Prediction of depression cases, incidence, and chronicity in a large occupational cohort using machine learning techniques: an analysis of the ELSA-Brasil study.

Abstract

Authors

• Diego Librenza-Garcia
  Graduation Program in Psychiatry, Universidade Federal das Ciências da Saúde de Porto Alegre, Porto Alegre, RS, Brazil; Bipolar Disorder Program, Laboratory of Molecular Psychiatry, Hospital de Clínicas de Porto Alegre (HCPA), Porto Alegre, RS, 90035-903, Brazil. Electronic address: diegolibrenzagarcia@gmail.com.
• Ives Cavalcante Passos
  Center of Excellence on Mood Disorder, Department of Psychiatry and Behavioral Sciences, The University of Texas Health Science Center at Houston, Houston, TX, USA; Bipolar Disorder Program and Laboratory of Molecular Psychiatry, Federal University of Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil.
• Jacson Gabriel Feiten
  Laboratory of Molecular Psychiatry, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil.
• Paulo A Lotufo
  Department of Internal Medicine, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil.
• Alessandra C Goulart
  Department of Internal Medicine, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil.
• Itamar de Souza Santos
  Department of Internal Medicine, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil.
• Maria Carmen Viana
  Department of Social Medicine, Postgraduate Program in Public Health, Center of Psychiatric Epidemiology (CEPEP), Federal University of Espírito Santo, Vitória, Brazil.
• Isabela M Benseñor
  Department of Internal Medicine, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil.
• Andre Russowsky Brunoni
  Department of Internal Medicine, Faculdade de Medicina da Universidade de São Paulo, São Paulo, Brazil.

Keywords

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