Predict hourly patient discharge probability in intensive care units using Data Mining

The length of stay (LOS) is an important metric to manage hospital units since a correct prevision of the LOS can contribute to reduce costs and optimize resources. This metric become more fundamental in intensive care units (ICU) where controlling patient condition and predict clinical events is ve...

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Detalhes bibliográficos
Autor principal: Portela, Filipe (author)
Outros Autores: Veloso, Rui (author), Oliveira, Sérgio Manuel Costa (author), Santos, Manuel (author), Abelha, António (author), Machado, José Manuel (author), Silva, Álvaro (author), Rua, Fernando (author)
Formato: article
Idioma:eng
Publicado em: 2015
Assuntos:
Data mining
ICU
INTCare
LOS
Occupancy rate
Texto completo:http://hdl.handle.net/1822/51954
País:Portugal
Oai:oai:repositorium.sdum.uminho.pt:1822/51954

Texto Completo

http://hdl.handle.net/1822/51954

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