Machine learning models help clinicians identify people who need advanced depression care

Researchers at Regenstrief Institute and Indiana University created decision models capable of predicting which patients might need more treatment for their depression than what their primary care provider can offer. The algorithms were specifically designed to provide information the clinician can act on and fit into existing clinical workflows. Depression is the most commonly occurring mental illness in the world. The World Health Organization estimates that it affects about 350 million people. Some people may be able to manage their depression on their own or with guidance from a primary care provider.