Dr. Yunyu Xiao

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.

Individuals with physical health concerns made up the largest and fastest growing of five subgroups of individuals who died by suicide in the United States over roughly twenty years, according to an analysis led by Weill Cornell Medicine in collaboration with Columbia University, UC Berkeley School of Public Health, the University of Hong Kong and University of Kentucky investigators.

A team led by researchers at Weill Cornell Medicine has used an AI-based approach to uncover underlying patterns among the conditions in which people are born, grow, live, work, and age, termed social determinants of health (SDoH), and then linked each pattern to children’s health outcomes.

Financial disruption as a result of pandemic containment policies in the United States adversely influenced children’s mental health.

Adult vaccination rates and social determinants of health—or the social and economic conditions in which families live and work—have played an important role in children’s mental health during the pandemic, according to a new study led by Weill Cornell Medicine investigators.