Machine learning models using EHR data significantly improved clinicians’ suicide risk assessments, offering more accurate predictions of future suicide attempts.

These pioneers in their fields represent the most influential researchers who have published multiple papers frequently cited by their peers that rank in the top […]

Since 1993, over 100 women have received a Claflin Distinguished Scholar Award, many of whom have gone on to become leaders at the hospital and […]

Published in JAMA Pediatrics, this survey-based study sheds light on the link between substance use and mental health issues among high school students.

New research focuses on improving strategies for predicting risk of suicide, advancing our understanding of suicide risk in unique populations, and designing interventions to reduce […]

Clinician-researchers at Massachusetts General Hospital are using big data to better identify people at risk for suicide attempts and are developing a decision-support tool for […]