The suicide death toll is alarmingly high, outnumbering deaths from war and homicide
worldwide (1). Many factors contribute to suicide death, making it difficult to prevent because …

In ever more pressured health-care systems, technological solutions offering scalability of
care and better resource targeting are appealing. Research on machine learning as a …

Deep learning transformer-based models using longitudinal electronic health records
(EHRs) have shown a great success in prediction of clinical diseases or outcomes …

Background Suicide is one of the main preventable causes of death. Artificial intelligence
(AI) could improve methods for assessing suicide risk. The objective of this review is to …

Importance The months after psychiatric hospital discharge are a time of high risk for suicide.
Intensive postdischarge case management, although potentially effective in suicide …

Artificial Intelligence: Review of Current and Future Applications in Medicine - PMC Back to Top
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Suicide risk is elevated among military service members who recently transitioned to civilian
life. Identifying high-risk service members before this transition could facilitate provision of …

Abstract Machine learning (ML) has emerged as a promising tool to enhance suicidal
prediction. However, as many large-sample studies mixed psychiatric and non-psychiatric …

BackgroundSuicide prediction models have been formulated in a variety of ways and are
heterogeneous in the strength of their predictions. Machine learning has been a proposed …

Importance Social determinants of health (SDOHs) are known to be associated with
increased risk of suicidal behaviors, but few studies use SDOHs from unstructured electronic …