Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/21711
Título: | Data mining predictive models for pervasive intelligent decision support in intensive care medicine |
Autor(es): | Portela, Filipe Pinto, Filipe Santos, Manuel Filipe |
Palavras-chave: | Data mining KDD Real time Pervasive IDSS Intensive care Intelligent decision support system |
Data: | 2012 |
Resumo(s): | The introduction of an Intelligent Decision Support System (IDSS) in a critical area like the Intensive Medicine is a complex and difficult process. In this area, their professionals don’t have much time to document the cases, because the patient direct care is always first. With the objective to reduce significantly the manual records and, enabling, at the same time, the possibility of developing an IDSS which can help in the decision making process, all data acquisition process and knowledge discovery in database phases were automated. From the data acquisition to the knowledge discovering, the entire process is autonomous and executed in real-time. On-line induced data mining models were used to predict organ failure and outcome. Preliminary results obtained with a limited population of patients showed that this approach can be applied successfully. |
Tipo: | Artigo em ata de conferência |
URI: | https://hdl.handle.net/1822/21711 |
ISBN: | 9789898565310 |
Arbitragem científica: | yes |
Acesso: | Acesso aberto |
Aparece nas coleções: | DSI - Engenharia e Gestão de Sistemas de Informação |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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KMIS_80_Paper.pdf | 405,92 kB | Adobe PDF | Ver/Abrir |