39 resultados para body scaled information
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Mestrado em Intervenção Sócio-Organizacional na Saúde - Área de especialização: Políticas de Administração e Gestão de Serviços de Saúde
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Relatório de Estágio apresentado à Escola Superior de Educação de Lisboa para obtenção de grau de mestre em Ensino do 1.º e 2.º Ciclo do Ensino Básico
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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica
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Thesis to obtain the Master of Science Degree in Computer Science and Engineering
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Introduction: Alcohol consumption starts at an early age in Portuguese people. Health problems and risk behavior associated with excessive consumption can be prevented or highly reduced through effective school programs. Health professionals, such as biomedical scientists, (BSc), are important in promoting healthy lifestyles through the transmission of knowledge. Objective: Explore the role of the BSc in promoting health via intervention and clarification actions, (ICA), with 9th grade students from Agrupamento de Escolas da Portela e Moscavide (AEPM) and Visconde Juromenha (AEVJ); Verify the relationship between participating in the ICA and the level of knowledge acquired from it. Methods: Behaviors and beliefs concerning alcohol consumption and knowledge about the repercussions of it in the human body, mainly regarding the liver, were assessed by questionnaire. The questionnaire was completed before and after the ICA, by the control group (CG) and the study group (SG), respectively. The answers concerning knowledge were given points, later converted to a score from 0 to 100%. Data was analyzed applying descriptive statistics and the t-student test using SPSS 20.0. Results: After statistical analysis, it was found an average score of 48.8% for SG and 46.2% for CG. The difference between groups was statistically significant only in AEPM where ICA included a practical methodology (microscopic and macroscopic observation of pork livers), contrary to AEVJ. Conclusions: BSc intervention through ICA’s improves teenagers’ knowledge. Theoretical knowledge associated with practical approaches improves the retention of information and the development of a conscious behavior about the consumption of alcohol.
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Mestrado em Gestão e Avaliação de Tecnologias em Saúde
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Mestrado em Tecnologia de Diagnóstico e Intervenção Cardiovascular - Área de especialização: Ultrassonografia cardiovascular
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Mestrado em Radiações Aplicadas às Tecnologias da Saúde
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Feature discretization (FD) techniques often yield adequate and compact representations of the data, suitable for machine learning and pattern recognition problems. These representations usually decrease the training time, yielding higher classification accuracy while allowing for humans to better understand and visualize the data, as compared to the use of the original features. This paper proposes two new FD techniques. The first one is based on the well-known Linde-Buzo-Gray quantization algorithm, coupled with a relevance criterion, being able perform unsupervised, supervised, or semi-supervised discretization. The second technique works in supervised mode, being based on the maximization of the mutual information between each discrete feature and the class label. Our experimental results on standard benchmark datasets show that these techniques scale up to high-dimensional data, attaining in many cases better accuracy than existing unsupervised and supervised FD approaches, while using fewer discretization intervals.