3.9 predictive modeling of mood changes for secondary prevention in youth depression

Current literature demonstrates an opportunity for novel analyses by applying machine learning to real-time individual patient-level data to predict clinical course in mood disorders. We have been collecting physiological and behavioral data by wearable and smartphone technologies from child and adolescent research participants with MDD (MDD-CA), with the aim of predicting relapse.

Source: Journal of the American Academy of Child and Adolescent Psychiatry - September 30, 2019 Category: Psychiatry Authors: Andrew Kidd, John Strauss, Lydia Sequeira, Peter Szatmari, Deepa Kundur, Marco Battaglia Source Type: research