995 resultados para Povo da rua
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Dissertação de mestrado em Direito Administrativo
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Este trabalho traz uma reflexão sobre a Educação Indígena no Brasil, com base em dados históricos e estatísticos, de forma a melhor compreender e adequar o currículo escolar às diferentes realidades contextuais. Compreender a educação dos índios nos dias atuais requer uma breve recomposição da historicidade desse povo. Exige o reconhecimento dos 500 anos de história do Brasil, onde os povos indígenas foram expostos a um violento processo civilizatório que implicou em transformações na cultura e identidade desses povos. Mesmo com o desenvolvimento de política de proteção ao índio e com leis voltadas para lhes assegurar a cidadania, observa-se um quadro de exclusão social e cultural.. Entretanto, a cidadania indígena vem sendo negada ao mesmo tempo em que se legitimam discursos de respeito à diversidade e a diferença. A Escola indígena específica e diferenciada surge como um projeto pensado pelos movimentos indígenas com a finalidade de reparar a lacuna existente na história da educação nacional.
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Dissertação de mestrado integrado em Arquitectura
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OBJETIVO: Realizar revisão sistemática para avaliar a adesão medicamentosa ao tratamento em pacientes do espectro esquizofrênico. MÉTODO: As buscas dos artigos foram conduzidas nas seguintes bases de dados: PubMed/Medline, Lilacs, SciELO e PePSIC, considerando artigos publicados entre 2001 e 2010. Na estratégia de busca, foram utilizados descritores de acordo com sua definição no DeCS e no MeSH: "schizophrenia" and "patient adherence" or "patient compliance" or "medication adherence". As correspondências em português e espanhol foram respectivamente "esquizofrenia/esquizofrenia" e "cooperação do paciente/cooperácion del paciente" ou "adesão à medicação/cumplimiento de lá medicación". Também foram realizadas buscas manuais nas referências dos artigos selecionados. RESULTADOS: A busca bibliográfica resultou em 1.692 artigos. Contudo, apenas 54 preencheram os critérios para compor esta revisão. CONCLUSÕES: A maioria dos estudos sobre o tema foi realizada em países desenvolvidos, prejudicando a aplicação dos achados à nossa realidade. As taxas da adesão e os métodos utilizados para avaliação variaram bastante, porém os fatores associados à não adesão se repetiram, como falta de insight, comorbidade com uso de substâncias psicoativas, falta de apoio social, efeitos colaterais da medicação, comportamento violento, situação de rua, tentativa de suicídio, entre outros. Assim sendo, há necessidade da realização de mais estudos nacionais para investigar potenciais variáveis associadas a não adesão e suas consequências para a população estudada.
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"Lecture notes in computer science series", ISSN 0302-9743, vol. 9121
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Dissertação de mestrado em Direitos Humanos
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Dissertação de mestrado em Sociologia (área de especialização em Organizações e Trabalho)
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Mechanical Ventilation is an artificial way to help a Patient to breathe. This procedure is used to support patients with respiratory diseases however in many cases it can provoke lung damages, Acute Respiratory Diseases or organ failure. With the goal to early detect possible patient breath problems a set of limit values was defined to some variables monitored by the ventilator (Average Ventilation Pressure, Compliance Dynamic, Flow, Peak, Plateau and Support Pressure, Positive end-expiratory pressure, Respiratory Rate) in order to create critical events. A critical event is verified when a patient has a value higher or lower than the normal range defined for a certain period of time. The values were defined after elaborate a literature review and meeting with physicians specialized in the area. This work uses data streaming and intelligent agents to process the values collected in real-time and classify them as critical or not. Real data provided by an Intensive Care Unit were used to design and test the solution. In this study it was possible to understand the importance of introduce critical events for Mechanically Ventilated Patients. In some cases a value is considered critical (can trigger an alarm) however it is a single event (instantaneous) and it has not a clinical significance for the patient. The introduction of critical events which crosses a range of values and a pre-defined duration contributes to improve the decision-making process by decreasing the number of false positives and having a better comprehension of the patient condition.
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This research work explores a new way of presenting and representing information about patients in critical care, which is the use of a timeline to display information. This is accomplished with the development of an interactive Pervasive Patient Timeline able to give to the intensivists an access in real-time to an environment containing patients clinical information from the moment in which the patients are admitted in the Intensive Care Unit (ICU) until their discharge This solution allows the intensivists to analyse data regarding vital signs, medication, exams, data mining predictions, among others. Due to the pervasive features, intensivists can have access to the timeline anywhere and anytime, allowing them to make decisions when they need to be made. This platform is patient-centred and is prepared to support the decision process allowing the intensivists to provide better care to patients due the inclusion of clinical forecasts.
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The decision support models in intensive care units are developed to support medical staff in their decision making process. However, the optimization of these models is particularly difficult to apply due to dynamic, complex and multidisciplinary nature. Thus, there is a constant research and development of new algorithms capable of extracting knowledge from large volumes of data, in order to obtain better predictive results than the current algorithms. To test the optimization techniques a case study with real data provided by INTCare project was explored. This data is concerning to extubation cases. In this dataset, several models like Evolutionary Fuzzy Rule Learning, Lazy Learning, Decision Trees and many others were analysed in order to detect early extubation. The hydrids Decision Trees Genetic Algorithm, Supervised Classifier System and KNNAdaptive obtained the most accurate rate 93.2%, 93.1%, 92.97% respectively, thus showing their feasibility to work in a real environment.
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The needs of reducing human error has been growing in every field of study, and medicine is one of those. Through the implementation of technologies is possible to help in the decision making process of clinics, therefore to reduce the difficulties that are typically faced. This study focuses on easing some of those difficulties by presenting real-time data mining models capable of predicting if a monitored patient, typically admitted in intensive care, will need to take vasopressors. Data Mining models were induced using clinical variables such as vital signs, laboratory analysis, among others. The best model presented a sensitivity of 94.94%. With this model it is possible reducing the misuse of vasopressors acting as prevention. At same time it is offered a better care to patients by anticipating their treatment with vasopressors.
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Patient blood pressure is an important vital signal to the physicians take a decision and to better understand the patient condition. In Intensive Care Units is possible monitoring the blood pressure due the fact of the patient being in continuous monitoring through bedside monitors and the use of sensors. The intensivist only have access to vital signs values when they look to the monitor or consult the values hourly collected. Most important is the sequence of the values collected, i.e., a set of highest or lowest values can signify a critical event and bring future complications to a patient as is Hypotension or Hypertension. This complications can leverage a set of dangerous diseases and side-effects. The main goal of this work is to predict the probability of a patient has a blood pressure critical event in the next hours by combining a set of patient data collected in real-time and using Data Mining classification techniques. As output the models indicate the probability (%) of a patient has a Blood Pressure Critical Event in the next hour. The achieved results showed to be very promising, presenting sensitivity around of 95%.
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Dissertação de mestrado em Português Língua Não Materna – Língua Estrangeira / Língua Segunda
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Dissertação apresentada na Universidade de Lisboa - Faculdade de Arquitetura, para obtenção do Grau de Mestre em Arquitetura.
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Dissertação apresentada na Universidade de Lisboa - Faculdade de Arquitetura, para obtenção do Grau de Mestre em Arquitetura.