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 …

Background Machine learning is a promising tool in the area of suicide prevention due to its
ability to combine the effects of multiple risk factors and complex interactions. The power of …

This study aimed to use machine learning (ML) models to predict the risk of self-harm and
suicide attempts in adolescents. We conducted secondary analysis of cross-sectional data …

Psychological and behavioral stress has increased enormously during Coronavirus Disease
2019 (COVID-19) pandemic. However, early prediction and intervention to address …

Background The rise of depression, anxiety, and suicide rates has led to increased demand
for telemedicine-based mental health screening and remote patient monitoring (RPM) …

Even though suicide is a relatively preventable poor outcome, its prediction remains an
elusive task. The main goal of this study was to develop machine learning classifiers to …

Predicting suicide risk based on risk and protective factors is a critical and complex
endeavor. In this study, we combined insights from comprehensive aetiological theories on …

Background A suicide attempt (SA) is a clinically serious action. Researchers have argued
that reducing long-term SA risk may be possible, provided that at-risk individuals are …

Background This study addresses the suicide risk predicting challenge by exploring the
predictive ability of machine learning (ML) models integrated with theory‐driven …

Introduction Every year about 800,000 complete suicide events occur. The identification of
biologic markers to identify subjects at risk would be helpful in targeting specific support …