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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Bibliographic Details
Main Author: Portela, Filipe (author)
Other Authors: Santos, Manuel Filipe (author), Machado, José Manuel (author), Abelha, António (author), Silva, Álvaro (author), Rua, Fernando (author)
Format: article
Language:eng
Published: 2013
Subjects:
Intensive care
Data quality
Real-time
Intelligent decision support
INTCare
Online Access:http://hdl.handle.net/1822/23558
Country:Portugal
Oai:oai:repositorium.sdum.uminho.pt:1822/23558
Description
Summary: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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