Submitted by Automa??o e Estat?stica (sst@bczm.ufrn.br) on 2017-10-18T20:24:43Z No. of bitstreams: 1 YaskaraYgaraMenescalPintoFernandes_TESE.pdf: 2632244 bytes, checksum: a599e082c85a496e5b7fd4d617b18831 (MD5) / Approved for entry into archive by Arlan Eloi Leite Silva (eloihistoriador@yahoo.com.br) on 2017-10-19T22:59:23Z (GMT) No. of bitstreams: 1 YaskaraYgaraMenescalPintoFernandes_TESE.pdf: 2632244 bytes, checksum: a599e082c85a496e5b7fd4d617b18831 (MD5) / Made available in DSpace on 2017-10-19T22:59:23Z (GMT). No. of bitstreams: 1 YaskaraYgaraMenescalPintoFernandes_TESE.pdf: 2632244 bytes, checksum: a599e082c85a496e5b7fd4d617b18831 (MD5) Previous issue date: 2017-09-06 / De acordo com a Organiza??o Mundial da Sa?de, cerca de 9,2% dos 28 milh?es dos rec?m-nascidos em todo o mundo s?o natimortos. Al?m disso, cerca de 358 mil mulheres morreram devido a complica??es com a gravidez em 2015. Parte dessas mortes poderiam ter sido evitadas com a melhoria na assist?ncia pr?-natal e agilidade no reconhecimento de problemas na gesta??o. Assim, esfor?os t?m sido realizados para disponibilizar os servi?os de sa?de com tecnologias que possam contribuir para o melhor acesso ? informa??o e aux?lio ? tomada de decis?o. ? neste contexto que a presente tese apresenta uma arquitetura para automatizar o processo classifica??o e encaminhamento de gestantes entre as unidades b?sica de sa?de e o hospital de refer?ncia atrav?s da plataforma de Telessa?de. A arquitetura de Telessa?de foi desenvolvida atrav?s de tr?s componentes: componente de aquisi??o de dados, respons?vel pela coleta e inser??o de dados; componente de processamento, ? o n?cleo da arquitetura, implementada atrav?s de sistemas especialistas para a classificar o risco gestacional; e o componente de p?s-processamento, respons?vel pela entrega e an?lise dos casos. Foram realizados os testes de aceita??o, teste de precis?o do sistema baseado em regras e teste de desempenho. Para a realiza??o dos testes foram utilizados 1380 formul?rios de encaminhamentos de situa??es reais. Diante dos resultados obtidos com a an?lise de dados reais, a arquitetura desenvolvida, chamada Eileithyia, atende aos requisitos de auxiliar especialistas m?dicos na classifica??o do risco gestacional, diminuindo os custos de transporte e o inconveniente do deslocamento das mulheres gr?vidas pelo Estado. / According to the World Health Organization, about 9.2% of the 28 million newborns worldwide are stillborn. Besides, about 358,000 women died due to complications related to pregnancy in 2015. Part of these deaths could have been avoided with improving prenatal care agility to recognize problems during pregnancy. Based on that, many efforts have been made to provide technologies that can contribute to offer better access to information and assist in decision-making. In this context, this work presents an architecture to automate the classification and referral process of pregnant women between the basic health units and the referral hospital through a Telehealth platform. The Telehealth architecture was developed in three components: The data acquisition component, responsible for collecting and inserting data; the data processing component, which is the core of the architecture implemented using expert systems to classify gestational risk; and the post-processing component, in charge of the delivery and analysis of cases. Acceptance test, system accuracy test based on rules and performance test were realized. For the tests, 1,380 referral forms of real situations were used. On the results obtained with real data analysis, the developed architecture, called Eileithyia, meets the requirements to assist medical specialists on gestational risk classification which decreases the inconvenience of pregnant women displacement and the resulting costs.