Rating organ failure via adverse events using data mining in the intensive care unit
Autor(a) principal: | |
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Data de Publicação: | 2008 |
Outros Autores: | , , , |
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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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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1799132813474136064 |