title: Characterization of suicidal behaviour with self-organizing maps.
abstract: 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.
authors.affiliation: Department of Signal Theory and Communication, Universidad Carlos III de Madrid, Avenida Universidad 30, 28911 Madrid, Spain. jose@tsc.uc3m.es
authors.forename: José M
authors.initials: JM
authors.lastname: Leiva-Murillo
authors.forename: Jorge
authors.initials: J
authors.lastname: López-Castromán
authors.forename: Enrique
authors.initials: E
authors.lastname: Baca-García
mesh_terms: D000293:Adolescent; D000437:Alcoholism / Q000150:complications / Q000523:psychology; D001185:Artificial Intelligence; D002648:Child; D002649:Child Abuse / Q000523:psychology; D015331:Cohort Studies; D019295:Computational Biology; D006801:Humans; D007175:Impulsive Behavior / Q000150:complications / Q000523:psychology; D001523:Mental Disorders / Q000150:complications / Q000523:psychology; D017711:Nonlinear Dynamics; D012307:Risk Factors; D013405:Suicide / Q000523:psychology* / Q000706:statistics & numerical data; D013406:Suicide, Attempted / Q000523:psychology / Q000706:statistics & numerical data; D055815:Young Adult