Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/8015
Título: | Rating organ failure via adverse events using data mining in the intensive care unit |
Autor(es): | Silva, Álvaro Cortez, Paulo Santos, Manuel Filipe Gomes, Lopes Neves, José |
Palavras-chave: | Adverse event Artificial neural network Critical care Data mining Multinomial logistic regression Organ failure assessment artificial neural networks |
Data: | 2008 |
Editora: | Elsevier 1 |
Revista: | Artificial Intelligence in Medicine |
Citação: | "Artificial Intelligence in Medicine". ISSN 0933-3657. 43:3 (Jul. 2008) 179--193. |
Resumo(s): | The main intensive care unit (ICU) goal is to avoid or reverse the organ failure process by adopting a timely intervention. Within this context, early identification of organ impairment is a key issue. The sequential organ failure assessment (SOFA) is an expert-driven score that is widely used in European ICUs to quantify organ disorder. This work proposes a complementary data-driven approach based on adverse events, defined from commonly monitored biometrics. The aim is to 8. study the impact of these events when predicting the risk of ICU organ failure. |
Tipo: | Artigo |
URI: | https://hdl.handle.net/1822/8015 |
DOI: | 10.1016/j.artmed.2008.03.010 |
ISSN: | 0933-3657 |
Versão da editora: | http://www.sciencedirect.com/science/journal/09333657 |
Arbitragem científica: | yes |
Acesso: | Acesso aberto |
Aparece nas coleções: | CAlg - Artigos em revistas internacionais / Papers in international journals DSI - Engenharia da Programação e dos Sistemas Informáticos |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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sofa3.pdf | main article | 1,5 MB | Adobe PDF | Ver/Abrir |