Evolutionary fuzzy rule extraction for subgroup discovery in a psychiatric emergency department

  • Authors:

  • C. J. Carmona;P. González;M. J. del Jesus;M. Navío-Acosta;L. Jiménez-Trevino

  • Affiliations:

  • University of Jaen, Department of Computer Science, 23071, Jaen, Spain;University of Jaen, Department of Computer Science, 23071, Jaen, Spain;University of Jaen, Department of Computer Science, 23071, Jaen, Spain;Hospital Universitario 12 de Octubre, CIBERSAM, Madrid, Spain;University of Oviedo, CIBERSAM, Department of Psychiatry, Oviedo, Spain

  • Venue:
  • Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special Issue on Evolutionary Fuzzy Systems
  • Year:
  • 2011

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Abstract

This paper describes the application of evolutionary fuzzy systems for subgroup discovery to a medical problem, the study on the type of patients who tend to visit the psychiatric emergency department in a given period of time of the day. In this problem, the objective is to characterise subgroups of patients according to their time of arrival at the emergency department. To solve this problem, several subgroup discovery algorithms have been applied to determine which of them obtains better results. The multiobjective evolutionary algorithm MESDIF for the extraction of fuzzy rules obtains better results and so it has been used to extract interesting information regarding the rate of admission to the psychiatric emergency department.