Evaluating the diagnostic utility of applying a machine learning algorithm to diffusion tensor MRI measures in individuals with major depressive disorder

Using MRI to diagnose mental disorders has been a long-term goal. Despite this, the vast majority of prior neuroimaging work has been descriptive rather than predictive. The current study applies support vector machine (SVM) learning to MRI measures of brain white matter to classify adults with Major Depressive Disorder (MDD) and healthy controls. In a precisely matched group of individuals with MDD (n = 25) and healthy controls (n = 25), SVM learning accurately (74%) classified patients and controls across a brain map of white matter fractional anisotropy values (FA).

Source: Psychiatry Research: Neuroimaging - March 22, 2017 Category: Psychiatry Authors: David M Schnyer, Peter C. Clasen, Christopher Gonzalez, Christopher G. Beevers Source Type: research