Open AccessPrediction of Sex-Specific Suicide Risk Using Machine Learning and Single-Payer Health Care Registry Data From Denmark
Author(s) -
Jaimie L. Gradus,
Anthony J. Rosellini,
Erzsébet HorváthPuhó,
Amy E. Street,
Isaac R. GalatzerLevy,
Tammy Jiang,
Timothy L. Lash,
Henrik Toft Sørensen
Publication year - 2019
Publication title -
jama psychiatry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 7.531
H-Index - 365
eISSN - 2168-6238
pISSN - 2168-622X
DOI - 10.1001/jamapsychiatry.2019.2905
Subject(s) - danish , medicine , population , suicide prevention , poison control , demography , public health , injury prevention , suicide attempt , psychiatry , gerontology , medical emergency , environmental health , philosophy , linguistics , nursing , sociology
Suicide is a public health problem, with multiple causes that are poorly understood. The increased focus on combining health care data with machine-learning approaches in psychiatry may help advance the understanding of suicide risk.
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