Sos socorrista: sistemas para auxiliar equipe médica na tomada de decisão de emergência

• Ano de defesa: 2018
• Autor(a) principal: Silva, José Erico Gomes da
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal Rural do Semi-Árido; Brasil; Centro de Ciências Exatas e Naturais - CCEN; UFERSA; Programa de Pós-Graduação em Ciência da Computação
• Palavras-chave em Português: Emergência; E-Health; Inteligência Artificial; Urgência; Artificial Intelligence; Emergence; Urgency; CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO
• Link de acesso: https://repositorio.ufersa.edu.br/handle/prefix/1095

The information and communication technologies have, each day establishing themselves more in our daily life to the point that their absence would generate great impact on the whole of society. This is noticeable in the world of work, consumption and habits of the population. Faced with so many technological advances, health is one of the areas that greatly benefits from sensors, actuators, equipment, instruments, software and hardware aimed at the aid, prevention, health promotion and quality of life of the individual. The overcrowding of the Hospital Emergency Services is a problem that plagues health regarding humanized patient care in the context of emergencies, a fact that is aggravated by the high rate of accidents and violence. This highlights the poor performance of the health system as a whole, emphasizing mainly the low quality of care and the delay in diagnosis and treatment, especially in the context of emergencies and emergencies. Therefore, the objective of this work was the development of a system called "SOS Socorrista", which aims to assist the regulatory team in the process of attendance of urgency and emergency occurrences in decision making. “SOS Socorrista” is a multiplatform responsive and relies on the foundation of E-Health and artificial intelligence techniques for knowledge representation, useful for information processing and decision making. The questions raised during the course of this work, provided solutions to the issues addressed here, thus generating scientific knowledge. In addition, it was possible to verify that the system presented satisfactory performance, assisting the medical team in decision making with a 90% success rate