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

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 automati...

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Detalhes bibliográficos
Autor principal: Portela, Filipe (author)
Outros Autores: Santos, Manuel Filipe (author), Machado, José Manuel (author), Abelha, António (author), Silva, Álvaro (author), Rua, Fernando (author)
Formato: article
Idioma:eng
Publicado em: 2013
Assuntos:
Intensive care
Data quality
Real-time
Intelligent decision support
INTCare
Texto completo:http://hdl.handle.net/1822/23558
País:Portugal
Oai:oai:repositorium.sdum.uminho.pt:1822/23558
Descrição
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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