016 SEPAR. Publicado por Elsevier España, S.L.U. All rights reserved.

Biobank classification in an Australian setting.

Science.gov (United States)

Rush, Amanda; Christiansen, Jeffrey H; Farrell, Jake P; Goode, Susan M; Scott, Rodney J; Spring, Kevin J; Byrne, Jennifer A

2015-06-01

In 2011, Watson and Barnes proposed a schema for classifying biobanks into 3 groups (mono-, oligo-, and poly-user), primarily based upon biospecimen access policies. We used results from a recent comprehensive survey of cancer biobanks in New South Wales, Australia to assess the applicability of this biobank classification schema in an Australian setting. Cancer biobanks were identified using publically available data, and by consulting with research managers. A comprehensive survey was developed and administered through a face-to-face setting. Data were analyzed using Microsoft Excel™ 2010 and IBM SPSS Statistics™ version 21.0. The cancer biobank cohort (n=23) represented 5 mono-user biobanks, 7 oligo-user biobanks, and 11 poly-user biobanks, and was analyzed as two groups (mono-/oligo- versus poly-user biobanks). Poly-user biobanks employed significantly more full-time equivalent staff, and were significantly more likely to have a website, share staff between biobanks, access governance support, utilize quality control measures, be aware of biobanking best practice documents, and offer staff training. Mono-/oligo-user biobanks were significantly more likely to seek advice from other biobanks. Our results further delineate a biobank classification system that is primarily based on access policy, and demonstrate its relevance in an Australian setting.

Primary care physicians' use of the proposed classification of common mental disorders for ICD-11

DEFF Research Database (Denmark)

Goldberg, David P.; Lam, Tai-Pong; Minhas, Fareed

2017-01-01

Background. The World Health Organization is revising the classification of common mental disorders in primary care for ICD-11. Major changes from the ICD-10 primary care version have been proposed for: (i) mood and anxiety disorders; and (ii) presentations of multiple somatic symptoms (bodily...... stress syndrome). This three-part field study explored the implementation of the revised classification by primary care physicians (PCPs) in five countries. Methods. Participating PCPs in Brazil, China, Mexico, Pakistan and Spain were asked to use the revised classification, first in patients...... that they suspected might be psychologically distressed (Part 1), and second in patients with multiple somatic symptoms causing distress or disability not wholly attributable to a known physical pathology, or with high levels of health anxiety (Part 2). Patients referred to Part 1 or Part 2 underwent a structured...

Variation in Results of Volume Measurements of Stumps of Lower-Limb Amputees : A Comparison of 4 Methods

NARCIS (Netherlands)

de Boer-Wilzing, Vera G.; Bolt, Arjen; Geertzen, Jan H.; Emmelot, Cornelis H.; Baars, Erwin C.; Dijkstra, Pieter U.

de Boer-Wilzing VG, Bolt A, Geertzen JH, Emmelot CH, Baars EC, Dijkstra PU. Variation in results of volume measurements of stumps of lower-limb amputees: a comparison of 4 methods. Arch Phys Med Rehabil 2011;92:941-6. Objective: To analyze the reliability of 4 methods (water immersion,

Acute pesticide poisoning: a proposed classification tool.

Science.gov (United States)

Thundiyil, Josef G; Stober, Judy; Besbelli, Nida; Pronczuk, Jenny

2008-03-01

Cases of acute pesticide poisoning (APP) account for significant morbidity and mortality worldwide. Developing countries are particularly susceptible due to poorer regulation, lack of surveillance systems, less enforcement, lack of training and inadequate access to information systems. Previous research has demonstrated wide variability in incidence rates for APP. This is possibly due to inconsistent reporting methodology and exclusion of occupational and non-intentional poisonings. The purpose of this document is to create a standard case definition to facilitate the identification and diagnosis of all causes of APP, especially at the field level, rural clinics and primary health-care systems. This document is a synthesis of existing literature and case definitions that have been previously proposed by other authors around the world. It provides a standardized case definition and classification scheme for APP into categories of probable, possible and unlikely/unknown cases. Its use is intended to be applicable worldwide to contribute to identification of the scope of existing problems and thus promote action for improved management and prevention. By enabling a field diagnosis for APP, this standardized case definition may facilitate immediate medical management of pesticide poisoning and aid in estimating its incidence.

Radioactive wastes: a proposal to its classification

International Nuclear Information System (INIS)

Domenech N, H.; Garcia L, N.; Hernandez S, A.

1996-01-01

On the basis of the quantities and the characteristics of the stored radioactive wastes in Cuba and the IAEA system of wastes classification, the concentration activities that would be used as limits for those categories are evaluated. This approach suggests a limit of 10 TBq/m 3 for short lived liquid wastes of Low and Intermediate Level (less than 30 years) and 5 TBq/m 3 for long lived liquid wastes (more than 30 years). For solid wastes the suggested limits are ten times lower. Taking into account the small quantities of arising wastes and to make easy its segregation, collection and disposal, a low level waste sub-classification in three new categories, whether or not they may be direct discharged, is suggested. As lower classification limit, while not specific exemption levels are established in the country, the use of an ALI min fraction is emphasized, meanwhile the total discharged activity will be no greater than 10 MBq or 100 MBq when the discharge occurs over the whole year. (authors). 6 refs., 5 tabs

Old resinous turpentine stumps as an indicator of the range of longleaf pine in Southeastern Virginia

Science.gov (United States)

Thomas L. Eberhardt; Philip M. Sheridan; Jolie M. Mahfouz; Chi-Leung So

2006-01-01

Wood anatomy cannot be used to differentiate between the southern yellow pine species. Wood samples collected from old resinous turpentine stumps in coastal Virginia were subjected to chemical and spectroscopic analyses in an effort to determine if they could be identified as longleaf pine. The age and resinous nature of the samples were manifested in high specific...

[Stump forming after traumatic foot amputation of a child--description of a new surgical procedure and literature review of lawnmower accidents].

Science.gov (United States)

Bayer, J; Zajonc, H; Strohm, P C; Vohrer, M; Maier-Lenz, D; Südkamp, N P; Schwering, L

2009-01-01

Amputation injuries in children occur in motor vehicle, farming and, importantly, lawn mower accidents. Treatment of lawn mower related injuries is complicated by gross wound contamination, avascular tissue, soft tissue defects and exposed bone. Many treatment options exist and often an adequate prosthetic supply is needed for rehabilitation. We report on an 8-year old boy who got under a ride-on lawn mower and sustained a subtotal amputation of his right foot. After initial surgery an amputation was subsequently necessary. For this, it had to be taken into account that the traumatic loss of the talus, calcaneus and parts of the cuboid bone would result in a length shortening of the right leg and so far not injured metatarsal and tarsal bones had to be sacrificed. Thus, we aimed to develop a new operation technique to optimize stump length as well as preserve tarsal bones and the possibility of limb growth. In order to achieve this, we performed a new stump forming operation in which we integrated uninjured tarsal and metatarsal bones. First a Lisfranc's amputation was performed and a metatarsal bone was kept aside. The talus, calcaneus as well as the cuboid bone were either completely or almost completely destroyed and were removed. The remaining cuneiform bones were transfixed by a notched metatarsal bone, thus achieving a tarsal arthrodesis, and the cartilages of the proximal joint surfaces were removed. The cartilage of the cranial and caudal navicular as well as the distal tibial joint surface was also removed and an arthrodesis between the distal tibia and the navicular bone was achieved by crossed Kirschner wires. Finally the cuneiform bones were placed inferior to the navicular bone. Further stump coverage was managed by skin and muscle flaps as well as split skin graft. Our patient was discharged on day 34. A fluent gait without crutches as well as sports activities were possible again as early as 6 1/2 months after the injury. Using our stump forming

Call for a Computer-Aided Cancer Detection and Classification Research Initiative in Oman.

Science.gov (United States)

Mirzal, Andri; Chaudhry, Shafique Ahmad

2016-01-01

Cancer is a major health problem in Oman. It is reported that cancer incidence in Oman is the second highest after Saudi Arabia among Gulf Cooperation Council countries. Based on GLOBOCAN estimates, Oman is predicted to face an almost two-fold increase in cancer incidence in the period 2008-2020. However, cancer research in Oman is still in its infancy. This is due to the fact that medical institutions and infrastructure that play central roles in data collection and analysis are relatively new developments in Oman. We believe the country requires an organized plan and efforts to promote local cancer research. In this paper, we discuss current research progress in cancer diagnosis using machine learning techniques to optimize computer aided cancer detection and classification (CAD). We specifically discuss CAD using two major medical data, i.e., medical imaging and microarray gene expression profiling, because medical imaging like mammography, MRI, and PET have been widely used in Oman for assisting radiologists in early cancer diagnosis and microarray data have been proven to be a reliable source for differential diagnosis. We also discuss future cancer research directions and benefits to Oman economy for entering the cancer research and treatment business as it is a multi-billion dollar industry worldwide.

Proposal for the classification of closed indoor spaces according to concentration of 222Rn and the possible doses involved

International Nuclear Information System (INIS)

Espinoza, Marco; Leon, Kety; Martinez, Jorge

2014-01-01

Radon causes more than 50 % of total dose from natural background radiation per year. It is widely demonstrated the capacity of radon to induce lung cancer in people exposed to this radioactive gas for long periods. Radon emerges continuously from materials that constitute soils, building materials and minerals present in our natural environment, all over the world. In our country, it is necessary to get better regulations to control the exposition of people to this gas inside buildings, dwellings and facilities where people spend their time. Our country has very simple and scarce regulations on this respect. At present, national regulations about radon are adaptations of recommendations and guides published for international organizations but without national studies or statistics to give realistic support to those rules. This work propose a classification for closed spaces where people live and work in this country taking into consideration their 222 Rn concentration and probable doses involved. (authors).

78 FR 54970 - Cotton Futures Classification: Optional Classification Procedure

Science.gov (United States)

2013-09-09

... Service 7 CFR Part 27 [AMS-CN-13-0043] RIN 0581-AD33 Cotton Futures Classification: Optional Classification Procedure AGENCY: Agricultural Marketing Service, USDA. ACTION: Proposed rule. SUMMARY: The... optional cotton futures classification procedure--identified and known as ``registration'' by the U.S...

Breast cancer molecular subtype classification using deep features: preliminary results

Science.gov (United States)

Zhu, Zhe; Albadawy, Ehab; Saha, Ashirbani; Zhang, Jun; Harowicz, Michael R.; Mazurowski, Maciej A.

2018-02-01

Radiogenomics is a field of investigation that attempts to examine the relationship between imaging characteris- tics of cancerous lesions and their genomic composition. This could offer a noninvasive alternative to establishing genomic characteristics of tumors and aid cancer treatment planning. While deep learning has shown its supe- riority in many detection and classification tasks, breast cancer radiogenomic data suffers from a very limited number of training examples, which renders the training of the neural network for this problem directly and with no pretraining a very difficult task. In this study, we investigated an alternative deep learning approach referred to as deep features or off-the-shelf network approach to classify breast cancer molecular subtypes using breast dynamic contrast enhanced MRIs. We used the feature maps of different convolution layers and fully connected layers as features and trained support vector machines using these features for prediction. For the feature maps that have multiple layers, max-pooling was performed along each channel. We focused on distinguishing the Luminal A subtype from other subtypes. To evaluate the models, 10 fold cross-validation was performed and the final AUC was obtained by averaging the performance of all the folds. The highest average AUC obtained was 0.64 (0.95 CI: 0.57-0.71), using the feature maps of the last fully connected layer. This indicates the promise of using this approach to predict the breast cancer molecular subtypes. Since the best performance appears in the last fully connected layer, it also implies that breast cancer molecular subtypes may relate to high level image features

Breast Cancer Survival Defined by the ER/PR/HER2 Subtypes and a Surrogate Classification according to Tumor Grade and Immunohistochemical Biomarkers

Directory of Open Access Journals (Sweden)

Carol A. Parise

2014-01-01

Full Text Available Introduction. ER, PR, and HER2 are routinely available in breast cancer specimens. The purpose of this study is to contrast breast cancer-specific survival for the eight ER/PR/HER2 subtypes with survival of an immunohistochemical surrogate for the molecular subtype based on the ER/PR/HER2 subtypes and tumor grade. Methods. We identified 123,780 cases of stages 1–3 primary female invasive breast cancer from California Cancer Registry. The surrogate classification was derived using ER/PR/HER2 and tumor grade. Kaplan-Meier survival analysis and Cox proportional hazards modeling were used to assess differences in survival and risk of mortality for the ER/PR/HER2 subtypes and surrogate classification within each stage. Results. The luminal B/HER2− surrogate classification had a higher risk of mortality than the luminal B/HER2+ for all stages of disease. There was no difference in risk of mortality between the ER+/PR+/HER2− and ER+/PR+/HER2+ in stage 3. With one exception in stage 3, the ER-negative subtypes all had an increased risk of mortality when compared with the ER-positive subtypes. Conclusions. Assessment of survival using ER/PR/HER2 illustrates the heterogeneity of HER2+ subtypes. The surrogate classification provides clear separation in survival and adjusted mortality but underestimates the wide variability within the subtypes that make up the classification.

Breast Cancer Survival Defined by the ER/PR/HER2 Subtypes and a Surrogate Classification according to Tumor Grade and Immunohistochemical Bio markers

International Nuclear Information System (INIS)

Parise, C. A.; Caggiano, V.

2014-01-01

ER, PR, and HER2 are routinely available in breast cancer specimens. The purpose of this study is to contrast breast cancer-specific survival for the eight ER/PR/HER2 subtypes with survival of an immunohistochemical surrogate for the molecular subtype based on the ER/PR/HER2 subtypes and tumor grade. Methods. We identified 123,780 cases of stages 1-3 primary female invasive breast cancer from California Cancer Registry. The surrogate classification was derived using ER/PR/HER2 and tumor grade. Kaplan-Meier survival analysis and Cox proportional hazards modeling were used to assess differences in survival and risk of mortality for the ER/PR/HER2 subtypes and surrogate classification within each stage. Results. The luminal B/HER2− surrogate classification had a higher risk of mortality than the luminal B/HER2+ for all stages of disease. There was no difference in risk of mortality between the ER+/PR+/HER2− and ER+/PR+/HER2+ in stage 3. With one exception in stage 3, the ER-negative subtypes all had an increased risk of mortality when compared with the ER-positive subtypes. Conclusions. Assessment of survival using ER/PR/HER2 illustrates the heterogeneity of HER2+ subtypes. The surrogate classification provides clear separation in survival and adjusted mortality but underestimates the wide variability within the subtypes that make up the classification.

Fungal Transformation of Tree Stumps into a Suitable Resource for Xylophagous Beetles via Changes in Elemental Ratios

Directory of Open Access Journals (Sweden)

Michał Filipiak

2016-04-01

Full Text Available The elements present in dead pine stumps inhabited by larvae of wood-boring beetles (Stictoleptura rubra, Arhopalus rusticus and Chalcophora mariana were analyzed over the initial (first 5 years; a chronosequence stages of wood decay. The quantities of N, P, K, Ca, Mg, Fe, Zn, Mn, Cu and Na (but not S increased with increases in the content of ergosterol (used as a proxy for the amount of fungal tissue. In fact, the amounts of P, N, K, Fe and Cu presented marked increases. These findings show that fungi stoichiometrically rearrange dead wood by importing externally occurring nutrients to decaying stumps. During the first years of wood decay, the ratios of C to other elements decrease substantially, but differently, for various elements, whereas the N:Fe, N:Cu, N:P and N:K ratios remain relatively stable. Therefore, the stoichiometric mismatch between xylophages and their food is greatly reduced. By changing the nutritional stoichiometry of dead wood, fungi create a nutritional niche for wood-eaters, and these changes enable the development of xylophages.

Fungal Transformation of Tree Stumps into a Suitable Resource for Xylophagous Beetles via Changes in Elemental Ratios

Science.gov (United States)

Filipiak, Michał; Sobczyk, Łukasz; Weiner, January

2016-01-01

The elements present in dead pine stumps inhabited by larvae of wood-boring beetles (Stictoleptura rubra, Arhopalus rusticus and Chalcophora mariana) were analyzed over the initial (first 5 years; a chronosequence) stages of wood decay. The quantities of N, P, K, Ca, Mg, Fe, Zn, Mn, Cu and Na (but not S) increased with increases in the content of ergosterol (used as a proxy for the amount of fungal tissue). In fact, the amounts of P, N, K, Fe and Cu presented marked increases. These findings show that fungi stoichiometrically rearrange dead wood by importing externally occurring nutrients to decaying stumps. During the first years of wood decay, the ratios of C to other elements decrease substantially, but differently, for various elements, whereas the N:Fe, N:Cu, N:P and N:K ratios remain relatively stable. Therefore, the stoichiometric mismatch between xylophages and their food is greatly reduced. By changing the nutritional stoichiometry of dead wood, fungi create a nutritional niche for wood-eaters, and these changes enable the development of xylophages.

Comparison of extra-corporeal knot-tying suture and metallic endo-clips in laparoscopic appendiceal stump closure in uncomplicated acute appendicitis

Directory of Open Access Journals (Sweden)

M. Nadeem

2016-01-01

Conclusion: The use of metallic endoclip for appendix stump closure is safe and less time consuming but costs higher. Because of the simplicity of the technique it's a useful alternative to the extracorporeal knotting especially for learners.

Training ANFIS structure using genetic algorithm for liver cancer classification based on microarray gene expression data

Directory of Open Access Journals (Sweden)

Bülent Haznedar

2017-02-01

Full Text Available Classification is an important data mining technique, which is used in many fields mostly exemplified as medicine, genetics and biomedical engineering. The number of studies about classification of the datum on DNA microarray gene expression is specifically increased in recent years. However, because of the reasons as the abundance of gene numbers in the datum as microarray gene expressions and the nonlinear relations mostly across those datum, the success of conventional classification algorithms can be limited. Because of these reasons, the interest on classification methods which are based on artificial intelligence to solve the problem on classification has been gradually increased in recent times. In this study, a hybrid approach which is based on Adaptive Neuro-Fuzzy Inference System (ANFIS and Genetic Algorithm (GA are suggested in order to classify liver microarray cancer data set. Simulation results are compared with the results of other methods. According to the results obtained, it is seen that the recommended method is better than the other methods.

PCA based feature reduction to improve the accuracy of decision tree c4.5 classification

Science.gov (United States)

Nasution, M. Z. F.; Sitompul, O. S.; Ramli, M.

2018-03-01

Splitting attribute is a major process in Decision Tree C4.5 classification. However, this process does not give a significant impact on the establishment of the decision tree in terms of removing irrelevant features. It is a major problem in decision tree classification process called over-fitting resulting from noisy data and irrelevant features. In turns, over-fitting creates misclassification and data imbalance. Many algorithms have been proposed to overcome misclassification and overfitting on classifications Decision Tree C4.5. Feature reduction is one of important issues in classification model which is intended to remove irrelevant data in order to improve accuracy. The feature reduction framework is used to simplify high dimensional data to low dimensional data with non-correlated attributes. In this research, we proposed a framework for selecting relevant and non-correlated feature subsets. We consider principal component analysis (PCA) for feature reduction to perform non-correlated feature selection and Decision Tree C4.5 algorithm for the classification. From the experiments conducted using available data sets from UCI Cervical cancer data set repository with 858 instances and 36 attributes, we evaluated the performance of our framework based on accuracy, specificity and precision. Experimental results show that our proposed framework is robust to enhance classification accuracy with 90.70% accuracy rates.

Classification of Cancer-related Death Certificates using Machine Learning

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Luke Butt

2013-05-01

Full Text Available BackgroundCancer monitoring and prevention relies on the critical aspect of timely notification of cancer cases. However, the abstraction and classification of cancer from the free-text of pathology reports and other relevant documents, such as death certificates, exist as complex and time-consuming activities.AimsIn this paper, approaches for the automatic detection of notifiable cancer cases as the cause of death from free-text death certificates supplied to Cancer Registries are investigated.Method A number of machine learning classifiers were studied. Features were extracted using natural language techniques and the Medtex toolkit. The numerous features encompassed stemmed words, bi-grams, and concepts from the SNOMED CT medical terminology. The baseline consisted of a keyword spotter using keywords extracted from the long description of ICD-10 cancer related codes.ResultsDeath certificates with notifiable cancer listed as the cause of death can be effectively identified with the methods studied in this paper. A Support Vector Machine (SVM classifier achieved best performance with an overall F-measure of 0.9866 when evaluated on a set of 5,000 free-text death certificates using the token stem feature set. The SNOMED CT concept plus token stem feature set reached the lowest variance (0.0032 and false negative rate (0.0297 while achieving an F-measure of 0.9864. The SVM classifier accounts for the first 18 of the top 40 evaluated runs, and entails the most robust classifier with a variance of 0.001141, half the variance of the other classifiers.ConclusionThe selection of features significantly produced the most influences on the performance of the classifiers, although the type of classifier employed also affects performance. In contrast, the feature weighting schema created a negligible effect on performance. Specifically, it is found that stemmed tokens with or without SNOMED CT concepts create the most effective feature when combined with

Investigating the mechanism underlying urinary continence recovery after radical prostatectomy: effectiveness of a longer urethral stump to prevent urinary incontinence.

Science.gov (United States)

Kadono, Yoshifumi; Nohara, Takahiro; Kawaguchi, Shohei; Naito, Renato; Urata, Satoko; Nakashima, Kazufumi; Iijima, Masashi; Shigehara, Kazuyoshi; Izumi, Kouji; Gabata, Toshifumi; Mizokami, Atsushi

2018-02-28

To assess the chronological changes in urinary incontinence and urethral function before and after radical prostatectomy (RP), and to compare the findings of pelvic magnetic resonance imaging (MRI) before and after RP to evaluate the anatomical changes. In total, 185 patients were evaluated with regard to the position of the distal end of the membranous urethra (DMU) on a mid-sagittal MRI slice and urethral sphincter function using the urethral pressure profilometry. The patients also underwent an abdominal leak point pressure test before RP and at 10 days and 12 months after RP. The results were then compared with the chronological changes in urinary incontinence. The MRI results showed that the DMU shifted proximally to an average distance of 4 mm at 10 days after RP and returned to the preoperative position at 12 months after RP. Urethral sphincter function also worsened 10 days after RP, with recovery after 12 months. The residual length of the urethral stump and urinary incontinence were significantly associated with the migration length of the DMU at 10 days after RP. The residual length of the urethral stump was a significant predictor of urinary incontinence after RP. This is the first study to elucidate that the slight vertical repositioning of the membranous urethra after RP causes chronological changes in urinary incontinence. A long urethral residual stump reduces urinary incontinence after RP. © 2018 The Authors BJU International © 2018 BJU International Published by John Wiley & Sons Ltd.

Validation of the prognostic gene portfolio, ClinicoMolecular Triad Classification, using an independent prospective breast cancer cohort and external patient populations.

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Wang, Dong-Yu; Done, Susan J; Mc Cready, David R; Leong, Wey L

2014-07-04

Using genome-wide expression profiles of a prospective training cohort of breast cancer patients, ClinicoMolecular Triad Classification (CMTC) was recently developed to classify breast cancers into three clinically relevant groups to aid treatment decisions. CMTC was found to be both prognostic and predictive in a large external breast cancer cohort in that study. This study serves to validate the reproducibility of CMTC and its prognostic value using independent patient cohorts. An independent internal cohort (n = 284) and a new external cohort (n = 2,181) were used to validate the association of CMTC between clinicopathological factors, 12 known gene signatures, two molecular subtype classifiers, and 19 oncogenic signalling pathway activities, and to reproduce the abilities of CMTC to predict clinical outcomes of breast cancer. In addition, we also updated the outcome data of the original training cohort (n = 147). The original training cohort reached a statistically significant difference (p value of the triad classification was reproduced in the second independent internal cohort and the new external validation cohort. CMTC achieved even higher prognostic significance when all available patients were analyzed (n = 4,851). Oncogenic pathways Myc, E2F1, Ras and β-catenin were again implicated in the high-risk groups. Both prospective internal cohorts and the independent external cohorts reproduced the triad classification of CMTC and its prognostic significance. CMTC is an independent prognostic predictor, and it outperformed 12 other known prognostic gene signatures, molecular subtype classifications, and all other standard prognostic clinicopathological factors. Our results support further development of CMTC portfolio into a guide for personalized breast cancer treatments.

Modern principles of prevention of anophthalmic syndrome: formation of the locomotor stump, the types of orbital implants

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I. V. Zapuskalov

2017-01-01

Full Text Available This article analyzes the current state of the problem of the correction of anophthalmic syndrome. Evaluated various methods of formation of the locomotor stump after removal of the eyeball, gave a detailed description of different types of materials for the fabrication of orbital implant, as well as reflect the basic principles of prevention of complications.

Classification of masses on mammograms using support vector machine

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Chu, Yong; Li, Lihua; Goldgof, Dmitry B.; Qui, Yan; Clark, Robert A.

2003-05-01

Mammography is the most effective method for early detection of breast cancer. However, the positive predictive value for classification of malignant and benign lesion from mammographic images is not very high. Clinical studies have shown that most biopsies for cancer are very low, between 15% and 30%. It is important to increase the diagnostic accuracy by improving the positive predictive value to reduce the number of unnecessary biopsies. In this paper, a new classification method was proposed to distinguish malignant from benign masses in mammography by Support Vector Machine (SVM) method. Thirteen features were selected based on receiver operating characteristic (ROC) analysis of classification using individual feature. These features include four shape features, two gradient features and seven Laws features. With these features, SVM was used to classify the masses into two categories, benign and malignant, in which a Gaussian kernel and sequential minimal optimization learning technique are performed. The data set used in this study consists of 193 cases, in which there are 96 benign cases and 97 malignant cases. The leave-one-out evaluation of SVM classifier was taken. The results show that the positive predict value of the presented method is 81.6% with the sensitivity of 83.7% and the false-positive rate of 30.2%. It demonstrated that the SVM-based classifier is effective in mass classification.

Horseshoe lung - a case report with unusual bronchial and pleural anomalies and a proposed new classification

International Nuclear Information System (INIS)

Figa, F.H.; Yoo, S.J.; Burrows, P.E.; Turner-Gomes, S.; Freedom, R.M.

1993-01-01

One case of horseshoe lung with associated scimitar syndrome is presented. Unusual bronchial and pleural anomalies as delineated by CT and plain chest radiographic imaging are described. The presence of bilateal fissures led to a newly proposed classification of horseshoe lung based on pleural anatomy. (orig.)

Horseshoe lung - a case report with unusual bronchial and pleural anomalies and a proposed new classification

Energy Technology Data Exchange (ETDEWEB)

Figa, F H [Dept. of Diagnostic Imaging and Division of Cardiology, Hospital for Sick Children, Toronto, ON (Canada); Yoo, S J; Burrows, P E [Dept. of Diagnostic Imaging and Division of Cardiology, Hospital for Sick Children, Toronto, ON (Canada); Turner-Gomes, S [McMaster Univ. Medical Center, Hamilton, ON (Canada); Freedom, R M [Dept. of Diagnostic Imaging and Division of Cardiology, Hospital for Sick Children, Toronto, ON (Canada)

1993-03-01

One case of horseshoe lung with associated scimitar syndrome is presented. Unusual bronchial and pleural anomalies as delineated by CT and plain chest radiographic imaging are described. The presence of bilateal fissures led to a newly proposed classification of horseshoe lung based on pleural anatomy. (orig.)

Classification of neuropathic pain in cancer patients: A Delphi expert survey report and EAPC/IASP proposal of an algorithm for diagnostic criteria.

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Brunelli, Cinzia; Bennett, Michael I; Kaasa, Stein; Fainsinger, Robin; Sjøgren, Per; Mercadante, Sebastiano; Løhre, Erik T; Caraceni, Augusto

2014-12-01

Neuropathic pain (NP) in cancer patients lacks standards for diagnosis. This study is aimed at reaching consensus on the application of the International Association for the Study of Pain (IASP) special interest group for neuropathic pain (NeuPSIG) criteria to the diagnosis of NP in cancer patients and on the relevance of patient-reported outcome (PRO) descriptors for the screening of NP in this population. An international group of 42 experts was invited to participate in a consensus process through a modified 2-round Internet-based Delphi survey. Relevant topics investigated were: peculiarities of NP in patients with cancer, IASP NeuPSIG diagnostic criteria adaptation and assessment, and standardized PRO assessment for NP screening. Median consensus scores (MED) and interquartile ranges (IQR) were calculated to measure expert consensus after both rounds. Twenty-nine experts answered, and good agreement was found on the statement "the pathophysiology of NP due to cancer can be different from non-cancer NP" (MED=9, IQR=2). Satisfactory consensus was reached for the first 3 NeuPSIG criteria (pain distribution, history, and sensory findings; MEDs⩾8, IQRs⩽3), but not for the fourth one (diagnostic test/imaging; MED=6, IQR=3). Agreement was also reached on clinical examination by soft brush or pin stimulation (MEDs⩾7 and IQRs⩽3) and on the use of PRO descriptors for NP screening (MED=8, IQR=3). Based on the study results, a clinical algorithm for NP diagnostic criteria in cancer patients with pain was proposed. Clinical research on PRO in the screening phase and on the application of the algorithm will be needed to examine their effectiveness in classifying NP in cancer patients. Copyright © 2014 International Association for the Study of Pain. Published by Elsevier B.V. All rights reserved.

Classification of neuropathic pain in cancer patients

DEFF Research Database (Denmark)

Brunelli, Cinzia; Bennett, Michael I; Kaasa, Stein

2014-01-01

and on the relevance of patient-reported outcome (PRO) descriptors for the screening of NP in this population. An international group of 42 experts was invited to participate in a consensus process through a modified 2-round Internet-based Delphi survey. Relevant topics investigated were: peculiarities of NP...... in patients with cancer, IASP NeuPSIG diagnostic criteria adaptation and assessment, and standardized PRO assessment for NP screening. Median consensus scores (MED) and interquartile ranges (IQR) were calculated to measure expert consensus after both rounds. Twenty-nine experts answered, and good agreement...... was proposed. Clinical research on PRO in the screening phase and on the application of the algorithm will be needed to examine their effectiveness in classifying NP in cancer patients....

Borax Stump Treatment for Control of Annosus Root Disease in the Eastside Pine Type Forests of Northeastern California

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John T. Kliejunas

1989-01-01

A historical perspective and description of recent studies on the use of borax to treat pine stumps against infection by Heterobasidion annosum in eastside pine stands of northeastern California are presented. The studies indicate that boraxing of pines in eastside pine stands is an effective means of preventing annosus infection. Data and...

Normed kernel function-based fuzzy possibilistic C-means (NKFPCM) algorithm for high-dimensional breast cancer database classification with feature selection is based on Laplacian Score

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Lestari, A. W.; Rustam, Z.

2017-07-01

In the last decade, breast cancer has become the focus of world attention as this disease is one of the primary leading cause of death for women. Therefore, it is necessary to have the correct precautions and treatment. In previous studies, Fuzzy Kennel K-Medoid algorithm has been used for multi-class data. This paper proposes an algorithm to classify the high dimensional data of breast cancer using Fuzzy Possibilistic C-means (FPCM) and a new method based on clustering analysis using Normed Kernel Function-Based Fuzzy Possibilistic C-Means (NKFPCM). The objective of this paper is to obtain the best accuracy in classification of breast cancer data. In order to improve the accuracy of the two methods, the features candidates are evaluated using feature selection, where Laplacian Score is used. The results show the comparison accuracy and running time of FPCM and NKFPCM with and without feature selection.

Feature selection and classification of MAQC-II breast cancer and multiple myeloma microarray gene expression data.

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Qingzhong Liu

Full Text Available Microarray data has a high dimension of variables but available datasets usually have only a small number of samples, thereby making the study of such datasets interesting and challenging. In the task of analyzing microarray data for the purpose of, e.g., predicting gene-disease association, feature selection is very important because it provides a way to handle the high dimensionality by exploiting information redundancy induced by associations among genetic markers. Judicious feature selection in microarray data analysis can result in significant reduction of cost while maintaining or improving the classification or prediction accuracy of learning machines that are employed to sort out the datasets. In this paper, we propose a gene selection method called Recursive Feature Addition (RFA, which combines supervised learning and statistical similarity measures. We compare our method with the following gene selection methods: Support Vector Machine Recursive Feature Elimination (SVMRFE, Leave-One-Out Calculation Sequential Forward Selection (LOOCSFS, Gradient based Leave-one-out Gene Selection (GLGS. To evaluate the performance of these gene selection methods, we employ several popular learning classifiers on the MicroArray Quality Control phase II on predictive modeling (MAQC-II breast cancer dataset and the MAQC-II multiple myeloma dataset. Experimental results show that gene selection is strictly paired with learning classifier. Overall, our approach outperforms other compared methods. The biological functional analysis based on the MAQC-II breast cancer dataset convinced us to apply our method for phenotype prediction. Additionally, learning classifiers also play important roles in the classification of microarray data and our experimental results indicate that the Nearest Mean Scale Classifier (NMSC is a good choice due to its prediction reliability and its stability across the three performance measurements: Testing accuracy, MCC values, and

RRHGE: A Novel Approach to Classify the Estrogen Receptor Based Breast Cancer Subtypes

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Ashish Saini

2014-01-01

Full Text Available Background. Breast cancer is the most common type of cancer among females with a high mortality rate. It is essential to classify the estrogen receptor based breast cancer subtypes into correct subclasses, so that the right treatments can be applied to lower the mortality rate. Using gene signatures derived from gene interaction networks to classify breast cancers has proven to be more reproducible and can achieve higher classification performance. However, the interactions in the gene interaction network usually contain many false-positive interactions that do not have any biological meanings. Therefore, it is a challenge to incorporate the reliability assessment of interactions when deriving gene signatures from gene interaction networks. How to effectively extract gene signatures from available resources is critical to the success of cancer classification. Methods. We propose a novel method to measure and extract the reliable (biologically true or valid interactions from gene interaction networks and incorporate the extracted reliable gene interactions into our proposed RRHGE algorithm to identify significant gene signatures from microarray gene expression data for classifying ER+ and ER− breast cancer samples. Results. The evaluation on real breast cancer samples showed that our RRHGE algorithm achieved higher classification accuracy than the existing approaches.

Using Variable Precision Rough Set for Selection and Classification of Biological Knowledge Integrated in DNA Gene Expression

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Calvo-Dmgz D.

2012-12-01

Full Text Available DNA microarrays have contributed to the exponential growth of genomic and experimental data in the last decade. This large amount of gene expression data has been used by researchers seeking diagnosis of diseases like cancer using machine learning methods. In turn, explicit biological knowledge about gene functions has also grown tremendously over the last decade. This work integrates explicit biological knowledge, provided as gene sets, into the classication process by means of Variable Precision Rough Set Theory (VPRS. The proposed model is able to highlight which part of the provided biological knowledge has been important for classification. This paper presents a novel model for microarray data classification which is able to incorporate prior biological knowledge in the form of gene sets. Based on this knowledge, we transform the input microarray data into supergenes, and then we apply rough set theory to select the most promising supergenes and to derive a set of easy interpretable classification rules. The proposed model is evaluated over three breast cancer microarrays datasets obtaining successful results compared to classical classification techniques. The experimental results shows that there are not significat differences between our model and classical techniques but it is able to provide a biological-interpretable explanation of how it classifies new samples.

Clinical application of a microfluidic chip for immunocapture and quantification of circulating exosomes to assist breast cancer diagnosis and molecular classification.

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Fang, Shimeng; Tian, Hongzhu; Li, Xiancheng; Jin, Dong; Li, Xiaojie; Kong, Jing; Yang, Chun; Yang, Xuesong; Lu, Yao; Luo, Yong; Lin, Bingcheng; Niu, Weidong; Liu, Tingjiao

2017-01-01

Increasing attention has been attracted by exosomes in blood-based diagnosis because cancer cells release more exosomes in serum than normal cells and these exosomes overexpress a certain number of cancer-related biomarkers. However, capture and biomarker analysis of exosomes for clinical application are technically challenging. In this study, we developed a microfluidic chip for immunocapture and quantification of circulating exosomes from small sample volume and applied this device in clinical study. Circulating EpCAM-positive exosomes were measured in 6 cases breast cancer patients and 3 healthy controls to assist diagnosis. A significant increase in the EpCAM-positive exosome level in these patients was detected, compared to healthy controls. Furthermore, we quantified circulating HER2-positive exosomes in 19 cases of breast cancer patients for molecular classification. We demonstrated that the exosomal HER2 expression levels were almost consistent with that in tumor tissues assessed by immunohistochemical staining. The microfluidic chip might provide a new platform to assist breast cancer diagnosis and molecular classification.

Validation of the prognostic gene portfolio, ClinicoMolecular Triad Classification, using an independent prospective breast cancer cohort and external patient populations

Science.gov (United States)

2014-01-01

Introduction Using genome-wide expression profiles of a prospective training cohort of breast cancer patients, ClinicoMolecular Triad Classification (CMTC) was recently developed to classify breast cancers into three clinically relevant groups to aid treatment decisions. CMTC was found to be both prognostic and predictive in a large external breast cancer cohort in that study. This study serves to validate the reproducibility of CMTC and its prognostic value using independent patient cohorts. Methods An independent internal cohort (n = 284) and a new external cohort (n = 2,181) were used to validate the association of CMTC between clinicopathological factors, 12 known gene signatures, two molecular subtype classifiers, and 19 oncogenic signalling pathway activities, and to reproduce the abilities of CMTC to predict clinical outcomes of breast cancer. In addition, we also updated the outcome data of the original training cohort (n = 147). Results The original training cohort reached a statistically significant difference (p risk groups. Conclusions Both prospective internal cohorts and the independent external cohorts reproduced the triad classification of CMTC and its prognostic significance. CMTC is an independent prognostic predictor, and it outperformed 12 other known prognostic gene signatures, molecular subtype classifications, and all other standard prognostic clinicopathological factors. Our results support further development of CMTC portfolio into a guide for personalized breast cancer treatments. PMID:24996446

International proposal for an acoustic classification scheme for dwellings

DEFF Research Database (Denmark)

Rasmussen, Birgit

2014-01-01

Acoustic classification schemes specify different quality levels for acoustic conditions. Regulations and classification schemes for dwellings typically include criteria for airborne and impact sound insulation, façade sound insulation and service equipment noise. However, although important...... classes, implying also trade barriers. Thus, a harmonized classification scheme would be useful, and the European COST Action TU0901 "Integrating and Harmonizing Sound Insulation Aspects in Sustainable Urban Housing Constructions", running 2009-2013 with members from 32 countries, including three overseas...... for quality of life, information about acoustic conditions is rarely available, neither for new or existing housing. Regulatory acoustic requirements will, if enforced, ensure a corresponding quality for new dwellings, but satisfactory conditions for occupants are not guaranteed. Consequently, several...

Surgical options in benign parotid tumors: a proposal for classification.

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Quer, Miquel; Vander Poorten, Vincent; Takes, Robert P; Silver, Carl E; Boedeker, Carsten C; de Bree, Remco; Rinaldo, Alessandra; Sanabria, Alvaro; Shaha, Ashok R; Pujol, Albert; Zbären, Peter; Ferlito, Alfio

2017-11-01

Different surgical options are currently available for treating benign tumors of the parotid gland, and the discussion on optimal treatment continues despite several meta-analyses. These options include more limited resections (extracapsular dissection, partial lateral parotidectomy) versus more extensive and traditional options (lateral parotid lobectomy, total parotidectomy). Different schools favor one option or another based on their experience, skills and tradition. This review provides a critical analysis of the literature regarding these options. The main limitation of all the studies is the bias of selection for different surgical approaches. For this reason, we propose a staging system that could facilitate clinical decision making and the comparison of results. We propose four categories based on the size of the tumor and its location within the parotid gland. Category I includes tumors up to 3 cm, which are mobile, close to the outer surface and close to the parotid borders. Category II includes deeper tumors up to 3 cm. Category III comprises tumors greater than 3 cm involving two levels of the parotid gland, and category IV tumors are greater than 3 cm and involve more than 2 levels. For each category and for the various pathologic types, a guideline of surgical extent is proposed. The objective of this classification is to facilitate prospective multicentric studies on surgical techniques in the treatment of benign parotid tumors and to enable the comparison of results of different clinical studies.

Evaluation of a 5-tier scheme proposed for classification of sequence variants using bioinformatic and splicing assay data

DEFF Research Database (Denmark)

Walker, Logan C; Whiley, Phillip J; Houdayer, Claude

2013-01-01

BRCA1 and 176 BRCA2 unique variants, from 77 publications. At least six independent reviewers from research and/or clinical settings comprehensively examined splicing assay methods and data reported for 22 variant assays of 21 variants in four publications, and classified the variants using the 5-tier......Splicing assays are commonly undertaken in the clinical setting to assess the clinical relevance of sequence variants in disease predisposition genes. A 5-tier classification system incorporating both bioinformatic and splicing assay information was previously proposed as a method to provide...... of results, and the lack of quantitative data for the aberrant transcripts. We propose suggestions for minimum reporting guidelines for splicing assays, and improvements to the 5-tier splicing classification system to allow future evaluation of its performance as a clinical tool....

Classification of Osteogenesis Imperfecta revisited

NARCIS (Netherlands)

van Dijk, F. S.; Pals, G.; van Rijn, R. R.; Nikkels, P. G. J.; Cobben, J. M.

2010-01-01

In 1979 Sillence proposed a classification of Osteogenesis Imperfecta (OI) in OI types I, II, III and IV. In 2004 and 2007 this classification was expanded with OI types V-VIII because of distinct clinical features and/or different causative gene mutations. We propose a revised classification of OI

On the appearance of acetylcholine receptors in denervated rat diaphragm, and its dependence on nerve stump length

International Nuclear Information System (INIS)

Uchitel, O.; Robbins, N.

1978-01-01

Acetylcholine (ACh) sensitivity and extrajunctional receptor distribution of the rat diaphragm were closely monitored during the early period following denervation. Both contracture in response to 10 μg/ml of ACh and extrajunctional binding of [ 125 I]alpha-bungarotoxin ([ 125 I]α-BTX) were first detectable 30 h after cutting the phrenic nerve in the thorax. If the nerve were cut more proximally, leaving a 3.5 cm distal nerve stump, the same level of ACh contracture and [ 125 I]α-BTX binding did not appear until 40 h after operation. This 10-h delay was far longer than the 3-h delay in transmission failure reportedly dependent on stump length. The earliest detectable extrajunctional [ 125 I]α-BTX binding appeared throughout the entire muscle fiber, and was not localized to the endplate region as would be expected if degeneration in the nerve terminal induced new receptors. However, later significant increases in [ 125 I]α-BTX binding at the endplate region could have resulted from such degeneration. All these results are consistent with neurotrophic regulation of muscle ACh receptors, working via a mechanism involving axonal transport. (Auth.)

High complication rate after low anterior resection for mid and high rectal cancer; results of a population-based study

NARCIS (Netherlands)

Bakker, I. S.; Snijders, H. S.; Wouters, M. W.; Havenga, K.; Tollenaar, R. A. E. M.; Wiggers, T.; Dekker, J. W. T.

Background: Surgical resection is the cornerstone of treatment for rectal cancer patients. Treatment options consist of a primary anastomosis, anastomosis with defunctioning stoma or end-colostomy with closure of the distal rectal stump. This study aimed to compare postoperative outcome of these

The k-Language Classification, a Proposed New Theory for Image Classification and Clustering at Pixel Level

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Alwi Aslan

2014-03-01

Full Text Available This theory attempted to explore the possibility of using regular language further in image analysis, departing from the use of string to represent the region in the image. But we are not trying to show an alternative idea about how to generate a string region, where there are many different ways how the image or region produces strings representing, in this paper we propose a way how to generate regular language or group of languages which performs both classify the set of strings generated by a group of a number of image regions. Researchers began by showing a proof that there is always a regular language that accepts a set of strings that produced the image, and then use the language to perform the classification. Research then expanded to the pixel level, on whether the regular language can be used for clustering pixels in the image, the researchers propose a systematic solution of this question. As a tool used to explore regular language is deterministic finite automata. On the end part before conclusion of this paper, we add revision version of this theory. There is another point of view to revision version, added for make this method more precision and more powerfull from before.

FEATURE EXTRACTION BASED WAVELET TRANSFORM IN BREAST CANCER DIAGNOSIS USING FUZZY AND NON-FUZZY CLASSIFICATION

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Pelin GORGEL

2013-01-01

Full Text Available This study helps to provide a second eye to the expert radiologists for the classification of manually extracted breast masses taken from 60 digital mammıgrams. These mammograms have been acquired from Istanbul University Faculty of Medicine Hospital and have 78 masses. The diagnosis is implemented with pre-processing by using feature extraction based Fast Wavelet Transform (FWT. Afterwards Adaptive Neuro-Fuzzy Inference System (ANFIS based fuzzy subtractive clustering and Support Vector Machines (SVM methods are used for the classification. It is a comparative study which uses these methods respectively. According to the results of the study, ANFIS based subtractive clustering produces ??% while SVM produces ??% accuracy in malignant-benign classification. The results demonstrate that the developed system could help the radiologists for a true diagnosis and decrease the number of the missing cancerous regions or unnecessary biopsies.

Multiplatform analysis of 12 cancer types reveals molecular classification within and across tissues of origin

DEFF Research Database (Denmark)

Hoadley, Katherine A; Yau, Christina; Wolf, Denise M

2014-01-01

Recent genomic analyses of pathologically defined tumor types identify "within-a-tissue" disease subtypes. However, the extent to which genomic signatures are shared across tissues is still unclear. We performed an integrative analysis using five genome-wide platforms and one proteomic platform...... on 3,527 specimens from 12 cancer types, revealing a unified classification into 11 major subtypes. Five subtypes were nearly identical to their tissue-of-origin counterparts, but several distinct cancer types were found to converge into common subtypes. Lung squamous, head and neck, and a subset...

Body mass index: different nutritional status according to WHO, OPAS and Lipschitz classifications in gastrointestinal cancer patients.

Science.gov (United States)

Barao, Katia; Forones, Nora Manoukian

2012-01-01

The body mass index (BMI) is the most common marker used on diagnoses of the nutritional status. The great advantage of this index is the easy way to measure, the low cost, the good correlation with the fat mass and the association to morbidity and mortality. To compare the BMI differences according to the WHO, OPAS and Lipschitz classification. A prospective study on 352 patients with esophageal, gastric or colorectal cancer was done. The BMI was calculated and analyzed by the classification of WHO, Lipschitz and OPAS. The mean age was 62.1 ± 12.4 years and 59% of them had more than 59 years. The BMI had not difference between the genders in patients cancer had more than 65 years. A different cut off must be used for this patients, because undernourished patients may be wrongly considered well nourished.

Application of texture analysis method for mammogram density classification

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Nithya, R.; Santhi, B.

2017-07-01

Mammographic density is considered a major risk factor for developing breast cancer. This paper proposes an automated approach to classify breast tissue types in digital mammogram. The main objective of the proposed Computer-Aided Diagnosis (CAD) system is to investigate various feature extraction methods and classifiers to improve the diagnostic accuracy in mammogram density classification. Texture analysis methods are used to extract the features from the mammogram. Texture features are extracted by using histogram, Gray Level Co-Occurrence Matrix (GLCM), Gray Level Run Length Matrix (GLRLM), Gray Level Difference Matrix (GLDM), Local Binary Pattern (LBP), Entropy, Discrete Wavelet Transform (DWT), Wavelet Packet Transform (WPT), Gabor transform and trace transform. These extracted features are selected using Analysis of Variance (ANOVA). The features selected by ANOVA are fed into the classifiers to characterize the mammogram into two-class (fatty/dense) and three-class (fatty/glandular/dense) breast density classification. This work has been carried out by using the mini-Mammographic Image Analysis Society (MIAS) database. Five classifiers are employed namely, Artificial Neural Network (ANN), Linear Discriminant Analysis (LDA), Naive Bayes (NB), K-Nearest Neighbor (KNN), and Support Vector Machine (SVM). Experimental results show that ANN provides better performance than LDA, NB, KNN and SVM classifiers. The proposed methodology has achieved 97.5% accuracy for three-class and 99.37% for two-class density classification.

Herbicidas e danos físicos em tocos de teca para controle de brotos após o desbaste Herbicides and physical damages in teak stumps to control of sprouts after thinning

Directory of Open Access Journals (Sweden)

Sidney Fernando Caldeira

2012-10-01

Full Text Available Tocos de árvores desbastadas de Tectona grandis apresentam rebrota intensa que compete com as árvores remanescentes. O objetivo deste trabalho foi avaliar a eficácia da aplicação isolada ou combinada de diferentes concentrações dos herbicidas picloram e triclopyr, associados ou não à aplicação de danos físicos, no controle dessas brotações. Em um povoamento com quatro anos de idade, os tocos foram tratados imediatamente após o desbaste. Em outro povoamento com seis anos, foram tratadas as brotações presentes nos tocos desbastados no ano anterior. Foi registrada a porcentagem de tocos mortos, o número de brotações por toco e as respectivas alturas. No primeiro ensaio, a aplicação combinada de picloram a 0,48% com triclopyr a 0,96%, associada a 20 rachas com machado matou todos os tocos. No segundo ensaio, a maior eficácia, 21,7%, foi registrada com roçada prévia das brotações e a aplicação de picloram a 0,96%. Após o desbaste, a aplicação isolada de picloram ou combinada com triclopyr associada ou não aos danos físicos é eficiente para controlar os brotos de teca. A aplicação nas rebrotas de tocos desbastados no ano anterior apresenta alguma eficiência, mas com menor percentual de tocos mortos em relação à aplicação após o desbaste.The stumps of thinning trees of Tectona grandis L.f. present intense sprouts that compete with the remaining trees. The efficacy of the control of sprouts with the herbicides picloram and triclopyr, associated or no it applications of physical damages, were evaluated. Immediately after thinning, in plantation with four years old, the stumps were treated, and in other plantation, with age of six, the sprouts of stumps thinned in the previous year, were treated. The percentage of died stumps, the number of sprouts by stump and the respective heights were registered. In the first trial, the combined application of picloram at 0.48% with triclopyr at 0.96%, associated a 20 cracks

Unsupervised Classification Using Immune Algorithm

OpenAIRE

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

2012-01-01

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

Laparoscopic completion radical cholecystectomy for T2 gallbladder cancer.

Science.gov (United States)

Gumbs, Andrew A; Hoffman, John P

2010-12-01

The role of minimally invasive surgery in the surgical management of gallbladder cancer is a matter of controversy. Because of the authors' growing experience with laparoscopic liver and pancreatic surgery, they have begun offering patients laparoscopic completion partial hepatectomies of the gallbladder bed with laparoscopic hepatoduodenal lymphadenectomy. The video shows the steps needed to perform laparoscopic resection of the residual gallbladder bed, the hepatoduodenal lymph node nodes, and the residual cystic duct stump in a setting with a positive cystic stump margin. The skin and fascia around the previous extraction site are resected, and this site is used for specimen retrieval during the second operation. To date, three patients have undergone laparoscopic radical cholecystectomy with hepatoduodenal lymph node dissection for gallbladder cancer. The average number of lymph nodes retrieved was 3 (range, 1-6), and the average estimated blood loss was 117 ml (range, 50-200 ml). The average operative time was 227 min (range, 120-360 min), and the average hospital length of stay was 4 days (range, 3-5 days). No morbidity or mortality was observed during 90 days of follow-up for each patient. Although controversy exists as to the best surgical approach for gallbladder cancer diagnosed after routine laparoscopic cholecystectomy, the minimally invasive approach seems feasible and safe, even after previous hepatobiliary surgery. If the previous extraction site cannot be ascertained, all port sites can be excised locally. Larger studies are needed to determine whether the minimally invasive approach to postoperatively diagnosed early-stage gallbladder cancer has any drawbacks.

Latent classification models

DEFF Research Database (Denmark)

Langseth, Helge; Nielsen, Thomas Dyhre

2005-01-01

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

On the classification techniques in data mining for microarray data classification

Science.gov (United States)

Aydadenta, Husna; Adiwijaya

2018-03-01

Cancer is one of the deadly diseases, according to data from WHO by 2015 there are 8.8 million more deaths caused by cancer, and this will increase every year if not resolved earlier. Microarray data has become one of the most popular cancer-identification studies in the field of health, since microarray data can be used to look at levels of gene expression in certain cell samples that serve to analyze thousands of genes simultaneously. By using data mining technique, we can classify the sample of microarray data thus it can be identified with cancer or not. In this paper we will discuss some research using some data mining techniques using microarray data, such as Support Vector Machine (SVM), Artificial Neural Network (ANN), Naive Bayes, k-Nearest Neighbor (kNN), and C4.5, and simulation of Random Forest algorithm with technique of reduction dimension using Relief. The result of this paper show performance measure (accuracy) from classification algorithm (SVM, ANN, Naive Bayes, kNN, C4.5, and Random Forets).The results in this paper show the accuracy of Random Forest algorithm higher than other classification algorithms (Support Vector Machine (SVM), Artificial Neural Network (ANN), Naive Bayes, k-Nearest Neighbor (kNN), and C4.5). It is hoped that this paper can provide some information about the speed, accuracy, performance and computational cost generated from each Data Mining Classification Technique based on microarray data.

Clinical classification of cancer cachexia: phenotypic correlates in human skeletal muscle.

Directory of Open Access Journals (Sweden)

Neil Johns

Full Text Available BACKGROUND: Cachexia affects the majority of patients with advanced cancer and is associated with a reduction in treatment tolerance, response to therapy, and duration of survival. One impediment towards the effective treatment of cachexia is a validated classification system. METHODS: 41 patients with resectable upper gastrointestinal (GI or pancreatic cancer underwent characterisation for cachexia based on weight-loss (WL and/or low muscularity (LM. Four diagnostic criteria were used >5%WL, >10%WL, LM, and LM+>2%WL. All patients underwent biopsy of the rectus muscle. Analysis included immunohistochemistry for fibre size and type, protein and nucleic acid concentration, Western blots for markers of autophagy, SMAD signalling, and inflammation. FINDINGS: Compared with non-cachectic cancer patients, patients with LM or LM+>2%WL, mean muscle fibre diameter was reduced by about 25% (p = 0.02 and p = 0.001 respectively. No significant difference in fibre diameter was observed if patients had WL alone. Regardless of classification, there was no difference in fibre number or proportion of fibre type across all myosin heavy chain isoforms. Mean muscle protein content was reduced and the ratio of RNA/DNA decreased in patients with either >5%WL or LM+>2%WL. Compared with non-cachectic patients, SMAD3 protein levels were increased in patients with >5%WL (p = 0.022 and with >10%WL, beclin (p = 0.05 and ATG5 (p = 0.01 protein levels were increased. There were no differences in phospho-NFkB or phospho-STAT3 levels across any of the groups. CONCLUSION: Muscle fibre size, biochemical composition and pathway phenotype can vary according to whether the diagnostic criteria for cachexia are based on weight loss alone, a measure of low muscularity alone or a combination of the two. For intervention trials where the primary end-point is a change in muscle mass or function, use of combined diagnostic criteria may allow identification of a more

Hand eczema classification

DEFF Research Database (Denmark)

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

2008-01-01

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

Long-term Evaluation of a Modified Double Staple Technique for Low Anterior Resection.

Science.gov (United States)

Illuminati, G; Carboni, F; Ceccanei, G; Pacilè, M A; Pizzardi, G; Palumbo, P; Vietri, F

2014-01-01

When performing low anterior resection for rectal cancer with the double staple technique, -closing the rectum with a linear stapler in the abdomen can be challenging, especially when dealing with a narrow pelvis. For such instances we proposed to modify this technique by pulling the rectal stump through the anus, doing an extra-anal resection of the tumor and linear suture of the rectal stump, before performing a standard, stapled colorectal anastomosis. The purpose of this study was to assess the adequacy of this modification of the double staple technique. Retrospective review of 108 patients undergoing a stapled, low colorectal or coloanal anastomosis, after -eversion, extra-anal resection of the tumor and linear closure of the rectal stump for colorectal cancer, from January 1990 to December 2012. Operative mortality was 0.9%. Fourteen patients (13%) presented early, surgery-related complications -consisting of 7 anastomotic leaks, 5 wound infections, 1 ureteral lesion, and 1 peristomal abscess. Late complications related to surgery included 5 incisional hernias (4.6%), 4 anastomotic strictures (3.7%), 4 neurogenic bladders (3.7%) and 2 fecal incontinences (1.8%). The incidence of local disease recurrence was 10%. Surgical and oncological results validate the proposed modification of the double staple technique, when facing difficulties in suturing the rectum from the abdomen. Copyright© Acta Chirurgica Belgica.

Thermogram breast cancer prediction approach based on Neutrosophic sets and fuzzy c-means algorithm.

Science.gov (United States)

Gaber, Tarek; Ismail, Gehad; Anter, Ahmed; Soliman, Mona; Ali, Mona; Semary, Noura; Hassanien, Aboul Ella; Snasel, Vaclav

2015-08-01

The early detection of breast cancer makes many women survive. In this paper, a CAD system classifying breast cancer thermograms to normal and abnormal is proposed. This approach consists of two main phases: automatic segmentation and classification. For the former phase, an improved segmentation approach based on both Neutrosophic sets (NS) and optimized Fast Fuzzy c-mean (F-FCM) algorithm was proposed. Also, post-segmentation process was suggested to segment breast parenchyma (i.e. ROI) from thermogram images. For the classification, different kernel functions of the Support Vector Machine (SVM) were used to classify breast parenchyma into normal or abnormal cases. Using benchmark database, the proposed CAD system was evaluated based on precision, recall, and accuracy as well as a comparison with related work. The experimental results showed that our system would be a very promising step toward automatic diagnosis of breast cancer using thermograms as the accuracy reached 100%.

Annual Research Review: The Nature and Classification of Reading Disorders--A Commentary on Proposals for DSM-5

Science.gov (United States)

Snowling, Margaret J.; Hulme, Charles

2012-01-01

This article reviews our understanding of reading disorders in children and relates it to current proposals for their classification in DSM-5. There are two different, commonly occurring, forms of reading disorder in children which arise from different underlying language difficulties. Dyslexia (as defined in DSM-5), or decoding difficulty, refers…

Mastectomy or breast conserving surgery? Factors affecting type of surgical treatment for breast cancer – a classification tree approach

International Nuclear Information System (INIS)

Martin, Michael A; Meyricke, Ramona; O'Neill, Terry; Roberts, Steven

2006-01-01

A critical choice facing breast cancer patients is which surgical treatment – mastectomy or breast conserving surgery (BCS) – is most appropriate. Several studies have investigated factors that impact the type of surgery chosen, identifying features such as place of residence, age at diagnosis, tumor size, socio-economic and racial/ethnic elements as relevant. Such assessment of 'propensity' is important in understanding issues such as a reported under-utilisation of BCS among women for whom such treatment was not contraindicated. Using Western Australian (WA) data, we further examine the factors associated with the type of surgical treatment for breast cancer using a classification tree approach. This approach deals naturally with complicated interactions between factors, and so allows flexible and interpretable models for treatment choice to be built that add to the current understanding of this complex decision process. Data was extracted from the WA Cancer Registry on women diagnosed with breast cancer in WA from 1990 to 2000. Subjects' treatment preferences were predicted from covariates using both classification trees and logistic regression. Tumor size was the primary determinant of patient choice, subjects with tumors smaller than 20 mm in diameter preferring BCS. For subjects with tumors greater than 20 mm in diameter factors such as patient age, nodal status, and tumor histology become relevant as predictors of patient choice. Classification trees perform as well as logistic regression for predicting patient choice, but are much easier to interpret for clinical use. The selected tree can inform clinicians' advice to patients

Proposed Core Competencies and Empirical Validation Procedure in Competency Modeling: Confirmation and Classification.

Science.gov (United States)

Baczyńska, Anna K; Rowiński, Tomasz; Cybis, Natalia

2016-01-01

Competency models provide insight into key skills which are common to many positions in an organization. Moreover, there is a range of competencies that is used by many companies. Researchers have developed core competency terminology to underline their cross-organizational value. The article presents a theoretical model of core competencies consisting of two main higher-order competencies called performance and entrepreneurship. Each of them consists of three elements: the performance competency includes cooperation, organization of work and goal orientation, while entrepreneurship includes innovativeness, calculated risk-taking and pro-activeness. However, there is lack of empirical validation of competency concepts in organizations and this would seem crucial for obtaining reliable results from organizational research. We propose a two-step empirical validation procedure: (1) confirmation factor analysis, and (2) classification of employees. The sample consisted of 636 respondents (M = 44.5; SD = 15.1). Participants were administered a questionnaire developed for the study purpose. The reliability, measured by Cronbach's alpha, ranged from 0.60 to 0.83 for six scales. Next, we tested the model using a confirmatory factor analysis. The two separate, single models of performance and entrepreneurial orientations fit quite well to the data, while a complex model based on the two single concepts needs further research. In the classification of employees based on the two higher order competencies we obtained four main groups of employees. Their profiles relate to those found in the literature, including so-called niche finders and top performers. Some proposal for organizations is discussed.

Umbilical Cord Management and Stump Care in Normal Childbirth in Slovenian and Croatian Maternity Hospitals.

Science.gov (United States)

Mivšek, Ana Polona; Petročnik, Petra; Skubic, Metka; Škodič Zakšek, Teja; Jug Došler, Anita

2017-12-01

The aim was to investigate first-care procedures for the newborn's umbilical cord at maternity hospitals in Slovenia and Croatia. The study was based on an empirical survey research approach and quantitative research paradigms and included all Slovenian (n=14) and all Croatian (n=35) maternity hospitals. Leaders of midwifery team of 14 Slovenian and 35 Croatian labor wards were invited to participate. The study was conducted in 2013, with 67% of Slovenian and 66% of Croatian maternity hospitals having responded. A causal and non-experimental method of empirical research was used. The research instrument was a questionnaire. Descriptive statistics was used on data analysis. The independence hypothesis was tested with the χ2-test or Kullback 2Î-test. A vast ma-jority of study wards employed delayed umbilical cord clamping, i.e. clamping the cord after pulsa-tion had ceased. Only 10% of Slovenian in comparison with 36.4% of Croatian maternity hospitals practiced dry cord care. Others applied disinfectant on the cord, in Slovenia most frequently 6% po-tassium permanganate, and in Croatia a combination of octenidine and phenoxyethanol. Most Croa-tian -maternity wards (95.7%) still covered the stump, while it was not regular practice in Slovenia. The authors estimate that the prevailing Slovenian and Croatian practices in regard to cord clamping are in accordance with the evidence, while improvements could be made regarding stump care, since dry cord care is the recommended method.

The Frequent Unusual Headache Syndromes: A Proposed Classification Based on Lifetime Prevalence.

Science.gov (United States)

Valença, Marcelo M; de Oliveira, Daniella A

2016-01-01

There is no agreement on a single cutoff point or prevalence for regarding a given disease as rare. The concept of what is a rare headache disorder is even less clear and the spectrum from a very frequent, frequent, occasional to rare headache syndrome is yet to be established. An attempt has been made to estimate the lifetime prevalence of each of the headache subtypes classified in the ICHD-II. Using the ICHD-II, 199 different headache subtypes were identified. The following classification was made according to the estimated lifetime prevalence of each headache disorder: very frequent (prevalence >10%); frequent (between 1 and 10%); occasional (between 0.07 and 1%); and unusual or rare (headache disorders, 7/199 (4%) as very frequent, 9/199 (5%) as frequent, and 29/199 (15%) as occasional forms of headache disorder. The unusual headache syndromes do not appear to be as infrequent in clinical practice as has been generally believed. About three-fourths of the classified headache disorders found in the ICHD-II can be considered as rare. This narrative review article may be regarded as an introduction to the concept of unusual headaches and a proposed classification of all headaches (at least those listed in the ICHD-II). © 2015 American Headache Society.

Restaging and Survival Analysis of 4036 Ovarian Cancer Patients According to the 2013 FIGO Classification for Ovarian, Fallopian Tube, and Primary Peritoneal Cancer

DEFF Research Database (Denmark)

Rosendahl, Mikkel; Høgdall, Claus Kim; Mosgaard, Berit Jul

2016-01-01

OBJECTIVE: With the 2013 International Federation of Gynecology and Obstetrics (FIGO) staging for ovarian, fallopian tube, and primary peritoneal cancer, the number of substages changed from 10 to 14. Any classification of a malignancy should easily assign patients to prognostic groups, refer....... MATERIALS AND METHODS: Demographic, surgical, histological, and survival data from 4036 ovarian cancer patients were used in the analysis. Five-year survival rates (5YSR) and hazard ratios for the old and revised FIGO staging were calculated using Kaplan-Meier curves and Cox regression. RESULTS: A total...

Radon classification of building ground

International Nuclear Information System (INIS)

Slunga, E.

1988-01-01

The Laboratories of Building Technology and Soil Mechanics and Foundation Engineering at the Helsinki University of Technology in cooperation with The Ministry of the Environment have proposed a radon classification for building ground. The proposed classification is based on the radon concentration in soil pores and on the permeability of the foundation soil. The classification includes four radon classes: negligible, normal, high and very high. Depending on the radon class the radon-technical solution for structures is chosen. It is proposed that the classification be done in general terms in connection with the site investigations for the planning of land use and in more detail in connection with the site investigations for an individual house. (author)

Video genre classification using multimodal features

Science.gov (United States)

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

2003-12-01

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

Traumatic subarachnoid pleural fistula in children: case report, algorithm and classification proposal

Directory of Open Access Journals (Sweden)

Moscote-Salazar Luis Rafael

2016-06-01

Full Text Available Subarachnoid pleural fistulas are rare. They have been described as complications of thoracic surgery, penetrating injuries and spinal surgery, among others. We present the case of a 3-year-old female child, who suffer spinal cord trauma secondary to a car accident, developing a posterior subarachnoid pleural fistula. To our knowledge this is the first reported case of a pediatric patient with subarachnoid pleural fistula resulting from closed trauma, requiring intensive multimodal management. We also present a management algorithm and a proposed classification. The diagnosis of this pathology is difficult when not associated with neurological deficit. A high degree of suspicion, multidisciplinary management and timely surgical intervention allow optimal management.

Clinical significance of combined detection of CYFRA21-1, NSE and CEA in classification and staging of patients with lung cancer

International Nuclear Information System (INIS)

Hu He; Li Yanhua; Liang Weida; Zhang Qin

2011-01-01

To explore clinical value of combined detection of CYFRA21-1, NSE and CEA in classification and staging of patients with lung cancer, the CYFRA21-1, NSE and CEA levels in pleural effusion in 330 patients with lung cancer and in 43 patients with benign were detected by the electrochemiluminescence. The results showed that CYFRA21-1, NSE and CEA levels in pleural effusion in patients with lung cancer group were significantly higher than that of in benign group (P<0.01). The positive rate of tumor markers in different pathological type lung cancer were different,which CYFRA21-1 positive rate in squamous cell cancer group was highest with 65.5%; CEA positive rate in glands cancer group was supreme with 65.0%; the NSE positive rate in differentiation cancer group was highest with 79.5%. The positive rate in three markers combined detection was higher than that in one item detection. The tumor marker levels in lung cancer were positively related with clinical staging. The higher of tumor marker levels and the more late of clinical staging, and the clinical III∼IV period was obviously higher than that I∼II period (P<0.05). The combined detection of CYFRA21-1, NSE and CEA may enhance the positive rate in lung cancer detection, and may have significant clinical value in the classification and staging of patients with lung cancer. (authors)

Mammogram classification scheme using 2D-discrete wavelet and local binary pattern for detection of breast cancer

Science.gov (United States)

Adi Putra, Januar

2018-04-01

In this paper, we propose a new mammogram classification scheme to classify the breast tissues as normal or abnormal. Feature matrix is generated using Local Binary Pattern to all the detailed coefficients from 2D-DWT of the region of interest (ROI) of a mammogram. Feature selection is done by selecting the relevant features that affect the classification. Feature selection is used to reduce the dimensionality of data and features that are not relevant, in this paper the F-test and Ttest will be performed to the results of the feature extraction dataset to reduce and select the relevant feature. The best features are used in a Neural Network classifier for classification. In this research we use MIAS and DDSM database. In addition to the suggested scheme, the competent schemes are also simulated for comparative analysis. It is observed that the proposed scheme has a better say with respect to accuracy, specificity and sensitivity. Based on experiments, the performance of the proposed scheme can produce high accuracy that is 92.71%, while the lowest accuracy obtained is 77.08%.

The correlation study of radiological findings with pathological classification of superficial depressed (IIc type) early gastric cancer

International Nuclear Information System (INIS)

Liu Linxiang; Deng Bingxing; Liu Yujin; Iinuma, G.; Moriyama, N.

2007-01-01

Objective: To investigate the relations between radiological findings and pathological classification of superficial depressed (II c type) early gastric cancer. Methods: Radiological features in subtonic double contrast barium examination and the endoscopic pictures of early gastric cancer compared with the global pathological specimens and micro-pathological features were prospectively studied. Combined with the gastric endoscopic pictures, the sharpness of margin of the lesions, the changes of converging mucosal folds and the changes of the depressed surface on the film of double contrast barium examination were analyzed. The correlation between the radiological features and histological classification of gastric cancer including well differentiated tubular adenocarcinoma (tub1), moderately differentiated tubular adenocarcinoma (tub2), poorly differentiated adenocarcinoma (por) and signet-ring cell carcinoma (sig) were studied. Results: In 102 cases of II c type early gastric cancer, there were tub1 27 cases, tub2 11, por 26 and sig 38 cases histologically. The margin of the depressed lesions of tubl (24 cases) and tub2 (9 cases) cancers were mostly unsharply demarcated or with fine spicular border, while the margin of lesions of por(15 cases) and sig(31 cases) were mostly clearly and sharply demarcated, with statistical significance (P<0.01). The depressed surface of tub1 and tub2 lesions (17 cases) revealed little unevenness, sometimes with evenly granulations, single nodule and scar-like depression, while that of por and sig lesions (41 cases) manifested as nodules of varying sizes, with statistical significance (P<0.01). Conclusion: The radiological findings of superficial depressed early gastric cancer in different histological types were different, the possible histological type could be speculated according to the radiological findings of the lesions. (authors)

Farmers prevailing perception profiles regarding GM crops: A classification proposal.

Science.gov (United States)

Almeida, Carla; Massarani, Luisa

2018-04-01

Genetically modified organisms have been at the centre of a major public controversy, involving different interests and actors. While much attention has been devoted to consumer views on genetically modified food, there have been few attempts to understand the perceptions of genetically modified technology among farmers. By investigating perceptions of genetically modified organisms among Brazilian farmers, we intend to contribute towards filling this gap and thereby add the views of this stakeholder group to the genetically modified debate. A comparative analysis of our data and data from other studies indicate there is a complex variety of views on genetically modified organisms among farmers. Despite this diversity, we found variations in such views occur within limited parameters, concerned principally with expectations or concrete experiences regarding the advantages of genetically modified crops, perceptions of risks associated with them, and ethical questions they raise. We then propose a classification of prevailing profiles to represent the spectrum of perceptions of genetically modified organisms among farmers.

Classification with support hyperplanes

NARCIS (Netherlands)

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

2006-01-01

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

Comparison of Computational Algorithms for the Classification of Liver Cancer using SELDI Mass Spectrometry: A Case Study

Directory of Open Access Journals (Sweden)

Robert J Hickey

2007-01-01

Full Text Available Introduction: As an alternative to DNA microarrays, mass spectrometry based analysis of proteomic patterns has shown great potential in cancer diagnosis. The ultimate application of this technique in clinical settings relies on the advancement of the technology itself and the maturity of the computational tools used to analyze the data. A number of computational algorithms constructed on different principles are available for the classification of disease status based on proteomic patterns. Nevertheless, few studies have addressed the difference in the performance of these approaches. In this report, we describe a comparative case study on the classification accuracy of hepatocellular carcinoma based on the serum proteomic pattern generated from a Surface Enhanced Laser Desorption/Ionization (SELDI mass spectrometer.Methods: Nine supervised classifi cation algorithms are implemented in R software and compared for the classification accuracy.Results: We found that the support vector machine with radial function is preferable as a tool for classification of hepatocellular carcinoma using features in SELDI mass spectra. Among the rest of the methods, random forest and prediction analysis of microarrays have better performance. A permutation-based technique reveals that the support vector machine with a radial function seems intrinsically superior in learning from the training data since it has a lower prediction error than others when there is essentially no differential signal. On the other hand, the performance of the random forest and prediction analysis of microarrays rely on their capability of capturing the signals with substantial differentiation between groups.Conclusions: Our finding is similar to a previous study, where classification methods based on the Matrix Assisted Laser Desorption/Ionization (MALDI mass spectrometry are compared for the prediction accuracy of ovarian cancer. The support vector machine, random forest and prediction

WHO/ISUP classification of the urothelial tumors of the urinary bladder

Directory of Open Access Journals (Sweden)

Zdenka Ovčak

2005-09-01

Full Text Available Background: The authors present the current classification of urothelial neoplasms of the urinary bladder. The classification of urothelial tumors of the urinary bladder of 1973 was despite some imperfection relatively successfuly used for more than thirty years. The three grade classification of papillary urothelial tumors without invasion has been based on evaluation of variations in architecture of covering epithelium and tumor cell anaplasia. As reccomended by the International Society of Urological Pathologists (ISUP, the World Health Organisation (WHO accepted the new WHO/ ISUP classification in 1998 that was revised in 2002 and finally published in 2004. With intention to avoid unnecessary diagnosis of cancer in patients having papillary urothelial tumors with rare invasive or metastastatic growth, this classification introduced a new entity, the papillary urothelial neoplasia of low malignant potential (PUNLMP. The additional change in classification was the division of invasive urothelial neoplasms only to low and high grade urothelial carcinomas.Conclusions: The authors’ opinion is that although the old classification is not recommended for use anymore the new one is not solving the elementary reproaches to previous classification such as terminological unsuitability and insufficient scientific reasoning. Our proposed solution in classification of papillary urothelial neoplasms would be the application of criteria analogous to that used in diagnostics of papillary noninvasive tumors of the head and neck or alimentary tract.

Initiative For Thyroid Cancer Diagnosis: Decision Support System For Anaplast Thyroid Cancer

Directory of Open Access Journals (Sweden)

Jamil Ahmed Chandio

2017-12-01

Full Text Available Due to the high level exposure of biomedical image analysis, Medical image mining has become one of the well-established research area(s of machine learning. AI (Artificial Intelligence techniques have been vastly used to solve the complex classification problems of thyroid cancer. Since the persistence of copycat chromatin properties and unavailability of nuclei measurement techniques, it is really problem for doctors to determine the initial phases of nuclei enlargement and to assess the early changes of chromatin distribution. For example involvement of multiple transparent overlapping of nuclei may become the cause of confusion to infer the growth pattern of nuclei variations. Un-decidable nuclei eccentric properties may become one of the leading causes for misdiagnosis in Anaplast cancers. In-order to mitigate all above stated problems this paper proposes a novel methodology so called “Decision Support System for Anaplast Thyroid Cancer” and it proposes a medical data preparation algorithm AD (Analpast_Cancers which helps to select the appropriate features of Anaplast cancers such as (1 enlargement of nuclei, (2 persistence of irregularity in nuclei and existence of hyper chromatin. Proposed methodology comprises over four major layers, first layer deals with the noise reduction, detection of nuclei edges and object clusters. Second layer selects the features of object of interest such as nuclei enlargement, irregularity and hyper chromatin. Third layer constructs the decision model to extract the hidden patterns of disease associated variables and final layer evaluates the performance evaluation by using confusion matrix, precision and recall measures. The overall classification accuracy is measured about 97.2% with 10-k fold cross validation.

Gene selection and classification for cancer microarray data based on machine learning and similarity measures

Directory of Open Access Journals (Sweden)

Liu Qingzhong

2011-12-01

Full Text Available Abstract Background Microarray data have a high dimension of variables and a small sample size. In microarray data analyses, two important issues are how to choose genes, which provide reliable and good prediction for disease status, and how to determine the final gene set that is best for classification. Associations among genetic markers mean one can exploit information redundancy to potentially reduce classification cost in terms of time and money. Results To deal with redundant information and improve classification, we propose a gene selection method, Recursive Feature Addition, which combines supervised learning and statistical similarity measures. To determine the final optimal gene set for prediction and classification, we propose an algorithm, Lagging Prediction Peephole Optimization. By using six benchmark microarray gene expression data sets, we compared Recursive Feature Addition with recently developed gene selection methods: Support Vector Machine Recursive Feature Elimination, Leave-One-Out Calculation Sequential Forward Selection and several others. Conclusions On average, with the use of popular learning machines including Nearest Mean Scaled Classifier, Support Vector Machine, Naive Bayes Classifier and Random Forest, Recursive Feature Addition outperformed other methods. Our studies also showed that Lagging Prediction Peephole Optimization is superior to random strategy; Recursive Feature Addition with Lagging Prediction Peephole Optimization obtained better testing accuracies than the gene selection method varSelRF.

Chaotic particle swarm optimization with mutation for classification.

Science.gov (United States)

Assarzadeh, Zahra; Naghsh-Nilchi, Ahmad Reza

2015-01-01

In this paper, a chaotic particle swarm optimization with mutation-based classifier particle swarm optimization is proposed to classify patterns of different classes in the feature space. The introduced mutation operators and chaotic sequences allows us to overcome the problem of early convergence into a local minima associated with particle swarm optimization algorithms. That is, the mutation operator sharpens the convergence and it tunes the best possible solution. Furthermore, to remove the irrelevant data and reduce the dimensionality of medical datasets, a feature selection approach using binary version of the proposed particle swarm optimization is introduced. In order to demonstrate the effectiveness of our proposed classifier, mutation-based classifier particle swarm optimization, it is checked out with three sets of data classifications namely, Wisconsin diagnostic breast cancer, Wisconsin breast cancer and heart-statlog, with different feature vector dimensions. The proposed algorithm is compared with different classifier algorithms including k-nearest neighbor, as a conventional classifier, particle swarm-classifier, genetic algorithm, and Imperialist competitive algorithm-classifier, as more sophisticated ones. The performance of each classifier was evaluated by calculating the accuracy, sensitivity, specificity and Matthews's correlation coefficient. The experimental results show that the mutation-based classifier particle swarm optimization unequivocally performs better than all the compared algorithms.

Chaotic Particle Swarm Optimization with Mutation for Classification

Science.gov (United States)

Assarzadeh, Zahra; Naghsh-Nilchi, Ahmad Reza

2015-01-01

In this paper, a chaotic particle swarm optimization with mutation-based classifier particle swarm optimization is proposed to classify patterns of different classes in the feature space. The introduced mutation operators and chaotic sequences allows us to overcome the problem of early convergence into a local minima associated with particle swarm optimization algorithms. That is, the mutation operator sharpens the convergence and it tunes the best possible solution. Furthermore, to remove the irrelevant data and reduce the dimensionality of medical datasets, a feature selection approach using binary version of the proposed particle swarm optimization is introduced. In order to demonstrate the effectiveness of our proposed classifier, mutation-based classifier particle swarm optimization, it is checked out with three sets of data classifications namely, Wisconsin diagnostic breast cancer, Wisconsin breast cancer and heart-statlog, with different feature vector dimensions. The proposed algorithm is compared with different classifier algorithms including k-nearest neighbor, as a conventional classifier, particle swarm-classifier, genetic algorithm, and Imperialist competitive algorithm-classifier, as more sophisticated ones. The performance of each classifier was evaluated by calculating the accuracy, sensitivity, specificity and Matthews's correlation coefficient. The experimental results show that the mutation-based classifier particle swarm optimization unequivocally performs better than all the compared algorithms. PMID:25709937

Prostate cancer detection from model-free T1-weighted time series and diffusion imaging

Science.gov (United States)

Haq, Nandinee F.; Kozlowski, Piotr; Jones, Edward C.; Chang, Silvia D.; Goldenberg, S. Larry; Moradi, Mehdi

2015-03-01

The combination of Dynamic Contrast Enhanced (DCE) images with diffusion MRI has shown great potential in prostate cancer detection. The parameterization of DCE images to generate cancer markers is traditionally performed based on pharmacokinetic modeling. However, pharmacokinetic models make simplistic assumptions about the tissue perfusion process, require the knowledge of contrast agent concentration in a major artery, and the modeling process is sensitive to noise and fitting instabilities. We address this issue by extracting features directly from the DCE T1-weighted time course without modeling. In this work, we employed a set of data-driven features generated by mapping the DCE T1 time course to its principal component space, along with diffusion MRI features to detect prostate cancer. The optimal set of DCE features is extracted with sparse regularized regression through a Least Absolute Shrinkage and Selection Operator (LASSO) model. We show that when our proposed features are used within the multiparametric MRI protocol to replace the pharmacokinetic parameters, the area under ROC curve is 0.91 for peripheral zone classification and 0.87 for whole gland classification. We were able to correctly classify 32 out of 35 peripheral tumor areas identified in the data when the proposed features were used with support vector machine classification. The proposed feature set was used to generate cancer likelihood maps for the prostate gland.

DEPA classification: a proposal for standardising PRP use and a retrospective application of available devices.

Science.gov (United States)

Magalon, J; Chateau, A L; Bertrand, B; Louis, M L; Silvestre, A; Giraudo, L; Veran, J; Sabatier, F

2016-01-01

Significant biological differences in platelet-rich plasma (PRP) preparations have been highlighted and could explain the large variability in the clinical benefit of PRP reported in the literature. The scientific community now recommends the use of classification for PRP injection; however, these classifications are focused on platelet and leucocyte concentrations. This presents the disadvantages of (1) not taking into account the final volume of the preparation; (2) omitting the presence of red blood cells in PRP and (3) not assessing the efficiency of production. On the basis of standards classically used in the Cell Therapy field, we propose the DEPA (Dose of injected platelets, Efficiency of production, Purity of the PRP, Activation of the PRP) classification to extend the characterisation of the injected PRP preparation. We retrospectively applied this classification on 20 PRP preparations for which biological characteristics were available in the literature. Dose of injected platelets varies from 0.21 to 5.43 billion, corresponding to a 25-fold increase. Only a Magellan device was able to obtain an A score for this parameter. Assessments of the efficiency of production reveal that no device is able to recover more than 90% of platelets from the blood. Purity of the preparation reveals that a majority of the preparations are contaminated by red blood cells as only three devices reach an A score for this parameter, corresponding to a percentage of platelets compared with red blood cells and leucocytes over 90%. These findings should provide significant help to clinicians in selecting a system that meets their specific needs for a given indication.

Recursive automatic classification algorithms

Energy Technology Data Exchange (ETDEWEB)

Bauman, E V; Dorofeyuk, A A

1982-03-01

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

Cluster Based Text Classification Model

DEFF Research Database (Denmark)

Nizamani, Sarwat; Memon, Nasrullah; Wiil, Uffe Kock

2011-01-01

We propose a cluster based classification model for suspicious email detection and other text classification tasks. The text classification tasks comprise many training examples that require a complex classification model. Using clusters for classification makes the model simpler and increases...... the accuracy at the same time. The test example is classified using simpler and smaller model. The training examples in a particular cluster share the common vocabulary. At the time of clustering, we do not take into account the labels of the training examples. After the clusters have been created......, the classifier is trained on each cluster having reduced dimensionality and less number of examples. The experimental results show that the proposed model outperforms the existing classification models for the task of suspicious email detection and topic categorization on the Reuters-21578 and 20 Newsgroups...

Gene expression classification of colon cancer into molecular subtypes: characterization, validation, and prognostic value.

Directory of Open Access Journals (Sweden)

Laetitia Marisa

Full Text Available Colon cancer (CC pathological staging fails to accurately predict recurrence, and to date, no gene expression signature has proven reliable for prognosis stratification in clinical practice, perhaps because CC is a heterogeneous disease. The aim of this study was to establish a comprehensive molecular classification of CC based on mRNA expression profile analyses.Fresh-frozen primary tumor samples from a large multicenter cohort of 750 patients with stage I to IV CC who underwent surgery between 1987 and 2007 in seven centers were characterized for common DNA alterations, including BRAF, KRAS, and TP53 mutations, CpG island methylator phenotype, mismatch repair status, and chromosomal instability status, and were screened with whole genome and transcriptome arrays. 566 samples fulfilled RNA quality requirements. Unsupervised consensus hierarchical clustering applied to gene expression data from a discovery subset of 443 CC samples identified six molecular subtypes. These subtypes were associated with distinct clinicopathological characteristics, molecular alterations, specific enrichments of supervised gene expression signatures (stem cell phenotype-like, normal-like, serrated CC phenotype-like, and deregulated signaling pathways. Based on their main biological characteristics, we distinguished a deficient mismatch repair subtype, a KRAS mutant subtype, a cancer stem cell subtype, and three chromosomal instability subtypes, including one associated with down-regulated immune pathways, one with up-regulation of the Wnt pathway, and one displaying a normal-like gene expression profile. The classification was validated in the remaining 123 samples plus an independent set of 1,058 CC samples, including eight public datasets. Furthermore, prognosis was analyzed in the subset of stage II-III CC samples. The subtypes C4 and C6, but not the subtypes C1, C2, C3, and C5, were independently associated with shorter relapse-free survival, even after

Proposal of cancer therapy system without rotating gantry

International Nuclear Information System (INIS)

Kodaira, Masanobu

2002-01-01

Beam therapy is one of useful methods for cancer therapy. Many results in National Institute of Radiological Sciences (NIRS) show many abilities of beam therapy for cancer therapy. In Japan, several beam therapy facilities are constructed or under construction. If its construction budget becomes to be smaller, beam therapy may be used as the general cancer therapy. But in the present beam therapy facilities, the budget of its construction is very large. One of the reasons of big budget is the construction of the big buildings equipped with thick shielding walls. Most of space of the facilities with thick shielding walls is devoted to the treatment equipments such as rotating gantries and beam transport lines. This proposal is that using oblique beam line and rotating treatment bed, multi-portal irradiation is realized without rotating gantry. At the same time, we designed adequate beam lines to minimize the total facilities. (author)

Prostate Cancer Molecular Imaging Standardized Evaluation (PROMISE): Proposed miTNM Classification for the Interpretation of PSMA-Ligand PET/CT.

Science.gov (United States)

Eiber, Matthias; Herrmann, Ken; Calais, Jeremie; Hadaschik, Boris; Giesel, Frederik L; Hartenbach, Markus; Hope, Thomas; Reiter, Robert; Maurer, Tobias; Weber, Wolfgang A; Fendler, Wolfgang P

2018-03-01

Prostate-specific membrane antigen (PSMA)-ligand PET imaging provides unprecedented accuracy for whole-body staging of prostate cancer. As PSMA-ligand PET/CT is increasingly adopted in clinical trials and routine practice worldwide, a unified language for image reporting is urgently needed. We propose a molecular imaging TNM system (miTNM, version 1.0) as a standardized reporting framework for PSMA-ligand PET/CT or PET/MRI. miTNM is designed to organize findings in comprehensible categories to promote the exchange of information among physicians and institutions. Additionally, flowcharts integrating findings of PSMA-ligand PET and morphologic imaging have been designed to guide image interpretation. Specific applications, such as assessment of prognosis or impact on management, should be evaluated in future trials. miTNM is a living framework that evolves with clinical experience and scientific data. © 2018 by the Society of Nuclear Medicine and Molecular Imaging.

Identification of immune cell infiltration in hematoxylin-eosin stained breast cancer samples: texture-based classification of tissue morphologies

Science.gov (United States)

Turkki, Riku; Linder, Nina; Kovanen, Panu E.; Pellinen, Teijo; Lundin, Johan

2016-03-01

The characteristics of immune cells in the tumor microenvironment of breast cancer capture clinically important information. Despite the heterogeneity of tumor-infiltrating immune cells, it has been shown that the degree of infiltration assessed by visual evaluation of hematoxylin-eosin (H and E) stained samples has prognostic and possibly predictive value. However, quantification of the infiltration in H and E-stained tissue samples is currently dependent on visual scoring by an expert. Computer vision enables automated characterization of the components of the tumor microenvironment, and texture-based methods have successfully been used to discriminate between different tissue morphologies and cell phenotypes. In this study, we evaluate whether local binary pattern texture features with superpixel segmentation and classification with support vector machine can be utilized to identify immune cell infiltration in H and E-stained breast cancer samples. Guided with the pan-leukocyte CD45 marker, we annotated training and test sets from 20 primary breast cancer samples. In the training set of arbitrary sized image regions (n=1,116) a 3-fold cross-validation resulted in 98% accuracy and an area under the receiver-operating characteristic curve (AUC) of 0.98 to discriminate between immune cell -rich and - poor areas. In the test set (n=204), we achieved an accuracy of 96% and AUC of 0.99 to label cropped tissue regions correctly into immune cell -rich and -poor categories. The obtained results demonstrate strong discrimination between immune cell -rich and -poor tissue morphologies. The proposed method can provide a quantitative measurement of the degree of immune cell infiltration and applied to digitally scanned H and E-stained breast cancer samples for diagnostic purposes.

Research on a Pulmonary Nodule Segmentation Method Combining Fast Self-Adaptive FCM and Classification

Directory of Open Access Journals (Sweden)

Hui Liu

2015-01-01

Full Text Available The key problem of computer-aided diagnosis (CAD of lung cancer is to segment pathologically changed tissues fast and accurately. As pulmonary nodules are potential manifestation of lung cancer, we propose a fast and self-adaptive pulmonary nodules segmentation method based on a combination of FCM clustering and classification learning. The enhanced spatial function considers contributions to fuzzy membership from both the grayscale similarity between central pixels and single neighboring pixels and the spatial similarity between central pixels and neighborhood and improves effectively the convergence rate and self-adaptivity of the algorithm. Experimental results show that the proposed method can achieve more accurate segmentation of vascular adhesion, pleural adhesion, and ground glass opacity (GGO pulmonary nodules than other typical algorithms.

Comparison of hand-craft feature based SVM and CNN based deep learning framework for automatic polyp classification.

Science.gov (United States)

Younghak Shin; Balasingham, Ilangko

2017-07-01

Colonoscopy is a standard method for screening polyps by highly trained physicians. Miss-detected polyps in colonoscopy are potential risk factor for colorectal cancer. In this study, we investigate an automatic polyp classification framework. We aim to compare two different approaches named hand-craft feature method and convolutional neural network (CNN) based deep learning method. Combined shape and color features are used for hand craft feature extraction and support vector machine (SVM) method is adopted for classification. For CNN approach, three convolution and pooling based deep learning framework is used for classification purpose. The proposed framework is evaluated using three public polyp databases. From the experimental results, we have shown that the CNN based deep learning framework shows better classification performance than the hand-craft feature based methods. It achieves over 90% of classification accuracy, sensitivity, specificity and precision.

Artificial neural networks as classification and diagnostic tools for lymph node-negative breast cancers

Energy Technology Data Exchange (ETDEWEB)

Eswari J, Satya; Chandrakar, Neha [National Institute of Technology Raipur, Raipur (India)

2016-04-15

Artificial neural networks (ANNs) can be used to develop a technique to classify lymph node negative breast cancer that is prone to distant metastases based on gene expression signatures. The neural network used is a multilayered feed forward network that employs back propagation algorithm. Once trained with DNA microarraybased gene expression profiles of genes that were predictive of distant metastasis recurrence of lymph node negative breast cancer, the ANNs became capable of correctly classifying all samples and recognizing the genes most appropriate to the classification. To test the ability of the trained ANN models in recognizing lymph node negative breast cancer, we analyzed additional idle samples that were not used beforehand for the training procedure and obtained the correctly classified result in the validation set. For more substantial result, bootstrapping of training and testing dataset was performed as external validation. This study illustrates the potential application of ANN for breast tumor diagnosis and the identification of candidate targets in patients for therapy.

Esophagus cancer

International Nuclear Information System (INIS)

Anon.

1989-01-01

Ways of metastatic spreading of esophagus cancer, depending on segmental division of esophagus are considered. Classification of esophagus cancer according to morphological structure, domestic clinical classification according to stages and international classification according to TNM system are presented. Diagnosis of esophagus cancer should be complex and based on results of clinical examination of patients, radiological, endoscopic and morphological investigations. Radiological, surgical and combined (preoperative radiotherapy with successive operation) methods of treatment are used in the case of esophagus cancer. Versions of preoperative radiotherapy are given. Favourable results of applying combined surgical treatment with preoperative radiotherapy are shown

Are preoperative histology and MRI useful for classification of endometrial cancer risk?

International Nuclear Information System (INIS)

Body, Noemie; Lavoué, Vincent; De Kerdaniel, Olivier; Foucher, Fabrice; Henno, Sébastien; Cauchois, Aurélie; Laviolle, Bruno; Leblanc, Marc; Levêque, Jean

2016-01-01

The 2010 guidelines of the French National Cancer Institute (INCa) classify patients with endometrial cancer into three risk groups for lymph node invasion and recurrence on the basis of MRI and histological analysis of an endometrial specimen obtained preoperatively. The classification guides therapeutic choices, which may include pelvic and/or para-aortic lymphadenectomy. The purpose of this study was to evaluate the diagnostic performance of preoperative assessment to help identify intermediate- or high-risk patients requiring lymphadenectomy. The study included all patients who underwent surgery for endometrial cancer between January 2010 and December 2013 at either Rennes University Hospital or Vannes Regional Hospital. The criteria for eligibility included a preoperative assessment with MRI and histological examination of an endometrial sample. A histological comparison was made between the preoperative and surgical specimens. Among the 91 patients who underwent a full preoperative assessment, the diagnosis of intermediate- or high-risk endometrial cancer was established by MRI and histology with a sensitivity of 70 %, specificity of 82 %, positive predictive value (PPV) of 87 %, negative predictive value (NPV) of 61 %, positive likelihood ratio (LR+) of 3.8 and negative likelihood ratio (LR-) of 0.3. The risk group was underestimated in 32 % of patients and overestimated in 7 % of patients. MRI underestimated endometrial cancer stage in 20 % of cases, while endometrial sampling underestimated the histological type in 4 % of cases and the grade in 9 % of cases. The preoperative assessment overestimated or underestimated the risk of recurrence in nearly 40 % of cases, with errors in lesion type, grade or stage. Erroneous preoperative risk assessment leads to suboptimal initial surgical management of patients with endometrial cancer

Glycosyltransferase Gene Expression Profiles Classify Cancer Types and Propose Prognostic Subtypes

Science.gov (United States)

Ashkani, Jahanshah; Naidoo, Kevin J.

2016-05-01

Aberrant glycosylation in tumours stem from altered glycosyltransferase (GT) gene expression but can the expression profiles of these signature genes be used to classify cancer types and lead to cancer subtype discovery? The differential structural changes to cellular glycan structures are predominantly regulated by the expression patterns of GT genes and are a hallmark of neoplastic cell metamorphoses. We found that the expression of 210 GT genes taken from 1893 cancer patient samples in The Cancer Genome Atlas (TCGA) microarray data are able to classify six cancers; breast, ovarian, glioblastoma, kidney, colon and lung. The GT gene expression profiles are used to develop cancer classifiers and propose subtypes. The subclassification of breast cancer solid tumour samples illustrates the discovery of subgroups from GT genes that match well against basal-like and HER2-enriched subtypes and correlates to clinical, mutation and survival data. This cancer type glycosyltransferase gene signature finding provides foundational evidence for the centrality of glycosylation in cancer.

Classification of Ovarian Cancer Surgery Facilitates Treatment Decisions in a Gynecological Multidisciplinary Team

DEFF Research Database (Denmark)

Bjørn, Signe Frahm; Schnack, Tine Henrichsen; Lajer, Henrik

2017-01-01

multidisciplinary team (MDT) decisions. Materials and Methods Four hundred eighteen women diagnosed with ovarian cancers (n = 351) or borderline tumors (n = 66) were selected for primary debulking surgery from January 2008 to July 2013. At an MDT meeting, women were allocated into 3 groups named "pre-COVA" 1 to 3...... classifying the expected extent of the primary surgery and need for postoperative care. On the basis of the operative procedures performed, women were allocated into 1 of the 3 corresponding COVA 1 to 3 groups. The outcome measure was the predictive value of the pre-COVA score compared with the actual COVA......-COVA classification predicted the actual COVA group in 79 (49%) FIGO stages I to IIIB and in 85 (45%) FIGO stages IIIC to IV. Conclusions The COVA classification system is a simple and useful tool in the MDT setting where specialists make treatment decisions based on advanced technology. The use of pre...

Tuning to optimize SVM approach for assisting ovarian cancer diagnosis with photoacoustic imaging.

Science.gov (United States)

Wang, Rui; Li, Rui; Lei, Yanyan; Zhu, Quing

2015-01-01

Support vector machine (SVM) is one of the most effective classification methods for cancer detection. The efficiency and quality of a SVM classifier depends strongly on several important features and a set of proper parameters. Here, a series of classification analyses, with one set of photoacoustic data from ovarian tissues ex vivo and a widely used breast cancer dataset- the Wisconsin Diagnostic Breast Cancer (WDBC), revealed the different accuracy of a SVM classification in terms of the number of features used and the parameters selected. A pattern recognition system is proposed by means of SVM-Recursive Feature Elimination (RFE) with the Radial Basis Function (RBF) kernel. To improve the effectiveness and robustness of the system, an optimized tuning ensemble algorithm called as SVM-RFE(C) with correlation filter was implemented to quantify feature and parameter information based on cross validation. The proposed algorithm is first demonstrated outperforming SVM-RFE on WDBC. Then the best accuracy of 94.643% and sensitivity of 94.595% were achieved when using SVM-RFE(C) to test 57 new PAT data from 19 patients. The experiment results show that the classifier constructed with SVM-RFE(C) algorithm is able to learn additional information from new data and has significant potential in ovarian cancer diagnosis.

Maximum mutual information regularized classification

KAUST Repository

Wang, Jim Jing-Yan

2014-09-07

In this paper, a novel pattern classification approach is proposed by regularizing the classifier learning to maximize mutual information between the classification response and the true class label. We argue that, with the learned classifier, the uncertainty of the true class label of a data sample should be reduced by knowing its classification response as much as possible. The reduced uncertainty is measured by the mutual information between the classification response and the true class label. To this end, when learning a linear classifier, we propose to maximize the mutual information between classification responses and true class labels of training samples, besides minimizing the classification error and reducing the classifier complexity. An objective function is constructed by modeling mutual information with entropy estimation, and it is optimized by a gradient descend method in an iterative algorithm. Experiments on two real world pattern classification problems show the significant improvements achieved by maximum mutual information regularization.

Maximum mutual information regularized classification

KAUST Repository

Wang, Jim Jing-Yan; Wang, Yi; Zhao, Shiguang; Gao, Xin

2014-01-01

In this paper, a novel pattern classification approach is proposed by regularizing the classifier learning to maximize mutual information between the classification response and the true class label. We argue that, with the learned classifier, the uncertainty of the true class label of a data sample should be reduced by knowing its classification response as much as possible. The reduced uncertainty is measured by the mutual information between the classification response and the true class label. To this end, when learning a linear classifier, we propose to maximize the mutual information between classification responses and true class labels of training samples, besides minimizing the classification error and reducing the classifier complexity. An objective function is constructed by modeling mutual information with entropy estimation, and it is optimized by a gradient descend method in an iterative algorithm. Experiments on two real world pattern classification problems show the significant improvements achieved by maximum mutual information regularization.

A scale space approach for unsupervised feature selection in mass spectra classification for ovarian cancer detection.

Science.gov (United States)

Ceccarelli, Michele; d'Acierno, Antonio; Facchiano, Angelo

2009-10-15

Mass spectrometry spectra, widely used in proteomics studies as a screening tool for protein profiling and to detect discriminatory signals, are high dimensional data. A large number of local maxima (a.k.a. peaks) have to be analyzed as part of computational pipelines aimed at the realization of efficient predictive and screening protocols. With this kind of data dimensions and samples size the risk of over-fitting and selection bias is pervasive. Therefore the development of bio-informatics methods based on unsupervised feature extraction can lead to general tools which can be applied to several fields of predictive proteomics. We propose a method for feature selection and extraction grounded on the theory of multi-scale spaces for high resolution spectra derived from analysis of serum. Then we use support vector machines for classification. In particular we use a database containing 216 samples spectra divided in 115 cancer and 91 control samples. The overall accuracy averaged over a large cross validation study is 98.18. The area under the ROC curve of the best selected model is 0.9962. We improved previous known results on the problem on the same data, with the advantage that the proposed method has an unsupervised feature selection phase. All the developed code, as MATLAB scripts, can be downloaded from http://medeaserver.isa.cnr.it/dacierno/spectracode.htm.

New proposals for the international classification of diseases-11 revision of pain diagnoses

DEFF Research Database (Denmark)

Rief, Winfried; Kaasa, Stein; Jensen, Rigmor

2012-01-01

The representation of pain diagnoses in current classification systems like International Classification of Diseases (ICD)-10 and Diagnostic and Statistical Manual of Mental Disorders (DSM)-IV does not adequately reflect the state of the art of pain research, and does not sufficiently support...... the clinical management and research programs for pain conditions. Moreover, there is an urgent need to harmonize classification of pain syndromes of special expert groups (eg, International Classification of Headache Disorders) and general classification systems (eg, ICD-11, DSM-V). Therefore, this paper...

Optimal preprocessing of serum and urine metabolomic data fusion for staging prostate cancer through design of experiment

International Nuclear Information System (INIS)

Zheng, Hong; Cai, Aimin; Zhou, Qi; Xu, Pengtao; Zhao, Liangcai; Li, Chen; Dong, Baijun; Gao, Hongchang

2017-01-01

Accurate classification of cancer stages will achieve precision treatment for cancer. Metabolomics presents biological phenotypes at the metabolite level and holds a great potential for cancer classification. Since metabolomic data can be obtained from different samples or analytical techniques, data fusion has been applied to improve classification accuracy. Data preprocessing is an essential step during metabolomic data analysis. Therefore, we developed an innovative optimization method to select a proper data preprocessing strategy for metabolomic data fusion using a design of experiment approach for improving the classification of prostate cancer (PCa) stages. In this study, urine and serum samples were collected from participants at five phases of PCa and analyzed using a 1 H NMR-based metabolomic approach. Partial least squares-discriminant analysis (PLS-DA) was used as a classification model and its performance was assessed by goodness of fit (R 2 ) and predictive ability (Q 2 ). Results show that data preprocessing significantly affect classification performance and depends on data properties. Using the fused metabolomic data from urine and serum, PLS-DA model with the optimal data preprocessing (R 2  = 0.729, Q 2  = 0.504, P < 0.0001) can effectively improve model performance and achieve a better classification result for PCa stages as compared with that without data preprocessing (R 2  = 0.139, Q 2  = 0.006, P = 0.450). Therefore, we propose that metabolomic data fusion integrated with an optimal data preprocessing strategy can significantly improve the classification of cancer stages for precision treatment. - Highlights: • NMR metabolomic analysis of body fluids can be used for staging prostate cancer. • Data preprocessing is an essential step for metabolomic analysis. • Data fusion improves information recovery for cancer classification. • Design of experiment achieves optimal preprocessing of metabolomic data fusion.

Breast cancer surgery and diagnosis-related groups (DRGs): patient classification and hospital reimbursement in 11 European countries.

Science.gov (United States)

Scheller-Kreinsen, David; Quentin, Wilm; Geissler, Alexander; Busse, Reinhard

2013-10-01

Researchers from eleven countries (i.e. Austria, England, Estonia, Finland, France, Germany, Ireland, Netherlands, Poland, Spain, and Sweden) compared how their DRG systems deal with breast cancer surgery patients. DRG algorithms and indicators of resource consumption were assessed for those DRGs that individually contain at least 1% of all breast cancer surgery patients. Six standardised case vignettes were defined and quasi prices according to national DRG-based hospital payment systems were ascertained. European DRG systems classify breast cancer surgery patients according to different sets of classification variables into three to seven DRGs. Quasi prices for an index case treated with partial mastectomy range from €577 in Poland to €5780 in the Netherlands. Countries award their highest payments for very different kinds of patients. Breast cancer specialists and national DRG authorities should consider how other countries' DRG systems classify breast cancer patients in order to identify potential scope for improvement and to ensure fair and appropriate reimbursement. Copyright © 2012 Elsevier Ltd. All rights reserved.

Profiling cancer

DEFF Research Database (Denmark)

Ciro, Marco; Bracken, Adrian P; Helin, Kristian

2003-01-01

In the past couple of years, several very exciting studies have demonstrated the enormous power of gene-expression profiling for cancer classification and prediction of patient survival. In addition to promising a more accurate classification of cancer and therefore better treatment of patients......, gene-expression profiling can result in the identification of novel potential targets for cancer therapy and a better understanding of the molecular mechanisms leading to cancer....

76 FR 22108 - Proposed Collection; Comment Request; Prostate, Lung, Colorectal and Ovarian Cancer Screening...

Science.gov (United States)

2011-04-20

... (prostate, lung, colorectal, and ovary). In addition, cancer incidence, stage shift, and case survival are... Request; Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (PLCO) (NCI) SUMMARY: In compliance... for public comment on proposed data collection projects, the National Cancer Institute (NCI), the...

Improving breast cancer classification with mammography, supported on an appropriate variable selection analysis

Science.gov (United States)

Pérez, Noel; Guevara, Miguel A.; Silva, Augusto

2013-02-01

This work addresses the issue of variable selection within the context of breast cancer classification with mammography. A comprehensive repository of feature vectors was used including a hybrid subset gathering image-based and clinical features. It aimed to gather experimental evidence of variable selection in terms of cardinality, type and find a classification scheme that provides the best performance over the Area Under Receiver Operating Characteristics Curve (AUC) scores using the ranked features subset. We evaluated and classified a total of 300 subsets of features formed by the application of Chi-Square Discretization, Information-Gain, One-Rule and RELIEF methods in association with Feed-Forward Backpropagation Neural Network (FFBP), Support Vector Machine (SVM) and Decision Tree J48 (DTJ48) Machine Learning Algorithms (MLA) for a comparative performance evaluation based on AUC scores. A variable selection analysis was performed for Single-View Ranking and Multi-View Ranking groups of features. Features subsets representing Microcalcifications (MCs), Masses and both MCs and Masses lesions achieved AUC scores of 0.91, 0.954 and 0.934 respectively. Experimental evidence demonstrated that classification performance was improved by combining image-based and clinical features. The most important clinical and image-based features were StromaDistortion and Circularity respectively. Other less important but worth to use due to its consistency were Contrast, Perimeter, Microcalcification, Correlation and Elongation.

Stratification and prognostic relevance of Jass’s molecular classification of colorectal cancer

OpenAIRE

Inti eZlobec; Inti eZlobec; Michel P Bihl; Anja eFoerster; Alex eRufle; Luigi eTerracciano; Alessandro eLugli; Alessandro eLugli

2012-01-01

Background: The current proposed model of colorectal tumorigenesis is based primarily on CpG island methylator phenotype (CIMP), microsatellite instability (MSI), KRAS, BRAF, and methylation status of 0-6-Methylguanine DNA Methyltransferase (MGMT) and classifies tumors into 5 subgroups. The aim of this study is to validate this molecular classification and test its prognostic relevance. Methods: 302 patients were included in this study. Molecular analysis was performed for 5 CIMP-related pro...

Multivalent Peptidomimetic Conjugates as Inhibitors of Androgen Receptor Function in Therapy-Resistant Prostate Cancer

Science.gov (United States)

2017-10-01

treat patients with prostate cancer, over time the tumors become resistant to the drugs, leaving few treatment options. The goal of this proposal is to...interactions with the AR. 15. SUBJECT TERMS androgen receptor, prostate cancer, peptidomimetic conjugates, 16. SECURITY CLASSIFICATION OF: 17...used successfully to treat patients with prostate cancer, over time the tumors become resistant to the drugs, leaving few treatment options. The goal

Simultaneous detection and classification of breast masses in digital mammograms via a deep learning YOLO-based CAD system.

Science.gov (United States)

Al-Masni, Mohammed A; Al-Antari, Mugahed A; Park, Jeong-Min; Gi, Geon; Kim, Tae-Yeon; Rivera, Patricio; Valarezo, Edwin; Choi, Mun-Taek; Han, Seung-Moo; Kim, Tae-Seong

2018-04-01

Automatic detection and classification of the masses in mammograms are still a big challenge and play a crucial role to assist radiologists for accurate diagnosis. In this paper, we propose a novel Computer-Aided Diagnosis (CAD) system based on one of the regional deep learning techniques, a ROI-based Convolutional Neural Network (CNN) which is called You Only Look Once (YOLO). Although most previous studies only deal with classification of masses, our proposed YOLO-based CAD system can handle detection and classification simultaneously in one framework. The proposed CAD system contains four main stages: preprocessing of mammograms, feature extraction utilizing deep convolutional networks, mass detection with confidence, and finally mass classification using Fully Connected Neural Networks (FC-NNs). In this study, we utilized original 600 mammograms from Digital Database for Screening Mammography (DDSM) and their augmented mammograms of 2,400 with the information of the masses and their types in training and testing our CAD. The trained YOLO-based CAD system detects the masses and then classifies their types into benign or malignant. Our results with five-fold cross validation tests show that the proposed CAD system detects the mass location with an overall accuracy of 99.7%. The system also distinguishes between benign and malignant lesions with an overall accuracy of 97%. Our proposed system even works on some challenging breast cancer cases where the masses exist over the pectoral muscles or dense regions. Copyright © 2018 Elsevier B.V. All rights reserved.

75 FR 78213 - Proposed Information Collection; Comment Request; 2012 Economic Census Classification Report for...

Science.gov (United States)

2010-12-15

... 8-digit North American Industry Classification System (NAICS) based code for use in the 2012... classification due to changes in NAICS for 2012. Collecting this classification information will ensure the... the reporting burden on sampled sectors. Proper NAICS classification data ensures high quality...

Effect of perioperative application of L-asrginine combined with intacted protein compound preparations on postoperative antitumor immunity and tumor load in patients with gastric cancer

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Xiu-Lan Jiang

2016-10-01

Full Text Available Objective: To analyze the effect of perioperative application of L-arginine combined with intacted protein compound preparations on postoperative antitumor immunity and tumor load in patients with gastric cancer. Methods: A total of 68 patients with gastric cancer received radical operation, and according to different perioperative nutrition intervention, they were divided into control group (normal glucose saline enteral nutrition and observation group (L-arginine combined with intacted protein compound preparations enteral nutrition by half. Postoperative short-term antitumor immune cell levels and serum levels of illness-related indexes, nutrition and inflammation indexes of two groups were detected, patients were followed up for 3 years and the gastric stump MRI changes were observed. Results: Venous blood CD4+ T lymphocyte level and CD4+ /CD8+ ratio of observation group 3 months after treatment were higher than those of control group while CD8+ T lymphocyte and Treg cell levels were lower than those of control group; serum Pentraxin-3, CYFRA21-1, TTF-1 and HE4 levels were lower than those of control group; ALB, PA and IL-2 levels were higher than those of control group while IL-6 and IL-10 levels were lower than those of control group (P<0.05. Gastric stump MRI images 3 years after operation were significantly different between two groups. Conclusions: Perioperative application of L-arginine combined with intacted protein compound preparations can optimize postoperative immune and nutritional state in patients with gastric cancer, and it also has positive effect on reducing the incidence of long-term gastric stump carcinoma and other aspects.

Proposals for Paraphilic Disorders in the International Classification of Diseases and Related Health Problems, Eleventh Revision (ICD-11).

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Krueger, Richard B; Reed, Geoffrey M; First, Michael B; Marais, Adele; Kismodi, Eszter; Briken, Peer

2017-07-01

The World Health Organization is currently developing the 11th revision of the International Classifications of Diseases and Related Health Problems (ICD-11), with approval of the ICD-11 by the World Health Assembly anticipated in 2018. The Working Group on the Classification of Sexual Disorders and Sexual Health (WGSDSH) was created and charged with reviewing and making recommendations for categories related to sexuality that are contained in the chapter of Mental and Behavioural Disorders in ICD-10 (World Health Organization 1992a). Among these categories was the ICD-10 grouping F65, Disorders of sexual preference, which describes conditions now widely referred to as Paraphilic Disorders. This article reviews the evidence base, rationale, and recommendations for the proposed revisions in this area for ICD-11 and compares them with DSM-5. The WGSDSH recommended that the grouping, Disorders of sexual preference, be renamed to Paraphilic Disorders and be limited to disorders that involve sexual arousal patterns that focus on non-consenting others or are associated with substantial distress or direct risk of injury or death. Consistent with this framework, the WGSDSH also recommended that the ICD-10 categories of Fetishism, Fetishistic Transvestism, and Sadomasochism be removed from the classification and new categories of Coercive Sexual Sadism Disorder, Frotteuristic Disorder, Other Paraphilic Disorder Involving Non-Consenting Individuals, and Other Paraphilic Disorder Involving Solitary Behaviour or Consenting Individuals be added. The WGSDSH's proposals for Paraphilic Disorders in ICD-11 are based on the WHO's role as a global public health agency and the ICD's function as a public health reporting tool.

Statistical Redundancy Testing for Improved Gene Selection in Cancer Classification Using Microarray Data

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J. Sunil Rao

2007-01-01

Full Text Available In gene selection for cancer classifi cation using microarray data, we define an eigenvalue-ratio statistic to measure a gene’s contribution to the joint discriminability when this gene is included into a set of genes. Based on this eigenvalueratio statistic, we define a novel hypothesis testing for gene statistical redundancy and propose two gene selection methods. Simulation studies illustrate the agreement between statistical redundancy testing and gene selection methods. Real data examples show the proposed gene selection methods can select a compact gene subset which can not only be used to build high quality cancer classifiers but also show biological relevance.

Dendrochronologically dated pine stumps document phase-wise bog expansion at a northwest German site between ca. 6700 and ca. 3400 BC

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Maike Achterberg, Inke Elisabeth; Eckstein, Jan; Birkholz, Bernhard; Bauerochse, Andreas; Leuschner, Hanns Hubert

2018-01-01

The investigated northwest German mire site at Totes Moor is densely covered with subfossil pine stumps (Pinus sylvestris L.) from the fen-bog transition. This facilitates the spatio-temporal reconstruction of mire development, which is based on 212 in situ tree stumps in the case study presented here. Six dendrochronologically dated site chronologies together cover 2345 years between 6703 and 3403 BC. The gaps in between are 6 to 550 years long. Additionally, a floating chronology of 309 years, containing 30 trees, was radiocarbon-dated to the beginning of the 7th millennium cal BC. Peat-stratigraphical survey was carried out additionally, and elevations a.s.l. were determined at several locations. Tree dying-off phases, which indicate water level rise at the site, mostly in context of the local fen-bog transition, are evident for ca. 6600-6450, ca. 6350-5750, ca. 5300-4900, ca. 4700-4550, ca. 3900-3850, ca. 3700-3600, ca. 3500-3450 and ca. 3400 BC. The spatial distribution of the dated in situ trees illustrates the phase-wise expansion of raised bog over fen peat at the site. The documented bog expansion pulses likely correspond to climatic wet sifts.

Childhood cancer and environmental integrity: a commentary and a proposal.

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Modonesi, Carlo; Oddone, Enrico; Panizza, Celestino; Gatta, Gemma

2017-04-10

Improvements in the health standards of developed and developing societies depend primarily on the relationships between economy and environment. Recent long-term changes in the chemical composition of man-made environments may be linked to changes in the biology of human beings. Here we argue that children are at the greatest risk of being affected by the dangerous effects of these changes, with particular reference to cancer. The concept of cancer risk must be extended to new contexts. Considering the increasing rates of chemical pollution and its spreading in the environment, we illustrate a proposal aiming to protect the human health, in an intra- and intergenerational perspective. A surveillance system of occupational and residential exposures should be implemented to prevent cancer risk in embryos and children.

A proposed classification system for high-level and other radioactive wastes

International Nuclear Information System (INIS)

Kocher, D.C.; Croff, A.G.

1987-06-01

This report presents a proposal for quantitative and generally applicable risk-based definitions of high-level and other radioactive wastes. On the basis of historical descriptions and definitions of high-level waste (HLW), in which HLW has been defined in terms of its source as waste from reprocessing of spent nuclear fuel, we propose a more general definition based on the concept that HLW has two distinct attributes: HLW is (1) highly radioactive and (2) requires permanent isolation. This concept leads to a two-dimensional waste classification system in which one axis, related to ''requires permanent isolation,'' is associated with long-term risks from waste disposal and the other axis, related to ''highly radioactive,'' is associated with shorter-term risks due to high levels of decay heat and external radiation. We define wastes that require permanent isolation as wastes with concentrations of radionuclides exceeding the Class-C limits that are generally acceptable for near-surface land disposal, as specified in the US Nuclear Regulatory Commission's rulemaking 10 CFR Part 61 and its supporting documentation. HLW then is waste requiring permanent isolation that also is highly radioactive, and we define ''highly radioactive'' as a decay heat (power density) in the waste greater than 50 W/m 3 or an external radiation dose rate at a distance of 1 m from the waste greater than 100 rem/h (1 Sv/h), whichever is the more restrictive. This proposal also results in a definition of Transuranic (TRU) Waste and Equivalent as waste that requires permanent isolation but is not highly radioactive and a definition of low-level waste (LLW) as waste that does not require permanent isolation without regard to whether or not it is highly radioactive

Breast cancer tumor classification using LASSO method selection approach

International Nuclear Information System (INIS)

Celaya P, J. M.; Ortiz M, J. A.; Martinez B, M. R.; Solis S, L. O.; Castaneda M, R.; Garza V, I.; Martinez F, M.; Ortiz R, J. M.

2016-10-01

Breast cancer is one of the leading causes of deaths worldwide among women. Early tumor detection is key in reducing breast cancer deaths and screening mammography is the widest available method for early detection. Mammography is the most common and effective breast cancer screening test. However, the rate of positive findings is very low, making the radiologic interpretation monotonous and biased toward errors. In an attempt to alleviate radiological workload, this work presents a computer-aided diagnosis (CAD x) method aimed to automatically classify tumor lesions into malign or benign as a means to a second opinion. The CAD x methos, extracts image features, and classifies the screening mammogram abnormality into one of two categories: subject at risk of having malignant tumor (malign), and healthy subject (benign). In this study, 143 abnormal segmentation s (57 malign and 86 benign) from the Breast Cancer Digital Repository (BCD R) public database were used to train and evaluate the CAD x system. Percentile-rank (p-rank) was used to standardize the data. Using the LASSO feature selection methodology, the model achieved a Leave-one-out-cross-validation area under the receiver operating characteristic curve (Auc) of 0.950. The proposed method has the potential to rank abnormal lesions with high probability of malignant findings aiding in the detection of potential malign cases as a second opinion to the radiologist. (Author)

Breast cancer tumor classification using LASSO method selection approach

Energy Technology Data Exchange (ETDEWEB)

Celaya P, J. M.; Ortiz M, J. A.; Martinez B, M. R.; Solis S, L. O.; Castaneda M, R.; Garza V, I.; Martinez F, M.; Ortiz R, J. M., E-mail: morvymm@yahoo.com.mx [Universidad Autonoma de Zacatecas, Av. Ramon Lopez Velarde 801, Col. Centro, 98000 Zacatecas, Zac. (Mexico)

2016-10-15

Breast cancer is one of the leading causes of deaths worldwide among women. Early tumor detection is key in reducing breast cancer deaths and screening mammography is the widest available method for early detection. Mammography is the most common and effective breast cancer screening test. However, the rate of positive findings is very low, making the radiologic interpretation monotonous and biased toward errors. In an attempt to alleviate radiological workload, this work presents a computer-aided diagnosis (CAD x) method aimed to automatically classify tumor lesions into malign or benign as a means to a second opinion. The CAD x methos, extracts image features, and classifies the screening mammogram abnormality into one of two categories: subject at risk of having malignant tumor (malign), and healthy subject (benign). In this study, 143 abnormal segmentation s (57 malign and 86 benign) from the Breast Cancer Digital Repository (BCD R) public database were used to train and evaluate the CAD x system. Percentile-rank (p-rank) was used to standardize the data. Using the LASSO feature selection methodology, the model achieved a Leave-one-out-cross-validation area under the receiver operating characteristic curve (Auc) of 0.950. The proposed method has the potential to rank abnormal lesions with high probability of malignant findings aiding in the detection of potential malign cases as a second opinion to the radiologist. (Author)

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

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

2018-05-01

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

Forensic age assessment by 3.0T MRI of the knee: proposal of a new MRI classification of ossification stages.

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Vieth, Volker; Schulz, Ronald; Heindel, Walter; Pfeiffer, Heidi; Buerke, Boris; Schmeling, Andreas; Ottow, Christian

2018-03-13

To explore the possibility of determining majority via a morphology-based examination of the epiphyseal-diaphyseal fusion by 3.0 T magnetic resonance imaging (MRI), a prospective cross-sectional study developing and applying a new stage classification was conducted. 344 male and 350 female volunteers of German nationality between the ages of 12-24 years were scanned between May 2013 and June 2015. A 3.0 T MRI scanner was used, acquiring a T1-weighted (T1-w) turbo spin-echo sequence (TSE) and a T2-weighted (T2-w) TSE sequence with fat suppression by spectral pre-saturation with inversion recovery (SPIR). The gathered information was sifted and a five-stage classification was formulated as a hypothesis. The images were then assessed using this classification. The relevant statistics were defined, the intra- and interobserver agreements were determined, and the differences between the sexes were analysed. The application of the new classification made it possible to correctly assess majority in both sexes by the examination of the epiphyses of the knee joint. The intra- and interobserver agreement levels were very good (κ > 0.80). The Mann-Whitney-U Test implied significant sex-related differences for most stages. Applying the presented MRI classification, it is possible to determine the completion of the 18th year of life in either sex by 3.0 T MRI of the knee joint. • Based on prospective referential data a new MRI classification was formulated. • The setting allows assessment of the age of an individual's skeletal development. • The classification scheme allows the reliable determination of majority in both sexes. • The staging shows a high reproducibility for instructed and trained professional personnel. • The proposed classification is likely to be adaptable to other long bone epiphyses.

The radiology of early esophageal cancer

International Nuclear Information System (INIS)

Uematsu, S.

1988-01-01

The radiographic diagnosis of early esophageal cancer is described based on 25 cases in which depth of invasion was limited to not more than the submucosal layer. It is emphasized that double contrast radiography should be designed to delineate the subtle abnormalities of the esophageal mucosa and margins of lesions which are characteristic of early cancer, and that further investigation should be directed to improving the method of examination so that the detection of ep- and mm-cancer which has a better prognosis than sm cancer can be detected more readily. A macroscopic classification of early esophageal cancer (elevated, flat, depressed and mixed type) which is useful for both endoscopic and radiographic diagnosis is proposed. The 5-year survival rate of esophageal cancer which was limited to the submucosal layer or less (ep-, mm- and sm-cancer) was 50%

Cell nuclei attributed relational graphs for efficient representation and classification of gastric cancer in digital histopathology

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Sharma, Harshita; Zerbe, Norman; Heim, Daniel; Wienert, Stephan; Lohmann, Sebastian; Hellwich, Olaf; Hufnagl, Peter

2016-03-01

This paper describes a novel graph-based method for efficient representation and subsequent classification in histological whole slide images of gastric cancer. Her2/neu immunohistochemically stained and haematoxylin and eosin stained histological sections of gastric carcinoma are digitized. Immunohistochemical staining is used in practice by pathologists to determine extent of malignancy, however, it is laborious to visually discriminate the corresponding malignancy levels in the more commonly used haematoxylin and eosin stain, and this study attempts to solve this problem using a computer-based method. Cell nuclei are first isolated at high magnification using an automatic cell nuclei segmentation strategy, followed by construction of cell nuclei attributed relational graphs of the tissue regions. These graphs represent tissue architecture comprehensively, as they contain information about cell nuclei morphology as vertex attributes, along with knowledge of neighborhood in the form of edge linking and edge attributes. Global graph characteristics are derived and ensemble learning is used to discriminate between three types of malignancy levels, namely, non-tumor, Her2/neu positive tumor and Her2/neu negative tumor. Performance is compared with state of the art methods including four texture feature groups (Haralick, Gabor, Local Binary Patterns and Varma Zisserman features), color and intensity features, and Voronoi diagram and Delaunay triangulation. Texture, color and intensity information is also combined with graph-based knowledge, followed by correlation analysis. Quantitative assessment is performed using two cross validation strategies. On investigating the experimental results, it can be concluded that the proposed method provides a promising way for computer-based analysis of histopathological images of gastric cancer.

[New International Classification of Chronic Pancreatitis (M-ANNHEIM multifactor classification system, 2007): principles, merits, and demerits].

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Tsimmerman, Ia S

2008-01-01

The new International Classification of Chronic Pancreatitis (designated as M-ANNHEIM) proposed by a group of German specialists in late 2007 is reviewed. All its sections are subjected to analysis (risk group categories, clinical stages and phases, variants of clinical course, diagnostic criteria for "established" and "suspected" pancreatitis, instrumental methods and functional tests used in the diagnosis, evaluation of the severity of the disease using a scoring system, stages of elimination of pain syndrome). The new classification is compared with the earlier classification proposed by the author. Its merits and demerits are discussed.

Validity of Three Recently Proposed Prognostic Grading Indexes for Breast Cancer Patients With Radiosurgically Treated Brain Metastases

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Yamamoto, Masaaki, E-mail: BCD06275@nifty.com [Katsuta Hospital Mito GammaHouse, Hitachi-naka (Japan); Department of Neurosurgery, Tokyo Women' s Medical University Medical Center E, Tokyo (Japan); Kawabe, Takuya [Katsuta Hospital Mito GammaHouse, Hitachi-naka (Japan); Department of Neurosurgery, Kyoto Prefectural University of Medicine Graduate School of Medical Sciences, Kyoto (Japan); Higuchi, Yoshinori [Department of Neurosurgery, Chiba University Graduate School of Medicine, Chiba (Japan); Sato, Yasunori [Clinical Research Center, Chiba University Graduate School of Medicine, Chiba (Japan); Barfod, Bierta E. [Katsuta Hospital Mito GammaHouse, Hitachi-naka (Japan); Kasuya, Hidetoshi [Department of Neurosurgery, Tokyo Women' s Medical University Medical Center E, Tokyo (Japan); Urakawa, Yoichi [Katsuta Hospital Mito GammaHouse, Hitachi-naka (Japan)

2012-12-01

Purpose: We tested the validity of 3 recently proposed prognostic indexes for breast cancer patients with brain metastases (METs) treated radiosurgically. The 3 indexes are Diagnosis-Specific Graded Prognostic Assessment (DS-GPA), New Breast Cancer (NBC)-Recursive Partitioning Analysis (RPA), and our index, sub-classification of RPA class II patients into 3 sub-classes (RPA class II-a, II-b and II-c) based on Karnofsky performance status, tumor number, original tumor status, and non-brain METs. Methods and Materials: This was an institutional review board-approved, retrospective cohort study using our database of 269 consecutive female breast cancer patients (mean age, 55 years; range, 26-86 years) who underwent Gamma Knife radiosurgery (GKRS) alone, without whole-brain radiation therapy, for brain METs during the 15-year period between 1996 and 2011. The Kaplan-Meier method was used to estimate the absolute risk of each event. Results: Kaplan-Meier plots of our patient series showed statistically significant survival differences among patients stratified into 3, 4, or 5 groups based on the 3 systems (P<.001). However, the mean survival time (MST) differences between some pairs of groups failed to reach statistical significance with all 3 systems. Thus, we attempted to regrade our 269 breast cancer patients into 3 groups by modifying our aforementioned index along with the original RPA class I and III, (ie, RPA I+II-a, II-b, and II-c+III). There were statistically significant MST differences among these 3 groups without overlap of 95% confidence intervals (CIs) between any 2 pairs of groups: 18.4 (95% CI = 14.0-29.5) months in I+II-a, 9.2 in II-b (95% CI = 6.8-12.9, P<.001 vs I+II-a) and 5.0 in II-c+III (95% CI = 4.2-6.8, P<.001 vs II-b). Conclusions: As none of the new grading systems, DS-GPS, BC-RPA and our system, was applicable to our set of radiosurgically treated patients for comparing survivals after GKRS, we slightly modified our system for breast cancer

Pondering the monoterpene composition of Pinus serotina Michx.: can limonene be used as a chemotaxonomic marker for the identification of old turpentine stumps?

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Thomas L. Eberhardt; Jolie M. Mahfouz; Philip M. Sheridan

2010-01-01

Wood samples from old turpentine stumps in Virginia were analyzed by GC-MS to determine if the monoterpene compositions could be used for species identification. Given that limonene is reported to be the predominant monoterpene for pond pine (Pinus serotina Michx.), low relative proportions of limonene in these samples appeared to suggest that these...

Impact of full field digital mammography on the classification and mammographic characteristics of interval breast cancers

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Knox, Mark, E-mail: marktknox@gmail.com; O’Brien, Angela, E-mail: angelaobrien@doctors.org.uk; Szabó, Endre, E-mail: endrebacsi@freemail.hu; Smith, Clare S., E-mail: csmith@mater.ie; Fenlon, Helen M., E-mail: helen.fenlon@cancerscreening.ie; McNicholas, Michelle M., E-mail: michelle.mcnicholas@cancerscreening.ie; Flanagan, Fidelma L., E-mail: fidelma.flanagan@cancerscreening.ie

2015-06-15

Highlights: • Digital mammography has changed the presentation of interval breast cancer. • Less interval breast cancers are associated with microcalcifications following FFDM. • Interval breast cancer audit remains a key feature of any breast screening program. - Abstract: Objective: Full field digital mammography (FFDM) is increasingly replacing screen film mammography (SFM) in breast screening programs. Interval breast cancers are an issue in all screening programs and the purpose of our study is to assess the impact of FFDM on the classification of interval breast cancers at independent blind review and to compare the mammographic features of interval cancers at FFDM and SFM. Materials and methods: This study included 138 cases of interval breast cancer, 76 following an FFDM screening examination and 62 following screening with SFM. The prior screening mammogram was assessed by each of five consultant breast radiologists who were blinded to the site of subsequent cancer. Subsequent review of the diagnostic mammogram was performed and cases were classified as missed, minimal signs, occult or true interval. Mammographic features of the interval cancer at diagnosis and any abnormality identified on the prior screening mammogram were recorded. Results: The percentages of cancers classified as missed at FFDM and SFM did not differ significantly, 10.5% (8 of 76) at FFDM and 8.1% (5 of 62) at SFM (p = .77). There were significantly less interval cancers presenting as microcalcifications (alone or in association with another abnormality) following screening with FFDM, 16% (12 of 76) than following a SFM examination, 32% (20 of 62) (p = .02). Conclusion: Interval breast cancers continue to pose a problem at FFDM. The switch to FFDM has changed the mammographic presentation of interval breast cancer, with less interval cancers presenting in association with microcalcifications.

Impact of full field digital mammography on the classification and mammographic characteristics of interval breast cancers

International Nuclear Information System (INIS)

Knox, Mark; O’Brien, Angela; Szabó, Endre; Smith, Clare S.; Fenlon, Helen M.; McNicholas, Michelle M.; Flanagan, Fidelma L.

2015-01-01

Highlights: • Digital mammography has changed the presentation of interval breast cancer. • Less interval breast cancers are associated with microcalcifications following FFDM. • Interval breast cancer audit remains a key feature of any breast screening program. - Abstract: Objective: Full field digital mammography (FFDM) is increasingly replacing screen film mammography (SFM) in breast screening programs. Interval breast cancers are an issue in all screening programs and the purpose of our study is to assess the impact of FFDM on the classification of interval breast cancers at independent blind review and to compare the mammographic features of interval cancers at FFDM and SFM. Materials and methods: This study included 138 cases of interval breast cancer, 76 following an FFDM screening examination and 62 following screening with SFM. The prior screening mammogram was assessed by each of five consultant breast radiologists who were blinded to the site of subsequent cancer. Subsequent review of the diagnostic mammogram was performed and cases were classified as missed, minimal signs, occult or true interval. Mammographic features of the interval cancer at diagnosis and any abnormality identified on the prior screening mammogram were recorded. Results: The percentages of cancers classified as missed at FFDM and SFM did not differ significantly, 10.5% (8 of 76) at FFDM and 8.1% (5 of 62) at SFM (p = .77). There were significantly less interval cancers presenting as microcalcifications (alone or in association with another abnormality) following screening with FFDM, 16% (12 of 76) than following a SFM examination, 32% (20 of 62) (p = .02). Conclusion: Interval breast cancers continue to pose a problem at FFDM. The switch to FFDM has changed the mammographic presentation of interval breast cancer, with less interval cancers presenting in association with microcalcifications

Prognostic Performance and Reproducibility of the 1973 and 2004/2016 World Health Organization Grading Classification Systems in Non-muscle-invasive Bladder Cancer: A European Association of Urology Non-muscle Invasive Bladder Cancer Guidelines Panel Systematic Review.

Science.gov (United States)

Soukup, Viktor; Čapoun, Otakar; Cohen, Daniel; Hernández, Virginia; Babjuk, Marek; Burger, Max; Compérat, Eva; Gontero, Paolo; Lam, Thomas; MacLennan, Steven; Mostafid, A Hugh; Palou, Joan; van Rhijn, Bas W G; Rouprêt, Morgan; Shariat, Shahrokh F; Sylvester, Richard; Yuan, Yuhong; Zigeuner, Richard

2017-11-01

Tumour grade is an important prognostic indicator in non-muscle-invasive bladder cancer (NMIBC). Histopathological classifications are limited by interobserver variability (reproducibility), which may have prognostic implications. European Association of Urology NMIBC guidelines suggest concurrent use of both 1973 and 2004/2016 World Health Organization (WHO) classifications. To compare the prognostic performance and reproducibility of the 1973 and 2004/2016 WHO grading systems for NMIBC. A systematic literature search was undertaken incorporating Medline, Embase, and the Cochrane Library. Studies were critically appraised for risk of bias (QUIPS). For prognosis, the primary outcome was progression to muscle-invasive or metastatic disease. Secondary outcomes were disease recurrence, and overall and cancer-specific survival. For reproducibility, the primary outcome was interobserver variability between pathologists. Secondary outcome was intraobserver variability (repeatability) by the same pathologist. Of 3593 articles identified, 20 were included in the prognostic review; three were eligible for the reproducibility review. Increasing tumour grade in both classifications was associated with higher disease progression and recurrence rates. Progression rates in grade 1 patients were similar to those in low-grade patients; progression rates in grade 3 patients were higher than those in high-grade patients. Survival data were limited. Reproducibility of the 2004/2016 system was marginally better than that of the 1973 system. Two studies on repeatability showed conflicting results. Most studies had a moderate to high risk of bias. Current grading classifications in NMIBC are suboptimal. The 1973 system identifies more aggressive tumours. Intra- and interobserver variability was slightly less in the 2004/2016 classification. We could not confirm that the 2004/2016 classification outperforms the 1973 classification in prediction of recurrence and progression. This article

Modified Angle's Classification for Primary Dentition.

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Chandranee, Kaushik Narendra; Chandranee, Narendra Jayantilal; Nagpal, Devendra; Lamba, Gagandeep; Choudhari, Purva; Hotwani, Kavita

2017-01-01

This study aims to propose a modification of Angle's classification for primary dentition and to assess its applicability in children from Central India, Nagpur. Modification in Angle's classification has been proposed for application in primary dentition. Small roman numbers i/ii/iii are used for primary dentition notation to represent Angle's Class I/II/III molar relationships as in permanent dentition, respectively. To assess applicability of modified Angle's classification a cross-sectional preschool 2000 children population from central India; 3-6 years of age residing in Nagpur metropolitan city of Maharashtra state were selected randomly as per the inclusion and exclusion criteria. Majority 93.35% children were found to have bilateral Class i followed by 2.5% bilateral Class ii and 0.2% bilateral half cusp Class iii molar relationships as per the modified Angle's classification for primary dentition. About 3.75% children had various combinations of Class ii relationships and 0.2% children were having Class iii subdivision relationship. Modification of Angle's classification for application in primary dentition has been proposed. A cross-sectional investigation using new classification revealed various 6.25% Class ii and 0.4% Class iii molar relationships cases in preschool children population in a metropolitan city of Nagpur. Application of the modified Angle's classification to other population groups is warranted to validate its routine application in clinical pediatric dentistry.

Compensatory neurofuzzy model for discrete data classification in biomedical

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Ceylan, Rahime

2015-03-01

Biomedical data is separated to two main sections: signals and discrete data. So, studies in this area are about biomedical signal classification or biomedical discrete data classification. There are artificial intelligence models which are relevant to classification of ECG, EMG or EEG signals. In same way, in literature, many models exist for classification of discrete data taken as value of samples which can be results of blood analysis or biopsy in medical process. Each algorithm could not achieve high accuracy rate on classification of signal and discrete data. In this study, compensatory neurofuzzy network model is presented for classification of discrete data in biomedical pattern recognition area. The compensatory neurofuzzy network has a hybrid and binary classifier. In this system, the parameters of fuzzy systems are updated by backpropagation algorithm. The realized classifier model is conducted to two benchmark datasets (Wisconsin Breast Cancer dataset and Pima Indian Diabetes dataset). Experimental studies show that compensatory neurofuzzy network model achieved 96.11% accuracy rate in classification of breast cancer dataset and 69.08% accuracy rate was obtained in experiments made on diabetes dataset with only 10 iterations.

Colombia: Territorial classification

International Nuclear Information System (INIS)

Mendoza Morales, Alberto

1998-01-01

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

Childhood cancer and environmental integrity: a commentary and a proposal

Directory of Open Access Journals (Sweden)

Carlo Modonesi

Full Text Available ABSTRACT Improvements in the health standards of developed and developing societies depend primarily on the relationships between economy and environment. Recent long-term changes in the chemical composition of man-made environments may be linked to changes in the biology of human beings. Here we argue that children are at the greatest risk of being affected by the dangerous effects of these changes, with particular reference to cancer. The concept of cancer risk must be extended to new contexts. Considering the increasing rates of chemical pollution and its spreading in the environment, we illustrate a proposal aiming to protect the human health, in an intra- and intergenerational perspective. A surveillance system of occupational and residential exposures should be implemented to prevent cancer risk in embryos and children.

Iris Image Classification Based on Hierarchical Visual Codebook.

Science.gov (United States)

Zhenan Sun; Hui Zhang; Tieniu Tan; Jianyu Wang

2014-06-01

Iris recognition as a reliable method for personal identification has been well-studied with the objective to assign the class label of each iris image to a unique subject. In contrast, iris image classification aims to classify an iris image to an application specific category, e.g., iris liveness detection (classification of genuine and fake iris images), race classification (e.g., classification of iris images of Asian and non-Asian subjects), coarse-to-fine iris identification (classification of all iris images in the central database into multiple categories). This paper proposes a general framework for iris image classification based on texture analysis. A novel texture pattern representation method called Hierarchical Visual Codebook (HVC) is proposed to encode the texture primitives of iris images. The proposed HVC method is an integration of two existing Bag-of-Words models, namely Vocabulary Tree (VT), and Locality-constrained Linear Coding (LLC). The HVC adopts a coarse-to-fine visual coding strategy and takes advantages of both VT and LLC for accurate and sparse representation of iris texture. Extensive experimental results demonstrate that the proposed iris image classification method achieves state-of-the-art performance for iris liveness detection, race classification, and coarse-to-fine iris identification. A comprehensive fake iris image database simulating four types of iris spoof attacks is developed as the benchmark for research of iris liveness detection.

A deep learning-based multi-model ensemble method for cancer prediction.

Science.gov (United States)

Xiao, Yawen; Wu, Jun; Lin, Zongli; Zhao, Xiaodong

2018-01-01

Cancer is a complex worldwide health problem associated with high mortality. With the rapid development of the high-throughput sequencing technology and the application of various machine learning methods that have emerged in recent years, progress in cancer prediction has been increasingly made based on gene expression, providing insight into effective and accurate treatment decision making. Thus, developing machine learning methods, which can successfully distinguish cancer patients from healthy persons, is of great current interest. However, among the classification methods applied to cancer prediction so far, no one method outperforms all the others. In this paper, we demonstrate a new strategy, which applies deep learning to an ensemble approach that incorporates multiple different machine learning models. We supply informative gene data selected by differential gene expression analysis to five different classification models. Then, a deep learning method is employed to ensemble the outputs of the five classifiers. The proposed deep learning-based multi-model ensemble method was tested on three public RNA-seq data sets of three kinds of cancers, Lung Adenocarcinoma, Stomach Adenocarcinoma and Breast Invasive Carcinoma. The test results indicate that it increases the prediction accuracy of cancer for all the tested RNA-seq data sets as compared to using a single classifier or the majority voting algorithm. By taking full advantage of different classifiers, the proposed deep learning-based multi-model ensemble method is shown to be accurate and effective for cancer prediction. Copyright © 2017 Elsevier B.V. All rights reserved.

Development of a classification system for cup anemometers - CLASSCUP

DEFF Research Database (Denmark)

Friis Pedersen, Troels

2003-01-01

the objectives to quantify the errors associated with the use of cup anemometers, and to determine the requirements for an optimum design of a cup anemometer, and to develop a classification system forquantification of systematic errors of cup anemometers. The present report describes this proposed...... classification system. A classification method for cup anemometers has been developed, which proposes general external operational ranges to be used. Anormal category range connected to ideal sites of the IEC power performance standard was made, and another extended category range for complex terrain...... was proposed. General classification indices were proposed for all types of cup anemometers. As a resultof the classification, the cup anemometer will be assigned to a certain class: 0.5, 1, 2, 3 or 5 with corresponding intrinsic errors (%) as a vector instrument (3D) or as a horizontal instrument (2D...

76 FR 14034 - Proposed Collection; Comment Request; NCI Cancer Genetics Services Directory Web-Based...

Science.gov (United States)

2011-03-15

... DEPARTMENT OF HEALTH AND HUMAN SERVICES National Institutes of Health Proposed Collection; Comment Request; NCI Cancer Genetics Services Directory Web-Based Application Form and Update Mailer Summary: In... Cancer Genetics Services Directory Web-based Application Form and Update Mailer. [[Page 14035

An approach for leukemia classification based on cooperative game theory.

Science.gov (United States)

Torkaman, Atefeh; Charkari, Nasrollah Moghaddam; Aghaeipour, Mahnaz

2011-01-01

Hematological malignancies are the types of cancer that affect blood, bone marrow and lymph nodes. As these tissues are naturally connected through the immune system, a disease affecting one of them will often affect the others as well. The hematological malignancies include; Leukemia, Lymphoma, Multiple myeloma. Among them, leukemia is a serious malignancy that starts in blood tissues especially the bone marrow, where the blood is made. Researches show, leukemia is one of the common cancers in the world. So, the emphasis on diagnostic techniques and best treatments would be able to provide better prognosis and survival for patients. In this paper, an automatic diagnosis recommender system for classifying leukemia based on cooperative game is presented. Through out this research, we analyze the flow cytometry data toward the classification of leukemia into eight classes. We work on real data set from different types of leukemia that have been collected at Iran Blood Transfusion Organization (IBTO). Generally, the data set contains 400 samples taken from human leukemic bone marrow. This study deals with cooperative game used for classification according to different weights assigned to the markers. The proposed method is versatile as there are no constraints to what the input or output represent. This means that it can be used to classify a population according to their contributions. In other words, it applies equally to other groups of data. The experimental results show the accuracy rate of 93.12%, for classification and compared to decision tree (C4.5) with (90.16%) in accuracy. The result demonstrates that cooperative game is very promising to be used directly for classification of leukemia as a part of Active Medical decision support system for interpretation of flow cytometry readout. This system could assist clinical hematologists to properly recognize different kinds of leukemia by preparing suggestions and this could improve the treatment of leukemic

Pyovagina and stump pyometra in a neutered XX sex-reversed Beagle: a case report

International Nuclear Information System (INIS)

Williams, J.; Partington, B.P.; Smith, B.; Hedlund, C.S.; Law, J.M.

1997-01-01

An 18-month-old, neutered male beagle presented with acute abdominal signs and a suppurative infection of the urogenital tract. Chromosomal sex was female (78, XX), gonadal sex was male (testicles), and phenotypic sex was ambiguous, with evidence of both male and female duct systems. The internal and external genitalia consisted of epididymides, an underdeveloped uterus with an immature spermatic cord, communication between the uterus or cranial vagina and the membranous urethra, a urethrographically male urethra, a hypoplastic os penis, and a hypoplastic penis with hypospadia. Based on these findings and the familial history of a similarly affected litter mate, the dog was diagnosed as having the XX male syndrome with pyovagina and uterine stump pyometra. Radiographic and ultrasonographic investigations are described, and abnormalities of chromosomal sex, gonadal sex, and phenotypic sex are discussed

A proposed classification system for high-level and other radioactive wastes

International Nuclear Information System (INIS)

Kocher, D.C.; Croff, A.G.

1989-01-01

On the basis of the definition of high-level wastes (HLW) in the Nuclear Waste Policy Act of 1982 and previous descriptions of reprocessing wastes, a definition is proposed based on the concept that HLW is any waste which is highly radioactive and requires permanent isolation. This conceptual definition of HLW leads to a two-dimensional waste classification system in which one axis, related to 'highly radioactive', is associated with shorter-term risks from waste management and disposal due to high levels of decay heat and external radiation, and the other axis, related to 'requires permanent isolation', is associated with longer-term risks from waste disposal. Wastes that are highly radioactive are defined quantitatively as wastes with a decay heat (power density) greater than 50 W/m 3 or an external dose-equivalent rate greater than 100 rem/h (1 Sv/h) at a distance of 1 m from the waste, whichever is more restrictive. Wastes that require permanent isolation are defined quantitatively as wastes with concentrations of radionuclides greater than the Class-C limits that are generally acceptable for near-surface land disposal, as obtained from the Nuclear Regulatory Commission's 10 CFR Part 61 and its associated methodology. This proposal leads to similar definitions of two other waste classes: transuranic (TRU) waste and equivalent is any waste that requires permanent isolation but is not highly radioactive; and low-level waste (LLW) is any waste that does not require permanent isolation, without regard to whether or not it is highly radioactive. 31 refs.; 3 figs.; 4 tabs

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

International Nuclear Information System (INIS)

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

2008-01-01

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

An immunologic portrait of cancer

Directory of Open Access Journals (Sweden)

Stroncek David F

2011-08-01

Full Text Available Abstract The advent of high-throughput technology challenges the traditional histopathological classification of cancer, and proposes new taxonomies derived from global transcriptional patterns. Although most of these molecular re-classifications did not endure the test of time, they provided bulk of new information that can reframe our understanding of human cancer biology. Here, we focus on an immunologic interpretation of cancer that segregates oncogenic processes independent from their tissue derivation into at least two categories of which one bears the footprints of immune activation. Several observations describe a cancer phenotype where the expression of interferon stimulated genes and immune effector mechanisms reflect patterns commonly observed during the inflammatory response against pathogens, which leads to elimination of infected cells. As these signatures are observed in growing cancers, they are not sufficient to entirely clear the organism of neoplastic cells but they sustain, as in chronic infections, a self-perpetuating inflammatory process. Yet, several studies determined an association between this inflammatory status and a favorable natural history of the disease or a better responsiveness to cancer immune therapy. Moreover, these signatures overlap with those observed during immune-mediated cancer rejection and, more broadly, immune-mediated tissue-specific destruction in other immune pathologies. Thus, a discussion concerning this cancer phenotype is warranted as it remains unknown why it occurs in immune competent hosts. It also remains uncertain whether a genetically determined response of the host to its own cancer, the genetic makeup of the neoplastic process or a combination of both drives the inflammatory process. Here we reflect on commonalities and discrepancies among studies and on the genetic or somatic conditions that may cause this schism in cancer behavior.

Modified angle's classification for primary dentition

Directory of Open Access Journals (Sweden)

Kaushik Narendra Chandranee

2017-01-01

Full Text Available Aim: This study aims to propose a modification of Angle's classification for primary dentition and to assess its applicability in children from Central India, Nagpur. Methods: Modification in Angle's classification has been proposed for application in primary dentition. Small roman numbers i/ii/iii are used for primary dentition notation to represent Angle's Class I/II/III molar relationships as in permanent dentition, respectively. To assess applicability of modified Angle's classification a cross-sectional preschool 2000 children population from central India; 3–6 years of age residing in Nagpur metropolitan city of Maharashtra state were selected randomly as per the inclusion and exclusion criteria. Results: Majority 93.35% children were found to have bilateral Class i followed by 2.5% bilateral Class ii and 0.2% bilateral half cusp Class iii molar relationships as per the modified Angle's classification for primary dentition. About 3.75% children had various combinations of Class ii relationships and 0.2% children were having Class iii subdivision relationship. Conclusions: Modification of Angle's classification for application in primary dentition has been proposed. A cross-sectional investigation using new classification revealed various 6.25% Class ii and 0.4% Class iii molar relationships cases in preschool children population in a metropolitan city of Nagpur. Application of the modified Angle's classification to other population groups is warranted to validate its routine application in clinical pediatric dentistry.

[Molecular classification of breast cancer patients obtained through the technique of chromogenic in situ hybridization (CISH)].

Science.gov (United States)

Fernández, Angel; Reigosa, Aldo

2013-12-01

Breast cancer is a heterogeneous disease composed of a growing number of biological subtypes, with substantial variability of the disease progression within each category. The aim of this research was to classify the samples object of study according to the molecular classes of breast cancer: luminal A, luminal B, HER2 and triple negative, as a result of the state of HER2 amplification obtained by the technique of chromogenic in situ hybridization (CISH). The sample consisted of 200 biopsies fixed in 10% formalin, processed by standard techniques up to paraffin embedding, corresponding to patients diagnosed with invasive ductal carcinoma of the breast. These biopsies were obtained from patients from private practice and the Institute of Oncology "Dr. Miguel Pérez Carreño", for immunohistochemistry (IHC) of hormone receptors and HER2 made in the Hospital Metropolitano del Norte, Valencia, Venezuela. The molecular classification of the patient's tumors considering the expression of estrogen and progesterone receptors by IHC and HER2 amplification by CISH, allowed those cases originally classified as unknown, since they had an indeterminate (2+) outcome for HER2 expression by IHC, to be grouped into the different molecular classes. Also, this classification permitted that some cases, initially considered as belonging to a molecular class, were assigned to another class, after the revaluation of the HER2 status by CISH.

Cluster Validity Classification Approaches Based on Geometric Probability and Application in the Classification of Remotely Sensed Images

Directory of Open Access Journals (Sweden)

LI Jian-Wei

2014-08-01

Full Text Available On the basis of the cluster validity function based on geometric probability in literature [1, 2], propose a cluster analysis method based on geometric probability to process large amount of data in rectangular area. The basic idea is top-down stepwise refinement, firstly categories then subcategories. On all clustering levels, use the cluster validity function based on geometric probability firstly, determine clusters and the gathering direction, then determine the center of clustering and the border of clusters. Through TM remote sensing image classification examples, compare with the supervision and unsupervised classification in ERDAS and the cluster analysis method based on geometric probability in two-dimensional square which is proposed in literature 2. Results show that the proposed method can significantly improve the classification accuracy.

3D nuclear organization of telomeres in the Hodgkin cell lines U-HO1 and U-HO1-PTPN1: PTPN1 expression prevents the formation of very short telomeres including "t-stumps"

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Lemieux Bruno

2010-12-01

Full Text Available Abstract Background In cancer cells the three-dimensional (3D telomere organization of interphase nuclei into a telomeric disk is heavily distorted and aggregates are found. In Hodgkin's lymphoma quantitative FISH (3D Q-FISH reveals a major impact of nuclear telomere dynamics during the transition form mononuclear Hodgkin (H to diagnostic multinuclear Reed-Sternberg (RS cells. In vitro and in vivo formation of RS-cells is associated with the increase of very short telomeres including "t-stumps", telomere loss, telomeric aggregate formation and the generation of "ghost nuclei". Results Here we analyze the 3D telomere dynamics by Q-FISH in the novel Hodgkin cell line U-HO1 and its non-receptor protein-tyrosine phosphatase N1 (PTPN1 stable transfectant U-HO1-PTPN1, derived from a primary refractory Hodgkin's lymphoma. Both cell lines show equally high telomerase activity but U-HO1-PTPN differs from U-HO1 by a three times longer doubling time, low STAT5A expression, accumulation of RS-cells (p As expected, multinuclear U-HO1-RS-cells and multinuclear U-HO1-PTPN1-RS-cells differ from their mononuclear H-precursors by their nuclear volume (p Conclusion Abundant RS-cells without additional very short telomeres including "t-stumps", high rate of apoptosis, but low STAT5A expression, are hallmarks of the U-HO1-PTPN1 cell line. These characteristics are independent of telomerase activity. Thus, PTPN1 induced dephosphorylation of STAT5 with consecutive lack of Akt/PKB activation and cellular arrest in G2, promoting induction of apoptosis, appears as a possible pathogenetic mechanism deserving further experimental investigation.

Early esophageal cancer detection using RF classifiers

Science.gov (United States)

Janse, Markus H. A.; van der Sommen, Fons; Zinger, Svitlana; Schoon, Erik J.; de With, Peter H. N.

2016-03-01

Esophageal cancer is one of the fastest rising forms of cancer in the Western world. Using High-Definition (HD) endoscopy, gastroenterology experts can identify esophageal cancer at an early stage. Recent research shows that early cancer can be found using a state-of-the-art computer-aided detection (CADe) system based on analyzing static HD endoscopic images. Our research aims at extending this system by applying Random Forest (RF) classification, which introduces a confidence measure for detected cancer regions. To visualize this data, we propose a novel automated annotation system, employing the unique characteristics of the previous confidence measure. This approach allows reliable modeling of multi-expert knowledge and provides essential data for real-time video processing, to enable future use of the system in a clinical setting. The performance of the CADe system is evaluated on a 39-patient dataset, containing 100 images annotated by 5 expert gastroenterologists. The proposed system reaches a precision of 75% and recall of 90%, thereby improving the state-of-the-art results by 11 and 6 percentage points, respectively.

Machine learning models in breast cancer survival prediction.

Science.gov (United States)

Montazeri, Mitra; Montazeri, Mohadeseh; Montazeri, Mahdieh; Beigzadeh, Amin

2016-01-01

Breast cancer is one of the most common cancers with a high mortality rate among women. With the early diagnosis of breast cancer survival will increase from 56% to more than 86%. Therefore, an accurate and reliable system is necessary for the early diagnosis of this cancer. The proposed model is the combination of rules and different machine learning techniques. Machine learning models can help physicians to reduce the number of false decisions. They try to exploit patterns and relationships among a large number of cases and predict the outcome of a disease using historical cases stored in datasets. The objective of this study is to propose a rule-based classification method with machine learning techniques for the prediction of different types of Breast cancer survival. We use a dataset with eight attributes that include the records of 900 patients in which 876 patients (97.3%) and 24 (2.7%) patients were females and males respectively. Naive Bayes (NB), Trees Random Forest (TRF), 1-Nearest Neighbor (1NN), AdaBoost (AD), Support Vector Machine (SVM), RBF Network (RBFN), and Multilayer Perceptron (MLP) machine learning techniques with 10-cross fold technique were used with the proposed model for the prediction of breast cancer survival. The performance of machine learning techniques were evaluated with accuracy, precision, sensitivity, specificity, and area under ROC curve. Out of 900 patients, 803 patients and 97 patients were alive and dead, respectively. In this study, Trees Random Forest (TRF) technique showed better results in comparison to other techniques (NB, 1NN, AD, SVM and RBFN, MLP). The accuracy, sensitivity and the area under ROC curve of TRF are 96%, 96%, 93%, respectively. However, 1NN machine learning technique provided poor performance (accuracy 91%, sensitivity 91% and area under ROC curve 78%). This study demonstrates that Trees Random Forest model (TRF) which is a rule-based classification model was the best model with the highest level of

Breast imaging reporting and data system (BI-RADS) or French 'classification ACR'

International Nuclear Information System (INIS)

Dilhuydy, Marie Helene

2007-01-01

Summary: The American College of Radiology Task Force on Breast Cancer published in 2003 Fourth edition of BI-RADS for Mammography. It is a lexicon of mammography terms including illustrations of each feature described, followed by a reporting format with assessment categories according to the degree of concern. The aim is to reduce inconsistencies in mammography reports and recommendations for assessment, to facilitate outcome monitoring and to allow each radiologist to audit his own mammography practice. In France, the Societe Francaise de Radiologie acquired the rights to translate BI-RADS, word for word and without adaptation or influence. The last edition was published in 2004. Simultaneously, French Haute Autorite de Sante and National Committee for Breast Cancer Screening proposed to all community practice mammography facilities a classification of detected abnormalities stating more clearly than BI-RADS do which feature has to be included in such and such assessment category and how to manage it. This 'classification ACR' is adapted from BI-RADS but strongly influenced by the context of the French nationwide screening programme, and by European recommendations to limitate undesirable risks of screening such as false positive and overdiagnosis. The differences between the two systems are discussed

Prediction of Depression in Cancer Patients With Different Classification Criteria, Linear Discriminant Analysis versus Logistic Regression.

Science.gov (United States)

Shayan, Zahra; Mohammad Gholi Mezerji, Naser; Shayan, Leila; Naseri, Parisa

2015-11-03

Logistic regression (LR) and linear discriminant analysis (LDA) are two popular statistical models for prediction of group membership. Although they are very similar, the LDA makes more assumptions about the data. When categorical and continuous variables used simultaneously, the optimal choice between the two models is questionable. In most studies, classification error (CE) is used to discriminate between subjects in several groups, but this index is not suitable to predict the accuracy of the outcome. The present study compared LR and LDA models using classification indices. This cross-sectional study selected 243 cancer patients. Sample sets of different sizes (n = 50, 100, 150, 200, 220) were randomly selected and the CE, B, and Q classification indices were calculated by the LR and LDA models. CE revealed the a lack of superiority for one model over the other, but the results showed that LR performed better than LDA for the B and Q indices in all situations. No significant effect for sample size on CE was noted for selection of an optimal model. Assessment of the accuracy of prediction of real data indicated that the B and Q indices are appropriate for selection of an optimal model. The results of this study showed that LR performs better in some cases and LDA in others when based on CE. The CE index is not appropriate for classification, although the B and Q indices performed better and offered more efficient criteria for comparison and discrimination between groups.

[Treatment of testicular cancer].

Science.gov (United States)

Droz, Jean-Pierre; Boyle, Helen; Culine, Stéphane; Fizazi, Karim; Fléchon, Aude; Massard, Christophe

2013-12-01

Germ-cell tumours (GCTs) are the most common type of cancer in young men. Since the late 1970s, disseminated GCT have been a paradigm for curable metastatic cancer and metastatic GCTs are highly curable with cisplatin-based chemotherapy followed by surgical resection of residual masses. Patients' prognosis is currently assessed using the International Germ-Cell Consensus Classification (IGCCC) and used to adapt the burden of chemotherapy. Approximately 20% of patients still do not achieve cure after first-line cisplatin-based chemotherapy, and need salvage chemotherapy (high dose or standard dose chemotherapy). Clinical stage I testicular cancer is the most common presentation and different strategies are proposed: adjuvant therapies, surgery or surveillance. During the last three decades, clinical trials and strong international collaborations lead to the development of a consensus in the management of GCTs.

A practicable approach for periodontal classification

Science.gov (United States)

Mittal, Vishnu; Bhullar, Raman Preet K.; Bansal, Rachita; Singh, Karanprakash; Bhalodi, Anand; Khinda, Paramjit K.

2013-01-01

The Diagnosis and classification of periodontal diseases has remained a dilemma since long. Two distinct concepts have been used to define diseases: Essentialism and Nominalism. Essentialistic concept implies the real existence of disease whereas; nominalistic concept states that the names of diseases are the convenient way of stating concisely the endpoint of a diagnostic process. It generally advances from assessment of symptoms and signs toward knowledge of causation and gives a feasible option to name the disease for which etiology is either unknown or it is too complex to access in routine clinical practice. Various classifications have been proposed by the American Academy of Periodontology (AAP) in 1986, 1989 and 1999. The AAP 1999 classification is among the most widely used classification. But this classification also has demerits which provide impediment for its use in day to day practice. Hence a classification and diagnostic system is required which can help the clinician to access the patient's need and provide a suitable treatment which is in harmony with the diagnosis for that particular case. Here is an attempt to propose a practicable classification and diagnostic system of periodontal diseases for better treatment outcome. PMID:24379855

The Classification of Romanian High-Schools

Science.gov (United States)

Ivan, Ion; Milodin, Daniel; Naie, Lucian

2006-01-01

The article tries to tackle the issue of high-schools classification from one city, district or from Romania. The classification criteria are presented. The National Database of Education is also presented and the application of criteria is illustrated. An algorithm for high-school multi-rang classification is proposed in order to build classes of…

FACET CLASSIFICATIONS OF E-LEARNING TOOLS

Directory of Open Access Journals (Sweden)

Olena Yu. Balalaieva

2013-12-01

Full Text Available The article deals with the classification of e-learning tools based on the facet method, which suggests the separation of the parallel set of objects into independent classification groups; at the same time it is not assumed rigid classification structure and pre-built finite groups classification groups are formed by a combination of values taken from the relevant facets. An attempt to systematize the existing classification of e-learning tools from the standpoint of classification theory is made for the first time. Modern Ukrainian and foreign facet classifications of e-learning tools are described; their positive and negative features compared to classifications based on a hierarchical method are analyzed. The original author's facet classification of e-learning tools is proposed.

Histological image classification using biologically interpretable shape-based features

International Nuclear Information System (INIS)

Kothari, Sonal; Phan, John H; Young, Andrew N; Wang, May D

2013-01-01

Automatic cancer diagnostic systems based on histological image classification are important for improving therapeutic decisions. Previous studies propose textural and morphological features for such systems. These features capture patterns in histological images that are useful for both cancer grading and subtyping. However, because many of these features lack a clear biological interpretation, pathologists may be reluctant to adopt these features for clinical diagnosis. We examine the utility of biologically interpretable shape-based features for classification of histological renal tumor images. Using Fourier shape descriptors, we extract shape-based features that capture the distribution of stain-enhanced cellular and tissue structures in each image and evaluate these features using a multi-class prediction model. We compare the predictive performance of the shape-based diagnostic model to that of traditional models, i.e., using textural, morphological and topological features. The shape-based model, with an average accuracy of 77%, outperforms or complements traditional models. We identify the most informative shapes for each renal tumor subtype from the top-selected features. Results suggest that these shapes are not only accurate diagnostic features, but also correlate with known biological characteristics of renal tumors. Shape-based analysis of histological renal tumor images accurately classifies disease subtypes and reveals biologically insightful discriminatory features. This method for shape-based analysis can be extended to other histological datasets to aid pathologists in diagnostic and therapeutic decisions

Lesion classification using clinical and visual data fusion by multiple kernel learning

Science.gov (United States)

Kisilev, Pavel; Hashoul, Sharbell; Walach, Eugene; Tzadok, Asaf

2014-03-01

To overcome operator dependency and to increase diagnosis accuracy in breast ultrasound (US), a lot of effort has been devoted to developing computer-aided diagnosis (CAD) systems for breast cancer detection and classification. Unfortunately, the efficacy of such CAD systems is limited since they rely on correct automatic lesions detection and localization, and on robustness of features computed based on the detected areas. In this paper we propose a new approach to boost the performance of a Machine Learning based CAD system, by combining visual and clinical data from patient files. We compute a set of visual features from breast ultrasound images, and construct the textual descriptor of patients by extracting relevant keywords from patients' clinical data files. We then use the Multiple Kernel Learning (MKL) framework to train SVM based classifier to discriminate between benign and malignant cases. We investigate different types of data fusion methods, namely, early, late, and intermediate (MKL-based) fusion. Our database consists of 408 patient cases, each containing US images, textual description of complaints and symptoms filled by physicians, and confirmed diagnoses. We show experimentally that the proposed MKL-based approach is superior to other classification methods. Even though the clinical data is very sparse and noisy, its MKL-based fusion with visual features yields significant improvement of the classification accuracy, as compared to the image features only based classifier.

Classification of breast masses in ultrasonic B scans using Nakagami and K distributions

International Nuclear Information System (INIS)

Shankar, P M; Dumane, Vishruta A; George, Thomas; Piccoli, Catherine W; Reid, John M; Forsberg, Flemming; Goldberg, Barry B

2003-01-01

Classification of breast masses in greyscale ultrasound images is undertaken using a multiparameter approach. Five parameters reflecting the non-Rayleigh nature of the backscattered echo were used. These parameters, based mostly on the Nakagami and K distributions, were extracted from the envelope of the echoes at the site, boundary, spiculated region and shadow of the mass. They were combined to create a linear discriminant. The performance of this discriminant for the classification of breast masses was studied using a data set consisting of 70 benign and 29 malignant cases. The A z value for the discriminant was 0.96 ± 0.02, showing great promise in the classification of masses into benign and malignant ones. The discriminant was combined with the level of suspicion values of the radiologist leading to an A z value of 0.97 ± 0.014. The parameters used here can be calculated with minimal clinical intervention, so the method proposed here may therefore be easily implemented in an automated fashion. These results also support the recent reports suggesting that ultrasound may help as an adjunct to mammography in breast cancer diagnostics to enhance the classification of breast masses

Identifying therapeutic targets in gastric cancer: the current status and future direction

Science.gov (United States)

Yu, Beiqin; Xie, Jingwu

2016-01-01

Gastric cancer is the third leading cause of cancer-related death worldwide. Our basic understanding of gastric cancer biology falls behind that of many other cancer types. Current standard treatment options for gastric cancer have not changed for the last 20 years. Thus, there is an urgent need to establish novel strategies to treat this deadly cancer. Successful clinical trials with Gleevec in CML and gastrointestinal stromal tumors have set up an example for targeted therapy of cancer. In this review, we will summarize major progress in classification, therapeutic options of gastric cancer. We will also discuss molecular mechanisms for drug resistance in gastric cancer. In addition, we will attempt to propose potential future directions in gastric cancer biology and drug targets. PMID:26373844

A proposal for a pharmacokinetic interaction significance classification system (PISCS) based on predicted drug exposure changes and its potential application to alert classifications in product labelling.

Science.gov (United States)

Hisaka, Akihiro; Kusama, Makiko; Ohno, Yoshiyuki; Sugiyama, Yuichi; Suzuki, Hiroshi

2009-01-01

Pharmacokinetic drug-drug interactions (DDIs) are one of the major causes of adverse events in pharmacotherapy, and systematic prediction of the clinical relevance of DDIs is an issue of significant clinical importance. In a previous study, total exposure changes of many substrate drugs of cytochrome P450 (CYP) 3A4 caused by coadministration of inhibitor drugs were successfully predicted by using in vivo information. In order to exploit these predictions in daily pharmacotherapy, the clinical significance of the pharmacokinetic changes needs to be carefully evaluated. The aim of the present study was to construct a pharmacokinetic interaction significance classification system (PISCS) in which the clinical significance of DDIs was considered with pharmacokinetic changes in a systematic manner. Furthermore, the classifications proposed by PISCS were compared in a detailed manner with current alert classifications in the product labelling or the summary of product characteristics used in Japan, the US and the UK. A matrix table was composed by stratifying two basic parameters of the prediction: the contribution ratio of CYP3A4 to the oral clearance of substrates (CR), and the inhibition ratio of inhibitors (IR). The total exposure increase was estimated for each cell in the table by associating CR and IR values, and the cells were categorized into nine zones according to the magnitude of the exposure increase. Then, correspondences between the DDI significance and the zones were determined for each drug group considering the observed exposure changes and the current classification in the product labelling. Substrate drugs of CYP3A4 selected from three therapeutic groups, i.e. HMG-CoA reductase inhibitors (statins), calcium-channel antagonists/blockers (CCBs) and benzodiazepines (BZPs), were analysed as representative examples. The product labelling descriptions of drugs in Japan, US and UK were obtained from the websites of each regulatory body. Among 220

A case of remnant pancreatic cancer after pancreatoduodenectomy successfully treated using chemotherapy and carbon-ion radiotherapy

International Nuclear Information System (INIS)

Yamamoto, Tatsuhito; Tokunou, Kazuhisa; Yamamoto, Hisato; Kamei, Ryoji; Kitamura, Yoshinori; Ando, Seiichiro

2016-01-01

We report a case of remnant pancreatic cancer after pancreatoduodenectomy that was successfully treated using chemotherapy and carbon-ion radiotherapy. A 68-year-old woman received SSPPD for pancreatic head cancer. Gemcitabine (GEM) was administered for a year as postoperative chemotherapy. One year 8 months after surgery, abdominal CT showed a 20 mm solid mass in the stump of the remnant pancreas and dilation of the distal pancreatic duct. FDG-PET revealed a solitary tumor without any recurrence. We diagnosed the patient with a solitary recurrence of pancreatic cancer. Chemotherapy (GEM) and carbon-ion radiotherapy were performed. After treatment, the lesion was not detected on CT or FDG-PET. Chemotherapy (GEM) and carbon-ion radiotherapy for locally advanced pancreatic cancer seems to be effective and there might result in a survival benefit. (author)

78 FR 53763 - Proposed Collection; 60-day Comment Request Cancer Trials Support Unit (CTSU) (NCI)

Science.gov (United States)

2013-08-30

... proposed data collection projects, the National Cancer Institute (NCI), National Institutes of Health (NIH), will publish periodic summaries of proposed projects to be submitted to the Office of Management and... proposed collection of information, including the validity of the methodology and assumptions used; (3...

A proposal for a new classification of complications in craniosynostosis surgery.

Science.gov (United States)

Shastin, Dmitri; Peacock, Sharron; Guruswamy, Velu; Kapetanstrataki, Melpo; Bonthron, David T; Bellew, Maggie; Long, Vernon; Carter, Lachlan; Smith, Ian; Goodden, John; Russell, John; Liddington, Mark; Chumas, Paul

2017-06-01

OBJECTIVE Complications have been used extensively to facilitate evaluation of craniosynostosis practice. However, description of complications tends to be nonstandardized, making comparison difficult. The authors propose a new pragmatic classification of complications that relies on prospective data collection, is geared to capture significant morbidity as well as any "near misses" in a systematic fashion, and can be used as a quality improvement tool. METHODS Data on complications for all patients undergoing surgery for nonsyndromic craniosynostosis between 2010 and 2015 were collected from a prospective craniofacial audit database maintained at the authors' institution. Information on comorbidities, details of surgery, and follow-up was extracted from medical records, anesthetic and operation charts, and electronic databases. Complications were defined as any unexpected event that resulted or could have resulted in a temporary or permanent damage to the child. RESULTS A total of 108 operations for the treatment of nonsyndromic craniosynostosis were performed in 103 patients during the 5-year study period. Complications were divided into 6 types: 0) perioperative occurrences; 1) inpatient complications; 2) outpatient complications not requiring readmission; 3) complications requiring readmission; 4) unexpected long-term deficit; and 5) mortality. These types were further subdivided according to the length of stay and time after discharge. The overall complication rate was found to be 35.9%. CONCLUSIONS The proportion of children with some sort of complication using the proposed definition was much higher than commonly reported, predominantly due to the inclusion of problems often dismissed as minor. The authors believe that these complications should be included in determining complication rates, as they will cause distress to families and may point to potential areas for improving a surgical service.

Cancer cell detection and classification using transformation invariant template learning methods

International Nuclear Information System (INIS)

Talware, Rajendra; Abhyankar, Aditya

2011-01-01

In traditional cancer cell detection, pathologists examine biopsies to make diagnostic assessments, largely based on cell morphology and tissue distribution. The process of image acquisition is very much subjective and the pattern undergoes unknown or random transformations during data acquisition (e.g. variation in illumination, orientation, translation and perspective) results in high degree of variability. Transformed Component Analysis (TCA) incorporates a discrete, hidden variable that accounts for transformations and uses the Expectation Maximization (EM) algorithm to jointly extract components and normalize for transformations. Further the TEMPLAR framework developed takes advantage of hierarchical pattern models and adds probabilistic modeling for local transformations. Pattern classification is based on Expectation Maximization algorithm and General Likelihood Ratio Tests (GLRT). Performance of TEMPLAR is certainly improved by defining area of interest on slide a priori. Performance can be further enhanced by making the kernel function adaptive during learning. (author)

Classification of Flotation Frothers

Directory of Open Access Journals (Sweden)

Jan Drzymala

2018-02-01

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