Machine learning for suicide risk prediction in children and adolescents with electronic health records

Accurate prediction of suicide risk among children and adolescents within an actionable time frame is an important but challenging task. Very few studies have comprehensively considered the clinical risk factors available to produce quantifiable risk scores for estimation of short- and long-term sui...

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Detalles Bibliográficos
Autores principales: Su, Chang, Aseltine, Robert, Doshi, Riddhi, Chen, Kun, Rogers, Steven C., Wang, Fei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7693189/
https://www.ncbi.nlm.nih.gov/pubmed/33243979
http://dx.doi.org/10.1038/s41398-020-01100-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7693189/
https://www.ncbi.nlm.nih.gov/pubmed/33243979
http://dx.doi.org/10.1038/s41398-020-01100-0

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