Machine learning strategies for predicting pediatric suicidal behaviors in a Brazilian emergency setting.

Isis F Carvalho¹, Ana Paula Couto da Silva¹, Anisio M Lacerda¹, Wagner Meira¹, Danilo Bastos Bispo Ferreira², Lys Malloy Diniz², Alexandre Luiz de Oliveira Serpa³, Maria Carolina Lobato Machado², Marco A Romano-Silva^2,4,5, Debora Marques de Miranda⁵, Gisele Lobo Pappa¹

¹Departamento de Ciência da Computação, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil.

²Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil.

³PPG em Ciências do Desenvolvimento Humano, Universidade Presbiteriana Mackenzie, São Paulo, SP, Brazil.

⁴Shanghai Mental Health Centre, Shanghai, China.

⁵Centro de Tecnologia e Medicina Molecular, Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil.

PubMed PMC DOI PDF

Abstract

BACKGROUND: Suicide is a leading cause of death worldwide, yet its prediction remains a challenge. This difficulty arises not only because suicidal behavior is a rare event in the general population, leading to significant class imbalance in datasets, but also due to its complex, multi-causal nature involving a non-linear interplay of sociodemographic and clinical factors. Furthermore, while the m…

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