Submission + - Psychologists enlist machine learning to help diagnose depression (utexas.edu)
aarondubrow writes: Depression affects about 6.7 percent of the U.S. population. Cognitive neuroscientists from The University of Texas at Austin have been able to classify individuals with major depressive disorder with roughly 75% accuracy using a machine learning approach. Their study revealed that diffusion tensor imaging (DTI) MRI scans — which tag water molecules to determine the extent to which those molecules are microscopically diffused in the brain over time — can accurately classify depressed or vulnerable individuals versus healthy controls. It also showed that predictive information is distributed across brain networks rather than being highly localized.