Real-time intelligent decision support in intensive medicine

Daily, a great amount of data that is gathered in intensive care units, which makes intensive medicine a very attractive field for applying knowledge discovery in databases. Previously unknown knowledge can be extracted from that data in order to create prediction and decision models. The challenge...

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Detalhes bibliográficos
Autor principal: Portela, Filipe (author)
Outros Autores: Santos, Manuel Filipe (author), Silva, Alvaro (author), Rua, Fernando (author), Vilas Boas, Marta (author), Neves, José (author)
Formato: conferencePaper
Idioma:eng
Publicado em: 2010
Assuntos:
Texto completo:http://hdl.handle.net/1822/33160
País:Portugal
Oai:oai:repositorium.sdum.uminho.pt:1822/33160
Descrição
Resumo:Daily, a great amount of data that is gathered in intensive care units, which makes intensive medicine a very attractive field for applying knowledge discovery in databases. Previously unknown knowledge can be extracted from that data in order to create prediction and decision models. The challenge is to perform those tasks in real-time, in order to assist the doctors in the decision making process. The Data Mining models should be continuously assessed and optimized, if necessary, to maintain a certain accuracy. In this paper we present the INTCare system, an intelligent decision support system for intensive medicine and the way it was adapted to the new requirements. Some preliminary results are analysed and discussed.