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Authors: Filipe Portela 1 ; Manuel Filipe Santos 1 ; Álvaro Silva 2 ; José Machado 3 ; António Abelha 3 and Fernando Rua 2

Affiliations: 1 Centro Algoritmi and Universidade do Minho, Portugal ; 2 Hospital Santo António, Portugal ; 3 Universidade do Minho, Portugal

ISBN: 978-989-8565-39-6

Keyword(s): Data Mining, Real time, Intelligent Decision Support Systems, Intensive Medicine.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Computational Intelligence ; Data Mining ; Databases and Information Systems Integration ; Enterprise Information Systems ; Evolutionary Computing ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Machine Learning ; Sensor Networks ; Signal Processing ; Soft Computing ; Symbolic Systems

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 en gineering process and achieved results, in terms of the performance attained, will be presented. (More)

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Paper citation in several formats:
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

@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},
}

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

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