@article{ref1,
title="Method to identify and predict suicide risk profiles of adolescents using techniques of conglomerate analysis and artificial neural network",
journal="Revista AVFT: Archivos venezolanos de farmacología y terapéutica",
year="2019",
author="Reyes-Ruiz, L. and Granadillo, E.J.L.H. and Alvarado, F.A.C.",
volume="38",
number="3",
pages="115-120",
abstract="This article presents the profiles of suicide risk in 119 adolescent high school students of public schools of the department of Atlántico. As a theoretical basis, the literature associated with the evaluation of suicide risk, the analysis of conglomerates and the artificial neural networks were used. For the above, information was taken related to suicidal risk factors, hopelessness, ideation, isolation and family support. As a result, a method was developed to identify, assess and predict suicide risk profiles in adolescents. It is concluded that the cluster analysis showed favorable conditions to classify 4 characteristic profiles of suicide risk and artificial neural networks with a capacity to predict with a 95.5% probability of correct classification. © 2019, Sociedad Venezolana de Farmacologia y de Farmacologia Clinica y Terapeutica. All rights reserved.<p /><p>Language: es</p>",
language="es",
issn="0798-0264",
doi="",
url="http://dx.doi.org/"
}