Differential Treatment Benefit Prediction For Treatment Selection in Depression: A Deep Learning Analysis of STAR*D and CO-MED Data
Joseph Mehltretter, Robert Fratila, David A. Benrimoh, Adam D. Kapelner, Kelly Perlman, Emily Snook, Sonia Ancoli Israel, Caitrin Armstrong, Marc Miresco, Gustavo Turecki
The paper uses deep learning to predict differential treatment benefits for depression using STAR*D and CO-MED data, showing improved remission rates with model-guided treatment selection.
Computational Psychiatry · Jan 1, 2020Peer-reviewedNeuroscience