AI tools fall short in predicting suicide, study finds
The accuracy of machine learning algorithms for predicting suicidal behavior is too low to be useful for screening or for prioritizing high-risk individuals for interventions, according to a new study published September 11th in the open-access journal PLOS Medicine by Matthew Spittal of the University of Melbourne, Australia, and colleagues.
Numerous risk assessment scales have been developed over the past 50 years to identify patients at high risk of suicide or self-harm. In general, these scales have had poor predictive accuracy, but the availability of modern machine ...