Browsing by Author "Ribeiro, Ricardo"
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- A abordagem do técnico de radiologia na triagem ortopédica em urgência hospitalarPublication . Ribeiro, Ricardo; Matos, IsabelIntrodução - O presente trabalho de investigação tem como objectivo identificar o processo adoptado pelos técnicos de radiologia no desempenho das suas tarefas específicas da triagem ortopédica do referido hospital de Lisboa. Metodologia - Os dados foram recolhidos junto de um grupo de técnicos de radiologia da urgência de um Hospital na região de Lisboa, por meio de entrevistas semi-estruturadas realizadas a 11 indivíduos e analisados através da técnica da análise de conteúdo, utilizando como referencial os princípios bioéticos da autonomia dos profissionais. Resultados - No processo de análise, emergiram três categorias no atendimento da triagem ortopédica aos doentes: a realização do exame; a avaliação da triagem realizada pelos técnicos de radiologia; o papel dos técnicos de radiologia na triagem ortopédica. Conclusões - Este estudo permitiu concluir que o técnico de radiologia tem capacidade técnica de decisão na escolha das incidências radiológicas mais adequadas ao estado clínico do paciente, no contexto da triagem radiológica. O estudo revela a necessidade de formação nesta área especifica.
- An ultrasound based computer-aided diagnosis tool for steatosis detectionPublication . Ribeiro, Ricardo; Marinho, Rui; Sanches, JoãoLiver steatosis is a common disease usually associated with social and genetic factors. Early detection and quantification is important since it can evolve to cirrhosis. In this paper, a new computer-aided diagnosis (CAD) system for steatosis classification, in a local and global basis, is presented. Bayes factor is computed from objective ultrasound textural features extracted from the liver parenchyma. The goal is to develop a CAD screening tool, to help in the steatosis detection. Results showed an accuracy of 93.33%, with a sensitivity of 94.59% and specificity of 92.11%, using the Bayes classifier. The proposed CAD system is a suitable graphical display for steatosis classification.
- Automatic diagnosis of liver steatosis by ultrasound using autoregressive tissue characterizationPublication . Ribeiro, Ricardo; Sanches, JoãoLiver steatosis is mainly a textural abnormality of the hepatic parenchyma due to fat accumulation on the hepatic vesicles. Today, the assessment is subjectively performed by visual inspection. Here a classifier based on features extracted from ultrasound (US) images is described for the automatic diagnostic of this phatology. The proposed algorithm estimates the original ultrasound radio-frequency (RF) envelope signal from which the noiseless anatomic information and the textural information encoded in the speckle noise is extracted. The features characterizing the textural information are the coefficients of the first order autoregressive model that describes the speckle field. A binary Bayesian classifier was implemented and the Bayes factor was calculated. The classification has revealed an overall accuracy of 100%. The Bayes factor could be helpful in the graphical display of the quantitative results for diagnosis purposes.
- Chronic liver disease staging classification based on ultrasound, clinical and laboratorial dataPublication . Ribeiro, Ricardo; Marinho, Rui; Velosa, José; Ramalho, Fernando; Sanches, JoãoIn 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.
- Classification and staging of chronic liver disease from multimodal dataPublication . Ribeiro, Ricardo; Marinho, Rui; Sanches, JoãoChronic 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 paradigmPublication . Acharya, U. R.; Sree, S. V.; Ribeiro, Ricardo; Krishnamurthi, G.; Marinho, Rui; Sanches, João; Suri, J. S.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.
- Diffuse liver disease classification from ultrasound surface characterization, clinical and laboratorial dataPublication . Ribeiro, Ricardo; Marinho, Rui; Velosa, José; Ramalho, Fernando; Sanches, JoãoIn 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.
- Do presencial… à distância! Alinhar a mudança para garantir qualidade do ensinoPublication . Coelho, André; Maia-Matos, Mário; Abreu, Renato; Ribeiro, Ricardo; Manteigas, VítorObjetivo: Criar questões relevantes e o ambiente adequado para a realização de testes à distância. Sumário: 1. Alinhamento construtivista. 2. Avaliação formativa e sumativa em EaD. 3. Boas práticas na avaliação de estudantes em EaD. 4. Boas práticas para testes online em EaD. 5. Como reduzir a oportunidade de fraude académica em EaD.
- Efeitos fiscais do aumento da retribuição mínima garantidaPublication . Ribeiro, Ricardo; Silva, AmândioA presente dissertação inicia-se com uma análise à dicotomia de impostos diretos e indiretos, bem como os seus princípios, passando por uma verificação de como é que os governos, pela utilização da política fiscal, podem impulsionar o salário mínimo nacional, sem que para isso sejam postos em causa milhares de postos de trabalho, que acabariam por custar milhões de euros ao orçamento anual do Estado. A partir da análise do salário mínimo nacional, o seu posicionamento ao nível europeu e dos seus sucessivos aumentos desde 2015, propusemo-nos a estudar as consequências que esses aumentos possam provocar a nível orçamental, bem como o impacto provocado em tempos de recessão económica, como a de 2011 e a atual. É possível a Retribuição Mínima Mensal Garantida ser aumentada, sem que isso implique um acréscimo de custos para a entidade empregadora? Que mecanismos tem o Estado ao seu dispor e quanto é que isso lhe custaria? São algumas das perguntas que pretendemos responder ao longo desta dissertação.
- Escola Superior de Tecnologia da Saúde de Lisboa combate COVID-19 com EaDPublication . Coelho, André; Maia-Matos, Mário; Abreu, Renato; Ribeiro, Ricardo; Manteigas, VítorNo cumprimento das orientações das autoridades competentes relativamente à pandemia de COVID 19 a ESTeSL suspendeu as atividades letivas presenciais, passando os ciclos de estudos a funcionar em “Ensino a Distância”. Objetivos do GADMED: planear, implementar e monitorizar o processo do ensino a distância, no âmbito de um desenvolvimento estratégico; incentivar e apoiar a criação de cursos online de diferentes tipologias, nomeadamente MOOCs e webinários; promover formações de apoio e desenvolvimento do “Ensino a Distância”, adequadas para docentes e/ou estudantes.
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