Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/67830

TítuloPredicting resurgery in intensive care - a data mining approach
Autor(es)Peixoto, Ricardo
Ribeiro, Lisete
Portela, Filipe
Santos, Manuel
Rua, Fernando
Palavras-chaveData Mining
Classification
Interventions
Reinterventions
INTCare
Data2017
EditoraElsevier Science BV
RevistaProcedia Computer Science
Resumo(s)Every day the surgical interventions are associated with medicine, and the area of critical care medicine is no exception. The goal of this work is to assist health professionals in predicting these interventions. Thus, when the Data Mining techniques are well applied it is possible, with the help of medical knowledge, to predict whether a particular patient should or not should be re-operated upon the same problem. In this study, some aspects, such as heart disease and age, and some data classes were built to improve the models created. In addition, several scenarios were created, with the objective can predict the resurgery patients. According the primary objective, the resurgery patients prediction, the metric used was the sensitivity, obtaining an approximate result of 90%.
TipoArtigo em ata de conferência
URIhttps://hdl.handle.net/1822/67830
DOI10.1016/j.procs.2017.08.291
ISSN1877-0509
Versão da editorahttps://www.sciencedirect.com/science/article/pii/S1877050917317003
Arbitragem científicayes
AcessoAcesso aberto
Aparece nas coleções:CAlg - Artigos em livros de atas/Papers in proceedings

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