Machine Learning Can Help Diagnose Depression

UPI reports that 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. Now they are using the Stampede supercomputer at the Texas Advanced Computing Center, or TACC, to train a machine learning algorithm that can identify similarities among hundreds of patients using magnetic resonance imaging, or MRI, genomics data and other factors to predict patients at risk for depression and anxiety.

This video was produced by YT Wochit Tech using