Suicide risk classification with machine learning techniques in a large Brazilian community sample (2023)
- Authors:
- USP affiliated authors: LOTUFO, PAULO ANDRADE - FM ; BENSEÑOR, ISABELA JUDITH MARTINS - FM ; BRUNONI, ANDRE RUSSOWSKY - FM
- Unidade: FM
- DOI: 10.1016/j.psychres.2023.115258
- Subjects: APRENDIZADO COMPUTACIONAL; SAÚDE PÚBLICA; SUICÍDIO
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Título do periódico: Psychiatry research
- ISSN: 0165-1781
- Volume/Número/Paginação/Ano: v. 325, article ID 115258, 10p, 2023
- Este periódico é de assinatura
- Este artigo NÃO é de acesso aberto
- Cor do Acesso Aberto: closed
-
ABNT
ROZA, Thiago Henrique et al. Suicide risk classification with machine learning techniques in a large Brazilian community sample. Psychiatry research, v. 325, 2023Tradução . . Disponível em: https://observatorio.fm.usp.br/handle/OPI/54558. Acesso em: 03 jun. 2024. -
APA
Roza, T. H., Seibel, G. de S., Recamonde-Mendoza, M., Lotufo, P. A., Benseñor, I. J. M., Passos, I. C., & Brunoni, A. R. (2023). Suicide risk classification with machine learning techniques in a large Brazilian community sample. Psychiatry research, 325. doi:10.1016/j.psychres.2023.115258 -
NLM
Roza TH, Seibel G de S, Recamonde-Mendoza M, Lotufo PA, Benseñor IJM, Passos IC, Brunoni AR. Suicide risk classification with machine learning techniques in a large Brazilian community sample [Internet]. Psychiatry research. 2023 ; 325[citado 2024 jun. 03 ] Available from: https://observatorio.fm.usp.br/handle/OPI/54558 -
Vancouver
Roza TH, Seibel G de S, Recamonde-Mendoza M, Lotufo PA, Benseñor IJM, Passos IC, Brunoni AR. Suicide risk classification with machine learning techniques in a large Brazilian community sample [Internet]. Psychiatry research. 2023 ; 325[citado 2024 jun. 03 ] Available from: https://observatorio.fm.usp.br/handle/OPI/54558 - A systematic review of non-invasive brain stimulation therapies and cardiovascular risk: implications for the treatment of major depressive disorder
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Informações sobre o DOI: 10.1016/j.psychres.2023.115258 (Fonte: oaDOI API)
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