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

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


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.

Palavras-chave: Machine Learning, Suicide prediction, Health application, Suicide risk factors


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CARVALHO, Isis F.; MIRANDA, Debora; DA SILVA, Ana Paula Couto; LACERDA, Anisio M.; MEIRA JR., Wagner; ROMANO-SILVA, Marco A.; LOBATO, Maria Carolina; PAPPA, Gisele L.. Prediction of suicidal behaviors in hospitalized children and adolescents in middle-income countries: a case study of Brazil. In: ENCONTRO NACIONAL DE INTELIGÊNCIA ARTIFICIAL E COMPUTACIONAL (ENIAC), 20. , 2023, Belo Horizonte/MG. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2023 . p. 1225-1236. ISSN 2763-9061. DOI:

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