995 resultados para Functional classification


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Myocardial Perfusion Gated Single Photon Emission Tomography (Gated-SPET) imaging is used for the combined evaluation of myocardial perfusion and left ventricular (LV) function. But standard protocols of the Gated-SPECT studies require long acquisition times for each study. It is therefore important to reduce as much as possible the total duration of image acquisition. However, it is known that this reduction leads to decrease on counts statistics per projection and raises doubts about the validity of the functional parameters determined by Gated-SPECT. Considering that, it’s difficult to carry out this analysis in real patients. For ethical, logistical and economical matters, simulated studies could be required for this analysis. Objective: Evaluate the influence of the total number of counts acquired from myocardium, in the calculation of myocardial functional parameters (LVEF – left ventricular ejection fraction, EDV – end-diastolic volume, ESV – end-sistolic volume) using routine software procedures.

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Copyright © 2013 John Wiley & Sons Ltd.

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Copyright © 2014 The Authors. Methods in Ecology and Evolution © 2014 British Ecological Society.

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OBJETIVO: Traduzir para o português e validar o questionário de qualidade de vida Functional Assessment of Cancer Therapy - Bone Marrow Transplantation (FACT-BMT) em pacientes transplantados de medula óssea. OBJETIVO: O estudo foi realizado em Ribeirão Preto, SP, em 2005. O FACT-BMT (versão 3) traduzido e a versão em português do Short Form-36 Health Survey (SF-36) foram aplicados simultaneamente em 55 pacientes consecutivos com leucemia, submetidos ao transplante e em seguimento. Dois parâmetros clínicos foram utilizados para testar a sensibilidade do questionário: tempo decorrido do transplante e presença ou não de doença do enxerto contra o hospedeiro. Foi utilizada a análise de variância (ANOVA) com o teste post hoc de Tukey. Aplicou-se o coeficiente alfa de Cronbach, padronizado para todas as questões, escore final e domínios. RESULTADOS: A média de idade dos pacientes foi 34,8±8,1 anos, com escolaridade média de 10,8±4,7 anos, sendo 78,1% do sexo feminino. A duração média de tempo pós-transplante foi de 29,8±32,19 meses. Nenhuma alteração do formato original do questionário foi observada no final do processo de tradução e adaptação cultural. A consistência interna foi alta (0,88). A correlação entre o questionário traduzido e o SF-36 variou de 0,35 a 0,57, considerada de moderada a boa para a maioria dos domínios de qualidade de vida. A avaliação das validades de construto e concorrente foi satisfatória e estatisticamente significativa. CONCLUSÕES: A versão para o português do FACT-BMT foi validada satisfatoriamente para a aplicação em pacientes brasileiros de ambos os sexos submetidos ao transplante de medula óssea.

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This paper presents a proposal for an automatic vehicle detection and classification (AVDC) system. The proposed AVDC should classify vehicles accordingly to the Portuguese legislation (vehicle height over the first axel and number of axels), and should also support profile based classification. The AVDC should also fulfill the needs of the Portuguese motorway operator, Brisa. For the classification based on the profile we propose:he use of Eigenprofiles, a technique based on Principal Components Analysis. The system should also support multi-lane free flow for future integration in this kind of environments.

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GimC/Prefoldin is a hetero-oligomeric complex involved in cytoskeleton biogenesis. In order to identify by two-hybrid system targets that directly interact with Gims and support the stress phenotypes, this work aimed the functional validation of all Gims in saccharomyces cerevisiae.

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Chronic liver disease (CLD) is most of the time an asymptomatic, progressive, and ultimately potentially fatal disease. In this study, an automatic hierarchical procedure to stage CLD using ultrasound images, laboratory tests, and clinical records are described. The first stage of the proposed method, called clinical based classifier (CBC), discriminates healthy from pathologic conditions. When nonhealthy conditions are detected, the method refines the results in three exclusive pathologies in a hierarchical basis: 1) chronic hepatitis; 2) compensated cirrhosis; and 3) decompensated cirrhosis. The features used as well as the classifiers (Bayes, Parzen, support vector machine, and k-nearest neighbor) are optimally selected for each stage. A large multimodal feature database was specifically built for this study containing 30 chronic hepatitis cases, 34 compensated cirrhosis cases, and 36 decompensated cirrhosis cases, all validated after histopathologic analysis by liver biopsy. The CBC classification scheme outperformed the nonhierachical one against all scheme, achieving an overall accuracy of 98.67% for the normal detector, 87.45% for the chronic hepatitis detector, and 95.71% for the cirrhosis detector.

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PURPOSE: Fatty liver disease (FLD) is an increasing prevalent disease that can be reversed if detected early. Ultrasound is the safest and ubiquitous method for identifying FLD. Since expert sonographers are required to accurately interpret the liver ultrasound images, lack of the same will result in interobserver variability. For more objective interpretation, high accuracy, and quick second opinions, computer aided diagnostic (CAD) techniques may be exploited. The purpose of this work is to develop one such CAD technique for accurate classification of normal livers and abnormal livers affected by FLD. METHODS: In this paper, the authors present a CAD technique (called Symtosis) that uses a novel combination of significant features based on the texture, wavelet transform, and higher order spectra of the liver ultrasound images in various supervised learning-based classifiers in order to determine parameters that classify normal and FLD-affected abnormal livers. RESULTS: On evaluating the proposed technique on a database of 58 abnormal and 42 normal liver ultrasound images, the authors were able to achieve a high classification accuracy of 93.3% using the decision tree classifier. CONCLUSIONS: This high accuracy added to the completely automated classification procedure makes the authors' proposed technique highly suitable for clinical deployment and usage.

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Chronic Liver Disease is a progressive, most of the time asymptomatic, and potentially fatal disease. In this paper, a semi-automatic procedure to stage this disease is proposed based on ultrasound liver images, clinical and laboratorial data. In the core of the algorithm two classifiers are used: a k nearest neighbor and a Support Vector Machine, with different kernels. The classifiers were trained with the proposed multi-modal feature set and the results obtained were compared with the laboratorial and clinical feature set. The results showed that using ultrasound based features, in association with laboratorial and clinical features, improve the classification accuracy. The support vector machine, polynomial kernel, outperformed the others classifiers in every class studied. For the Normal class we achieved 100% accuracy, for the chronic hepatitis with cirrhosis 73.08%, for compensated cirrhosis 59.26% and for decompensated cirrhosis 91.67%.

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In this work the identification and diagnosis of various stages of chronic liver disease is addressed. The classification results of a support vector machine, a decision tree and a k-nearest neighbor classifier are compared. Ultrasound image intensity and textural features are jointly used with clinical and laboratorial data in the staging process. The classifiers training is performed by using a population of 97 patients at six different stages of chronic liver disease and a leave-one-out cross-validation strategy. The best results are obtained using the support vector machine with a radial-basis kernel, with 73.20% of overall accuracy. The good performance of the method is a promising indicator that it can be used, in a non invasive way, to provide reliable information about the chronic liver disease staging.

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In this work liver contour is semi-automatically segmented and quantified in order to help the identification and diagnosis of diffuse liver disease. The features extracted from the liver contour are jointly used with clinical and laboratorial data in the staging process. The classification results of a support vector machine, a Bayesian and a k-nearest neighbor classifier are compared. A population of 88 patients at five different stages of diffuse liver disease and a leave-one-out cross-validation strategy are used in the classification process. The best results are obtained using the k-nearest neighbor classifier, with an overall accuracy of 80.68%. The good performance of the proposed method shows a reliable indicator that can improve the information in the staging of diffuse liver disease.

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Steatosis, also known as fatty liver, corresponds to an abnormal retention of lipids within the hepatic cells and reflects an impairment of the normal processes of synthesis and elimination of fat. Several causes may lead to this condition, namely obesity, diabetes, or alcoholism. In this paper an automatic classification algorithm is proposed for the diagnosis of the liver steatosis from ultrasound images. The features are selected in order to catch the same characteristics used by the physicians in the diagnosis of the disease based on visual inspection of the ultrasound images. The algorithm, designed in a Bayesian framework, computes two images: i) a despeckled one, containing the anatomic and echogenic information of the liver, and ii) an image containing only the speckle used to compute the textural features. These images are computed from the estimated RF signal generated by the ultrasound probe where the dynamic range compression performed by the equipment is taken into account. A Bayes classifier, trained with data manually classified by expert clinicians and used as ground truth, reaches an overall accuracy of 95% and a 100% of sensitivity. The main novelties of the method are the estimations of the RF and speckle images which make it possible to accurately compute textural features of the liver parenchyma relevant for the diagnosis.

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Analyses of species-diversity patterns of remote islands have been crucial to the development of biogeographic theory, yet little is known about corresponding patterns in functional traits on islands and how, for example, they may be affected by the introduction of exotic species. We collated trait data for spiders and beetles and used a functional diversity index (FRic) to test for nonrandomness in the contribution of endemic, other native (also combined as indigenous), and exotic species to functional-trait space across the nine islands of the Azores. In general, for both taxa and for each distributional category, functional diversity increases with species richness, which, in turn scales with island area. Null simulations support the hypothesis that each distributional group contributes to functional diversity in proportion to their species richness. Exotic spiders have added novel trait space to a greater degree than have exotic beetles, likely indicating greater impact of the reduction of immigration filters and/or differential historical losses of indigenous species. Analyses of species occurring in native-forest remnants provide limited indications of the operation of habitat filtering of exotics for three islands, but only for beetles. Although the general linear (not saturating) pattern of trait-space increase with richness of exotics suggests an ongoing process of functional enrichment and accommodation, further work is urgently needed to determine how estimates of extinction debt of indigenous species should be adjusted in the light of these findings.

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Introdução: Nas crianças/jovens com Paralisia Cerebral (PC), as limitações motoras repercutem-se em limitações funcionais e, consequentemente, na diminuição da participação em ocupações. Sendo as manifestações da PC diferentes de indivíduo para indivíduo, estas vão refletir, dependendo da gravidade, quadro motor, ambiente físico e social, diferentes níveis de participação. Objetivo: O objetivo deste estudo foi avaliar a relação entre a idade, sexo e grau de comprometimento motor e a participação em crianças/jovens com diagnóstico de paralisia cerebral com idades compreendidas entre os 5 e os 18 anos na ilha de São Miguel. Amostra e Métodos: 25 crianças de ambos os sexos (5- 18 anos), sinalizadas em instituições especializadas de reabilitação e em Centros de Atividades Ocupações (CAO’s) na Ilha de São Miguel – Açores. Foram aplicados dois instrumentos de avaliação às crianças/jovens, Gross Motor Function Measure e Quality of Upper Extremity Skills Test, e foram entregues aos pais os outros dois instrumentos para autopreenchimento, Assessment of Life Habits e Child Health Questionnaire – Parent- Form 50. Na análise estatística, recorreu-se a testes como o Kolmogorov-Smirnov, Tstudent ou Mann-Whitney, teste de Fisher, teste de Spearman e ANOVA. Resultados: Não foram encontradas relações significativas entre a idade e o sexo e o nível de participação das crianças/jovens com PC. Contrariamente, ao avaliarmos a relação entre o grau de participação e o grau de afetação verificamos que esta é significativa (p=0,004). Conclusão: Na nossa amostra não se encontrou uma influência da idade e do sexo com a frequência da participação (relações não foram significativas). Contudo, pode-se concluir que as crianças/jovens que apresentam menos limitações motoras, como as que se enquadram no nível I/II da Gross Motor Function Classification System, apresentam níveis de participação maiores do que as que apresentam níveis de afetação motora maiores (Nível V)

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OBJECTIVE: To evaluate musculoskeletal disorders among active industrial workers. METHODS: The study was carried out in São Carlos, Southeastern Brazil, in 2005. One hundred and thirty-four female workers were physically evaluated and answered questions about their physical symptoms, filled out a pain scale and gave responses in the Oswestry Disability Questionnaire, and the Work Ability Index questionnaire. The data were analyzed descriptively, and in correlation tests and through applying logistic regression. The outcome was evaluated in relation to the perceptions of pain, symptoms, physical assessment, ability to work and disability. RESULTS: Clinical evaluations and sick leave presented positive correlations with the subjective variables. The Work Ability Index presented a negative correlation with the physical disability index (r=-0.69). Symptoms reported at the time of the assessment presented a good correlation with the results from the pain scale and the clinical findings. Previous sick leave showed an association with disability (OR=1.13; 95% CI:1.08;1.18). CONCLUSION: Symptom reports and pain scales may be useful for assessing current conditions at the time of evaluating individuals with work-related musculoskeletal disorders, as they are easier to apply. In more severe cases of such injuries, clinical and functional evaluations and questionnaires such as those relating to ability to work and disability are preferable. Precise and specific evaluations of these disorders may contribute towards fairer legal and administrative decisions.