Predicting Sex-Specific Nonfatal Suicide Attempt Risk Using Machine Learning and Data From Danish National Registries.

Gradus, Jaimie L; Rosellini, Anthony J; Horváth-Puhó, Erzsébet; Jiang, Tammy; Street, Amy E; Galatzer-Levy, Isaac; Lash, Timothy L; Sørensen, Henrik T

Gradus, Jaimie L; Rosellini, Anthony J; Horváth-Puhó, Erzsébet; Jiang, Tammy; Street, Amy E; Galatzer-Levy, Isaac; Lash, Timothy L; Sørensen, Henrik T.

Am J Epidemiol ; 190(12): 2517-2527, 2021 12 01.

Article in En | MEDLINE | ID: mdl-33877265

Subject(s)

Machine Learning; Suicide, Attempted/statistics & numerical data; Adolescent; Adult; Denmark/epidemiology; Emigrants and Immigrants/statistics & numerical data; Female; Health Status; Humans; Male; Mental Disorders/epidemiology; Mental Health/statistics & numerical data; Middle Aged; Registries; Risk Factors; Sociodemographic Factors; Young Adult

Key words

Denmark; National Registry; machine learning; prediction; suicide attempts

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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Suicide, Attempted / Machine Learning Type of study: Diagnostic_studies / Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Adolescent / Adult / Female / Humans / Male / Middle aged Country/Region as subject: Europa Language: En Journal: Am J Epidemiol Year: 2021 Type: Article

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