Suicide and suicide-related behaviors are prevalent yet notoriously difficult to predict.
Specifically, short-term predictors and correlates of suicide risk remain largely unknown …

Research has posited that machine learning could improve suicide risk prediction models,
which have traditionally performed poorly. This systematic review and meta-analysis …

This study aims to identify the timescale of suicidal thinking, leveraging real-time monitoring
data and a number of different analytic approaches. Participants were 105 adults with past …

Importance Half of the people who die by suicide make a health care visit within 1 month of
their death. However, clinicians lack the tools to identify these patients. Objective To predict …

Now in an extensively revised third edition with 65% new material, this is the authoritative
presentation of the Collaborative Assessment and Management of Suicidality (CAMS) …

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 …

The suicide rate (currently 14 per 100,000) has barely changed in the United States over the
past 100 years. There is a need for new ways of preventing suicide. Further, research has …

Nine percent of people worldwide report thinking about suicide at some point during their
lives. A fundamental question we currently lack a clear answer to is: why do suicidal …

In the past decade, two themes have emerged across suicide research. First, according to
meta-analyses, the ability to predict and prevent suicidal thoughts and behaviours is weaker …

Most theories of suicide propose within-person changes in psychological states cause
suicidal thoughts/behaviors; however, most studies use between-person analyses. Thus …