Prediction of suicidal behaviors in hospitalized children and adolescents in middle-income countries: a case study of Brazil

• Isis F. Carvalho Federal University of Minas Gerais
• Debora Miranda Federal University of Minas Gerais
• Ana Paula Couto da Silva Federal University of Minas Gerais
• Anisio M. Lacerda Federal University of Minas Gerais
• Wagner Meira Jr. Federal University of Minas Gerais
• Marco A. Romano-Silva Federal University of Minas Gerais
• Maria Carolina Lobato Federal University of Minas Gerais
• Gisele L. Pappa Federal University of Minas Gerais

DOI: https://doi.org/10.5753/eniac.2023.234861

Abstract

Suicide is the first leading cause of death among children and adolescents worldwide. Predictors of suicide-related behaviours might help in the task of intervening to avoid or monitor future suicide risks. In this paper, a sample of individuals who were taken to a Child Psychiatry Facility in Brazil was analyzed. Machine learning algorithms were used to generate models for predicting suicidal behaviour, and the features that better explain this complex behaviour were also analyzed. Results show a sensitivity of 0.83 and a specificity of 0.97.

Keywords: Machine Learning, Suicide prediction, Health application, Suicide risk factors

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