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Authors: M. Domínguez 1 ; J. Aroba 2 ; J. G. Enríquez 1 ; I. Ramos 1 ; J. M. Lucena-Soto 3 and M. J. Escalona 1

Affiliations: 1 University of Seville, Spain ; 2 University of Huelva, Spain ; 3 Hospital Universitario Virgen del Rocío, Spain

ISBN: 978-989-758-027-7

Keyword(s): HIV, Virological Events, Prefurge, Unsupervised Learning.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Data Mining ; Databases and Information Systems Integration ; Enterprise Application Integration ; Enterprise Information Systems ; Information Systems Analysis and Specification ; Problem Solving ; Sensor Networks ; Signal Processing ; Soft Computing ; Software Engineering

Abstract: Virological events in HIV-infected patients can rise with no apparent reason. Therefore, when they appear, immunologists or medical doctors do not know whether they will produce other future virological events or they will entail relevant clinical consequences. This paper presents the results of applying Prefurge to HIV-infected patients’ clinical data, with the aim of obtaining rules and information about this set of clinical trials data that will relate these kinds of virological events.

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Paper citation in several formats:
Domínguez M., Aroba J., G. Enríquez J., Ramos I., M. Lucena-Soto J. and J. Escalona M. (2014). Advances in the Decision Making for Treatments of Chronic Patients Using Fuzzy Logic and Data Mining Techniques.In Proceedings of the 16th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-027-7, pages 325-330. DOI: 10.5220/0004969503250330

@conference{iceis14,
author={M. Domínguez and J. Aroba and J. G. Enríquez and I. Ramos and J. M. Lucena-Soto and M. J. Escalona},
title={Advances in the Decision Making for Treatments of Chronic Patients Using Fuzzy Logic and Data Mining Techniques},
booktitle={Proceedings of the 16th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2014},
pages={325-330},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004969503250330},
isbn={978-989-758-027-7},
}

TY - CONF

JO - Proceedings of the 16th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - Advances in the Decision Making for Treatments of Chronic Patients Using Fuzzy Logic and Data Mining Techniques
SN - 978-989-758-027-7
AU - Domínguez M.
AU - Aroba J.
AU - G. Enríquez J.
AU - Ramos I.
AU - M. Lucena-Soto J.
AU - J. Escalona M.
PY - 2014
SP - 325
EP - 330
DO - 10.5220/0004969503250330

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