Rating organ failure via adverse events using data mining in the intensive care unit

Detalhes bibliográficos
Autor(a) principal: Silva, Álvaro
Data de Publicação: 2008
Outros Autores: Cortez, Paulo, Santos, Manuel Filipe, Gomes, Lopes, Neves, José
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/1822/8015
Resumo: 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.
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spelling Rating organ failure via adverse events using data mining in the intensive care unitAdverse eventArtificial neural networkCritical careData miningMultinomial logistic regressionOrgan failure assessmentartificial neural networksScience & TechnologyThe 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.FRICEBIOMED - projecto BMH4-CT96-0817, EURICUS IIFundação para a Ciência ea Tecnologia (FCT) - projecto PTDC/EIA/72819/2006.ElsevierUniversidade do MinhoSilva, ÁlvaroCortez, PauloSantos, Manuel FilipeGomes, LopesNeves, José20082008-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/1822/8015eng"Artificial Intelligence in Medicine". ISSN 0933-3657. 43:3 (Jul. 2008) 179--193.0933-365710.1016/j.artmed.2008.03.01018486459http://www.sciencedirect.com/science/journal/09333657info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-21T12:34:59Zoai:repositorium.sdum.uminho.pt:1822/8015Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T19:30:48.790867Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Rating organ failure via adverse events using data mining in the intensive care unit
title Rating organ failure via adverse events using data mining in the intensive care unit
spellingShingle Rating organ failure via adverse events using data mining in the intensive care unit
Silva, Álvaro
Adverse event
Artificial neural network
Critical care
Data mining
Multinomial logistic regression
Organ failure assessment
artificial neural networks
Science & Technology
title_short Rating organ failure via adverse events using data mining in the intensive care unit
title_full Rating organ failure via adverse events using data mining in the intensive care unit
title_fullStr Rating organ failure via adverse events using data mining in the intensive care unit
title_full_unstemmed Rating organ failure via adverse events using data mining in the intensive care unit
title_sort Rating organ failure via adverse events using data mining in the intensive care unit
author Silva, Álvaro
author_facet Silva, Álvaro
Cortez, Paulo
Santos, Manuel Filipe
Gomes, Lopes
Neves, José
author_role author
author2 Cortez, Paulo
Santos, Manuel Filipe
Gomes, Lopes
Neves, José
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Universidade do Minho
dc.contributor.author.fl_str_mv Silva, Álvaro
Cortez, Paulo
Santos, Manuel Filipe
Gomes, Lopes
Neves, José
dc.subject.por.fl_str_mv Adverse event
Artificial neural network
Critical care
Data mining
Multinomial logistic regression
Organ failure assessment
artificial neural networks
Science & Technology
topic Adverse event
Artificial neural network
Critical care
Data mining
Multinomial logistic regression
Organ failure assessment
artificial neural networks
Science & Technology
description 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.
publishDate 2008
dc.date.none.fl_str_mv 2008
2008-01-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/1822/8015
url http://hdl.handle.net/1822/8015
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv "Artificial Intelligence in Medicine". ISSN 0933-3657. 43:3 (Jul. 2008) 179--193.
0933-3657
10.1016/j.artmed.2008.03.010
18486459
http://www.sciencedirect.com/science/journal/09333657
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv
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