Predicting short-term suicidal thoughts in adolescents using machine learning: developing decision tools to identify daily level risk after hospitalization

BACKGROUND: Mobile technology offers unique opportunities for monitoring short-term suicide risk in daily life. In this study of suicidal adolescent inpatients, theoretically informed risk factors were assessed daily following discharge to predict near-term suicidal ideation and inform decision algo...

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Detalles Bibliográficos
Autores principales: Czyz, E. K., Koo, H. J., Al-Dajani, N., King, C. A., Nahum-Shani, I.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cambridge University Press 2023
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9814182/
https://www.ncbi.nlm.nih.gov/pubmed/34879890
http://dx.doi.org/10.1017/S0033291721005006

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9814182/
https://www.ncbi.nlm.nih.gov/pubmed/34879890
http://dx.doi.org/10.1017/S0033291721005006

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