Real-time decision support in intensive medicine: an intelligent approach for monitoring data quality

Detalhes bibliográficos
Autor(a) principal: Portela, Filipe
Data de Publicação: 2013
Outros Autores: Santos, Manuel Filipe, Machado, José Manuel, Abelha, António, Silva, Álvaro, Rua, Fernando
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Texto Completo: http://hdl.handle.net/1822/23558
Resumo: Intensive Medicine is an area where big amounts of data are generated every day. The process to obtain knowledge from these data is extremely difficult and sometimes dangerous. The main obstacles of this process are the number of data collected manually and the quality of the data collected automatically. Information quality is a major constrain to the success of Intelligent Decision Support Systems (IDSS). This is the case of INTCare an IDSS which operates in real-time. Data quality needs to be ensured in a continuous way. The quality must be assured essentially in the data acquisition process and in the evaluation of the results obtained from data mining models. To automate this process a set of intelligent agents have been developed to perform a set of data quality tasks. This paper explores the data quality issues in IDSS and presents an intelligent approach for monitoring the data quality in INTCare system.
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spelling Real-time decision support in intensive medicine: an intelligent approach for monitoring data qualityIntensive careData qualityReal-timeIntelligent decision supportINTCareIntensive Medicine is an area where big amounts of data are generated every day. The process to obtain knowledge from these data is extremely difficult and sometimes dangerous. The main obstacles of this process are the number of data collected manually and the quality of the data collected automatically. Information quality is a major constrain to the success of Intelligent Decision Support Systems (IDSS). This is the case of INTCare an IDSS which operates in real-time. Data quality needs to be ensured in a continuous way. The quality must be assured essentially in the data acquisition process and in the evaluation of the results obtained from data mining models. To automate this process a set of intelligent agents have been developed to perform a set of data quality tasks. This paper explores the data quality issues in IDSS and presents an intelligent approach for monitoring the data quality in INTCare system.Fundação para a Ciência e a Tecnologia (FCT)EtpublishingUniversidade do MinhoPortela, FilipeSantos, Manuel FilipeMachado, José ManuelAbelha, AntónioSilva, ÁlvaroRua, Fernando2013-032013-03-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/1822/23558eng2301-3796info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-05-11T04:23:57Zoai:repositorium.sdum.uminho.pt:1822/23558Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T14:47:17.180417Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Real-time decision support in intensive medicine: an intelligent approach for monitoring data quality
title Real-time decision support in intensive medicine: an intelligent approach for monitoring data quality
spellingShingle Real-time decision support in intensive medicine: an intelligent approach for monitoring data quality
Portela, Filipe
Intensive care
Data quality
Real-time
Intelligent decision support
INTCare
title_short Real-time decision support in intensive medicine: an intelligent approach for monitoring data quality
title_full Real-time decision support in intensive medicine: an intelligent approach for monitoring data quality
title_fullStr Real-time decision support in intensive medicine: an intelligent approach for monitoring data quality
title_full_unstemmed Real-time decision support in intensive medicine: an intelligent approach for monitoring data quality
title_sort Real-time decision support in intensive medicine: an intelligent approach for monitoring data quality
author Portela, Filipe
author_facet Portela, Filipe
Santos, Manuel Filipe
Machado, José Manuel
Abelha, António
Silva, Álvaro
Rua, Fernando
author_role author
author2 Santos, Manuel Filipe
Machado, José Manuel
Abelha, António
Silva, Álvaro
Rua, Fernando
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv Universidade do Minho
dc.contributor.author.fl_str_mv Portela, Filipe
Santos, Manuel Filipe
Machado, José Manuel
Abelha, António
Silva, Álvaro
Rua, Fernando
dc.subject.por.fl_str_mv Intensive care
Data quality
Real-time
Intelligent decision support
INTCare
topic Intensive care
Data quality
Real-time
Intelligent decision support
INTCare
description Intensive Medicine is an area where big amounts of data are generated every day. The process to obtain knowledge from these data is extremely difficult and sometimes dangerous. The main obstacles of this process are the number of data collected manually and the quality of the data collected automatically. Information quality is a major constrain to the success of Intelligent Decision Support Systems (IDSS). This is the case of INTCare an IDSS which operates in real-time. Data quality needs to be ensured in a continuous way. The quality must be assured essentially in the data acquisition process and in the evaluation of the results obtained from data mining models. To automate this process a set of intelligent agents have been developed to perform a set of data quality tasks. This paper explores the data quality issues in IDSS and presents an intelligent approach for monitoring the data quality in INTCare system.
publishDate 2013
dc.date.none.fl_str_mv 2013-03
2013-03-01T00:00:00Z
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dc.language.iso.fl_str_mv eng
language eng
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dc.publisher.none.fl_str_mv Etpublishing
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repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
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