914 resultados para Part-time Work
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Dissertação de mestrado em Sociologia da Infância
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Dissertação de mestrado em Ciências da Comunicação (área de especialização em Informação e Jornalismo)
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Dissertação de mestrado em História
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Dissertação de mestrado em Ciências da Comunicação (área de especialização em Informação e Jornalismo)
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Relatório de estágio de mestrado em Ensino de Música
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Relatório de estágio de mestrado em Ensino do Português no 3.º Ciclo do Ensino Básico e no Ensino Secundário e do Espanhol nos Ensinos Básico e Secundário
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Dissertação de mestrado em Estudos da Criança (área de especialização em Integração Curricular e Inovação Educativa)
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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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Hospitals have multiple data sources, such as embedded systems, monitors and sensors. The number of data available is increasing and the information are used not only to care the patient but also to assist the decision processes. The introduction of intelligent environments in health care institutions has been adopted due their ability to provide useful information for health professionals, either in helping to identify prognosis or also to understand patient condition. Behind of this concept arises this Intelligent System to track patient condition (e.g. critic events) in health care. This system has the great advantage of being adaptable to the environment and user needs. The system is focused in identifying critic events from data streaming (e.g. vital signs and ventilation) which is particularly valuable for understanding the patient’s condition. This work aims to demonstrate the process of creating an intelligent system capable of operating in a real environment using streaming data provided by ventilators and vital signs monitors. Its development is important to the physician because becomes possible crossing multiple variables in real-time by analyzing if a value is critic or not and if their variation has or not clinical importance.
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Tese de Doutoramento em Engenharia Civil (área de especialização em Engenharia de Estruturas).
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Dissertação de mestrado integrado em Arquitectura (área de especialização em Cidade e Território)