Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/2215

TitleOrgan failure diagnosis by artificial neural networks
Author(s)Silva, Álvaro
Cortez, Paulo
Santos, Manuel Filipe
Gomes, Lopes
Neves, José
KeywordsIntensive care medicine
Classification
Multilayer perceptrons
Out of range measurements
Sequential organ failure assessment
Issue dateSep-2003
PublisherACTA Press
CitationIASTED INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND APPLICATIONS (AIA 2003), 3, Benalmádena, 2003 - " Proceedings of the third IASTED International Conference on... ". Calgary : ACTA Press, 2003. p. 706-711.
Abstract(s)In recent years, Clinical Data Mining has gained an increasing acceptance by the research community, due to its potential to find answers that could extend life or give comfort to ill persons. In particular, the use of tools such as Artificial Neural Networks, which have been mostly used in classification tasks. The present work reports the adoption of these techniques for the prediction of organ dysfunction of Intensive Care Unit patients. The novelty of this approach is due to the use intermediate outcomes, defined by the Out of Range Measurements of four bedside monitored variables, which obtained an overall accuracy of 70%.
TypeConference paper
URIhttp://hdl.handle.net/1822/2215
Peer-Reviewedyes
AccessOpen access
Appears in Collections:CAlg - Artigos em livros de atas/Papers in proceedings
DSI - Engenharia da Programação e dos Sistemas Informáticos

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