Efetividade da reeducação postural global no tratamento de um caso de lombociatalgia de origem discal

A Reeducação Postural Global (RPG) é um método que promove o alongamento da musculatura estática (tónica), incluindo a intervertebral, que está constantemente em contração, originando grandes forças compressivas sobre o disco intervertebral. Apesar de ser uma modalidade de tratamento muito utilizada, existem poucos estudos que suportem a sua base teórica e a sua efetividade clínica. Objetivo: Avaliar a efetividade do método de RPG no tratamento de um caso de lombociatalgia de origem discal. Métodos: Estudo de caso clínico de um professor de 56 anos de idade, com sintomas de hérnia discal lombar no nível de L4-L5, associada a uma anterolistesis de L5, confirmada por Ressonância Magnética. A avaliação e tratamento centrou-se no método de RPG realizado ao longo de duas sessões. Na primeira sessão foi utilizada uma postura de abertura de coxofemoral em decúbito durante 30 minutos, enquanto que na segunda foi utilizada inicialmente essa postura durante 20 minutos, seguida de uma postura em fechamento de coxofemoral em carga durante 15 minutos. Foram analisados os dados relativos à avaliação postural (inspecção visual), à dor (Escala Visual Analógica), à força muscular dos peroniais e extensores dos dedos (Teste Muscular Manual), à presença de formigueiro e ao reflexo aquiliano antes e depois de cada uma das sessões. Resultados: No final das duas sessões, verificaram-se alterações na avaliação postural, principalmente com a diminuição da hiperlordose lombar e da retroversão dos ilíacos, normalização do reflexo aquiliano e da força muscular, diminuição da sensação de formigueiro e desaparecimento total da dor. Conclusão: Os resultados obtidos neste estudo sugerem que a Reeducação Postural Global foi efectiva no tratamento de um caso de lombociatalgia com origem numa hérnia discal lombar.

Interpretation of gravity data to delineate structural features connected to low-temperature geothermal resources at Northeastern Portugal

A great number of low-temperature geothermal fields occur in Northern-Portugal related to fractured rocks. The most important superficial manifestations of these hydrothermal systems appear in pull-apart tectonic basins and are strongly conditioned by the orientation of the main fault systems in the region. This work presents the interpretation of gravity gradient maps and 3D inversion model produced from a regional gravity survey. The horizontal gradients reveal a complex fault system. The obtained 3D model of density contrast puts into evidence the main fault zone in the region and the depth distribution of the granitic bodies. Their relationship with the hydrothermal systems supports the conceptual models elaborated from hydrochemical and isotopic water analyses. This work emphasizes the importance of the role of the gravity method and analysis to better understand the connection between hydrothermal systems and the fractured rock pattern and surrounding geology. (c) 2013 Elsevier B.V. All rights reserved.

Classification and staging of chronic liver disease from multimodal data

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.

Data mining framework for fatty liver disease classification in ultrasound: a hybrid feature extraction paradigm

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.

Chronic liver disease staging classification based on ultrasound, clinical and laboratorial data

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.

Diffuse liver disease classification from ultrasound surface characterization, clinical and laboratorial data

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.

Previsão de vento baseado em técnicas de Data Mining

Mestrado em Engenharia Electrotécnica – Sistemas Eléctricos de Energia

Data envelopment analysis: eficiência relativa das unidades de tomada de decisão

A avaliação das organizações e a deterntinação da performance obtida pelo exercício da gestão, tem sido uma preocupação constante de gestores e accionistas, embora com objectivos diversos. Nos dias de hoje, a questão coloca-se com maior acuidade quer pela competitividade acrescida quer pela dimensão e complexidade actual das empresas. Pretendemos com este trabalho fazer uma descrição da metodologia DEA - Data Envelopment Analysis - nas suas formulações iniciais mais simples. A metodologia do DEA, pretende obter uma medida única e simples de avaliação da eficiência, combinando um conjunto de outputs e de inputs relativos às diferentes unidades homogéneas que se pretendem avaliar. O método DEA é um método não paramétrico que pelas suas características é particularmente adequado à avaliação de unidades homogéneas não necessariamente lucrativas. Concluímos, em geral, que são úteis e constituem um avanço importante, as informações obtidas através do DEA mas que outros métodos, designadamente rácios e análises de regressão, podem dar um contributo importante para complementar aquela análise.

New data on hoverflies (Diptera: Syrphidae) from the Azorean island Pico (Portugal)

The hoverfly fauna of the Azores currently comprises 23 species (Smit 2010), but the current state of knowledge concerning these species differs for each island. In the year 1938, R. Frey and R. Storå recorded the first seven hoverfly species on Pico Island (Frey 1945), and these very same ones were still mentioned by Rojo et al. (1997). Smit (2010) added one more species to this list (Table 1). In the summer of 2014, the author of this article sampled hoverflies on Pico Island in several habitats. In this paper, the results will be presented.

Agreement between data obtained from repeated interviews with a six-years interval

The objective of the study was to compare information collected through face-to-face interviews at first time and six years later in a city of Southeastern Brazil. In 1998, 32 mothers (N=32) of children aged 20 to 30 months answered a face-to-face interview with structured questions regarding their children's brushing habits. Six years later this same interview was repeated with the same mothers. Both interviews were compared for overall agreement, kappa and weighted kappa. Overall agreement between both interviews varied from 41 to 96%. Kappa values ranged from 0.00 to 0.65 (very bad to good) without any significant differences. The results showed lack of agreement when the same interview is conducted six years later, showing that the recall bias can be a methodological problem of interviews.

Spatial analysis of urban violence based on emergency room data

OBJECTIVE: To estimate the spatial intensity of urban violence events using wavelet-based methods and emergency room data. METHODS: Information on victims attended at the emergency room of a public hospital in the city of São Paulo, Southeastern Brazil, from January 1, 2002 to January 11, 2003 were obtained from hospital records. The spatial distribution of 3,540 events was recorded and a uniform random procedure was used to allocate records with incomplete addresses. Point processes and wavelet analysis technique were used to estimate the spatial intensity, defined as the expected number of events by unit area. RESULTS: Of all georeferenced points, 59% were accidents and 40% were assaults. There is a non-homogeneous spatial distribution of the events with high concentration in two districts and three large avenues in the southern area of the city of São Paulo. CONCLUSIONS: Hospital records combined with methodological tools to estimate intensity of events are useful to study urban violence. The wavelet analysis is useful in the computation of the expected number of events and their respective confidence bands for any sub-region and, consequently, in the specification of risk estimates that could be used in decision-making processes for public policies.

Modelo de data mining para detecção de tumores em exames de rastreio

Dissertação para obtenção do grau de Mestre em Engenharia Informática

On clustering interval data with different scales of measures : experimental results

This article is is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. Attribution-NonCommercial (CC BY-NC) license lets others remix, tweak, and build upon work non-commercially, and although the new works must also acknowledge & be non-commercial.

Hierarchical cluster analysis of groups of individuals : application to business data

3rd SMTDA Conference Proceedings, 11-14 June 2014, Lisbon Portugal.