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Computational and Mathematical Methods in Medicine
Volume 2013 (2013), Article ID 136743, 9 pages
Research Article

Characterization of Suicidal Behaviour with Self-Organizing Maps

1Department of Signal Theory and Communication, Universidad Carlos III de Madrid, Avenida Universidad 30, 28911 Madrid, Spain
2Department of Psychiatry, Fundación Jiménez Díaz, Avenida Reyes Católicos 2, 28040 Madrid, Spain
3Centre Hospitalier Regional Universitaire de Montpellier, France

Received 30 November 2012; Revised 5 March 2013; Accepted 6 March 2013

Academic Editor: Reinoud Maex

Copyright © 2013 José M. Leiva-Murillo et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The study of the variables involved in suicidal behavior is important from a social, medical, and economical point of view. Given the high number of potential variables of interest, a large population of subjects must be analysed in order to get conclusive results. In this paper, we describe a method based on self-organizing maps (SOMs) for finding the most relevant variables even when their relation to suicidal behavior is strongly nonlinear. We have applied the method to a cohort with more than 8,000 subjects and 600 variables and discovered four groups of variables involved in suicidal behavior. According to the results, there are four main groups of risk factors that characterize the population of suicide attempters: mental disorders, alcoholism, impulsivity, and childhood abuse. The identification of specific subpopulations of suicide attempters is consistent with current medical knowledge and may provide a new avenue of research to improve the management of suicidal cases.