Using machine learning technology, a new study has identified three distinct profiles describing social and economic factors that are associated with a higher risk of suicide. Scientists at Weill Cornell Medicine and Columbia University Vagelos College of Physicians and Surgeons led the research that showed suicide rates vary significantly across the three clusters and that the patterns differ geographically across the United States.
Machine learning uncovers social risk clusters linked to suicide across the US
