Novel Algorithm Could Help Predict Depression Diagnoses

An innovative supercomputing program could assist psychologists with diagnosing mental health conditions.Researchers are using the Stampede Supercomputer, stationed at the Texas Advanced Computing Center, to teach a machine-learning algorithm that can sift through diverse data sets and potentially predict which patients are at risk of developing depression and anxiety.The team conducted a study where they had 52 treatment-seeking participants with depression and 45 healthy control participants receive diffusion tensor imaging (DTI) MRI scans. This process entails tagging water molecules to analyze the level of which these particles are microscopically diffused in the brain over a certain period of time.”We feed in whole brain data or a subset and predict disease classifications or any potential behavioral measure such as measures of negative information bias,” said David Schnyer, a psychology professor and cognitive neuroscientists at the University of Texas at Austin, in a statement.

Source: Novel Algorithm Could Help Predict Depression Diagnoses

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