Machine learning model helps identify patients at risk of postpartum depression

Postpartum depression (PPD) affects up to 15% of individuals after childbirth. Early identification of patients at risk of PPD could improve proactive mental health support. Mass General Brigham researchers developed a machine learning model that can evaluate patients’ PPD risk using readily accessible clinical and demographic factors. Findings demonstrating the model’s promising predictive capabilities are published in the American Journal of Psychiatry.