Real-time intelligent decision support and monitoring system of critical patients
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | https://hdl.handle.net/1822/78025 |
Resumo: | Intensive care units are places where patients’ vital signs are continuously monitored and recorded alongside a multiplicity of clinical parameters. The main goal of this work is to study and develop an intelligent system to promote new decision-making knowledge crucial to provide better treatment to the patient. This article presents the achieved goals; in particular, the system developed for monitoring the clinical data and, using data mining technologies, for predicting clinical events with great sensitivity (90–100%), including organ failure probability, read-missions, and sepsis. |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Real-time intelligent decision support and monitoring system of critical patientsSistema inteligente de apoio à decisão e monitorização de doentes críticos em tempo-realData miningIntelligent decision support systemIntensive medicineReal-time online learningIntensive care units are places where patients’ vital signs are continuously monitored and recorded alongside a multiplicity of clinical parameters. The main goal of this work is to study and develop an intelligent system to promote new decision-making knowledge crucial to provide better treatment to the patient. This article presents the achieved goals; in particular, the system developed for monitoring the clinical data and, using data mining technologies, for predicting clinical events with great sensitivity (90–100%), including organ failure probability, read-missions, and sepsis.Este trabalho foi apoiado por fundos nacionais – FCT – Fundação para a Ciência e a Tecnologia no âmbito do projeto FCOMP-01-0124-FEDER-022674 e está enquadrado no projeto de investigação financiado pela FCT: INTCare II – PTDC/EEI-SII/1302/2012Karger AGUniversidade do MinhoPortela, FilipeDos Santos, Manuel Filipe Vieira TorresAbelha, AntónioMachado, José ManuelSilva, Álvaro MoreiraMartins, Fernando Rua20172017-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/1822/78025engda Silva Portela, C. F., Vieira Torres dos Santos, M. F., da Silva Abelha, A. C., Machado, J. M., Moreira Silva, Á., & Rua Martins, F. (2017). Sistema inteligente de apoio à decisão e monitorização de doentes críticos em tempo-real. Portuguese Journal of Public Health, 35(3), 179-192. doi: 10.1159/0004861462504-31372504-314510.1159/000486146https://www.karger.com/Article/FullText/486146info: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:RCAAP2023-07-21T12:51:05Zoai:repositorium.sdum.uminho.pt:1822/78025Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T19:49:54.340426Repositório 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 |
Real-time intelligent decision support and monitoring system of critical patients Sistema inteligente de apoio à decisão e monitorização de doentes críticos em tempo-real |
title |
Real-time intelligent decision support and monitoring system of critical patients |
spellingShingle |
Real-time intelligent decision support and monitoring system of critical patients Portela, Filipe Data mining Intelligent decision support system Intensive medicine Real-time online learning |
title_short |
Real-time intelligent decision support and monitoring system of critical patients |
title_full |
Real-time intelligent decision support and monitoring system of critical patients |
title_fullStr |
Real-time intelligent decision support and monitoring system of critical patients |
title_full_unstemmed |
Real-time intelligent decision support and monitoring system of critical patients |
title_sort |
Real-time intelligent decision support and monitoring system of critical patients |
author |
Portela, Filipe |
author_facet |
Portela, Filipe Dos Santos, Manuel Filipe Vieira Torres Abelha, António Machado, José Manuel Silva, Álvaro Moreira Martins, Fernando Rua |
author_role |
author |
author2 |
Dos Santos, Manuel Filipe Vieira Torres Abelha, António Machado, José Manuel Silva, Álvaro Moreira Martins, Fernando Rua |
author2_role |
author author author author author |
dc.contributor.none.fl_str_mv |
Universidade do Minho |
dc.contributor.author.fl_str_mv |
Portela, Filipe Dos Santos, Manuel Filipe Vieira Torres Abelha, António Machado, José Manuel Silva, Álvaro Moreira Martins, Fernando Rua |
dc.subject.por.fl_str_mv |
Data mining Intelligent decision support system Intensive medicine Real-time online learning |
topic |
Data mining Intelligent decision support system Intensive medicine Real-time online learning |
description |
Intensive care units are places where patients’ vital signs are continuously monitored and recorded alongside a multiplicity of clinical parameters. The main goal of this work is to study and develop an intelligent system to promote new decision-making knowledge crucial to provide better treatment to the patient. This article presents the achieved goals; in particular, the system developed for monitoring the clinical data and, using data mining technologies, for predicting clinical events with great sensitivity (90–100%), including organ failure probability, read-missions, and sepsis. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017 2017-01-01T00:00:00Z |
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 |
https://hdl.handle.net/1822/78025 |
url |
https://hdl.handle.net/1822/78025 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
da Silva Portela, C. F., Vieira Torres dos Santos, M. F., da Silva Abelha, A. C., Machado, J. M., Moreira Silva, Á., & Rua Martins, F. (2017). Sistema inteligente de apoio à decisão e monitorização de doentes críticos em tempo-real. Portuguese Journal of Public Health, 35(3), 179-192. doi: 10.1159/000486146 2504-3137 2504-3145 10.1159/000486146 https://www.karger.com/Article/FullText/486146 |
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 |
Karger AG |
publisher.none.fl_str_mv |
Karger AG |
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 |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799133081895960576 |