Researchers use machine learning to help diagnose depression

A new study from the University of Texas suggests machine learning with a supercomputer may help identify people susceptible to developing depression. Depression is the leading cause of disability for people between the ages of 15 and 44, and affects more than 15 million American adults each year. Researchers have studied mental illness by identifying the relationship between brain function and structure using neuroimaging data for years. "One difficulty with that work is that it's primarily descriptive," David Schnyer, a cognitive neuroscientist at the University of Texas, said in a press release. "The brain networks may appear to differ between two groups, but it doesn't tell us about what patterns actually predit which group you will fall into. We're looking for diagnostic measures that are predictive for outcomes like vulnerability to depression or dementia."