Data Mining for Real-Time Intelligent Decision Support System in Intensive Care Medicine

Filipe Portela, Manuel Filipe Santos, Álvaro Silva, José Machado, António Abelha, Fernando Rua

2013

Abstract

The introduction of Intelligent Decision Support Systems (IDSS) in critical areas like Intensive Medicine is a complex and difficult process. The professionals of Intensive Care Units (ICU) haven’t much time to register data because the direct care to the patients is always mandatory. In order to help doctors in the decision making process, the INTCare system has been deployed in the ICU of Centro Hospitalar of Porto, Portugal. INTCare is an IDSS that makes use of data mining models to predict the outcome and the organ failure probability for the ICU patients. This paper introduces the work carried out in order to automate the processes of data acquisition and data mining. The main goal of this work is to reduce significantly the manual efforts of the staff in the ICU. All the processes are autonomous and are executed in real-time. In particular, Decision Trees, Support Vector Machines and Naïve Bayes were used with online data to continuously adapt the predictive models. The data engineering process and achieved results, in terms of the performance attained, will be presented.

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Paper Citation


in Harvard Style

Portela F., Santos M., Silva Á., Machado J., Abelha A. and Rua F. (2013). Data Mining for Real-Time Intelligent Decision Support System in Intensive Care Medicine . In Proceedings of the 5th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-8565-39-6, pages 270-276. DOI: 10.5220/0004253702700276


in Bibtex Style

@conference{icaart13,
author={Filipe Portela and Manuel Filipe Santos and Álvaro Silva and José Machado and António Abelha and Fernando Rua},
title={Data Mining for Real-Time Intelligent Decision Support System in Intensive Care Medicine},
booktitle={Proceedings of the 5th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2013},
pages={270-276},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004253702700276},
isbn={978-989-8565-39-6},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 5th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - Data Mining for Real-Time Intelligent Decision Support System in Intensive Care Medicine
SN - 978-989-8565-39-6
AU - Portela F.
AU - Santos M.
AU - Silva Á.
AU - Machado J.
AU - Abelha A.
AU - Rua F.
PY - 2013
SP - 270
EP - 276
DO - 10.5220/0004253702700276