Differential Treatment Benefit Prediction for Treatment Selection in Depression: A Deep Learning Analysis of STAR*D and CO-MED Data

Differential Treatment Benefit Prediction for Treatment Selection in Depression: A Deep Learning Analysis of STAR*D and CO-MED Data

Depression affects one in nine people, but treatment response rates remain low. There is significant potential in the use of computational modeling techniques to predict individual patient responses and thus provide more personalized treatment. Deep learning is a promising computational technique th...

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Bibliographic Details
Main Authors: Joseph Mehltretter, Robert Fratila, David A. Benrimoh, Adam Kapelner, Kelly Perlman, Emily Snook, Sonia Israel, Caitrin Armstrong, Marc Miresco, Gustavo Turecki
Format: Article
Language:English
Published: Ubiquity Press 2020-01-01
Series:Computational Psychiatry
Subjects:
depression
treatment selection
artificial intelligence
machine learning
treatment prediction
mood disorders
Online Access:https://cpsyjournal.org/articles/26

Internet

https://cpsyjournal.org/articles/26

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