Optimizing prediction of response to antidepressant medications using machine learning and integrated genetic, clinical, and demographic data

Optimizing prediction of response to antidepressant medications using machine learning and integrated genetic, clinical, and demographic data

Abstract Major depressive disorder (MDD) is complex and multifactorial, posing a major challenge of tailoring the optimal medication for each patient. Current practice for MDD treatment mainly relies on trial and error, with an estimated 42–53% response rates for antidepressant use. Here, we sought...

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Bibliographic Details
Main Authors: Dekel Taliaz, Amit Spinrad, Ran Barzilay, Zohar Barnett-Itzhaki, Dana Averbuch, Omri Teltsh, Roy Schurr, Sne Darki-Morag, Bernard Lerer
Format: Article
Language:English
Published: Nature Publishing Group 2021-07-01
Series:Translational Psychiatry
Online Access:https://doi.org/10.1038/s41398-021-01488-3

Internet

https://doi.org/10.1038/s41398-021-01488-3

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