A Deep Learning Approach for Predicting Antidepressant Response in Major Depression Using Clinical and Genetic Biomarkers

A Deep Learning Approach for Predicting Antidepressant Response in Major Depression Using Clinical and Genetic Biomarkers

In the wake of recent advances in scientific research, personalized medicine using deep learning techniques represents a new paradigm. In this work, our goal was to establish deep learning models which distinguish responders from non-responders, and also to predict possible antidepressant treatment...

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Bibliographic Details
Main Authors: Eugene Lin, Po-Hsiu Kuo, Yu-Li Liu, Younger W.-Y. Yu, Albert C. Yang, Shih-Jen Tsai
Format: Article
Language:English
Published: Frontiers Media S.A. 2018-07-01
Series:Frontiers in Psychiatry
Subjects:
antidepressant
deep learning
genome-wide association studies
major depressive disorder
multilayer feedforward neural networks
personalized medicine
Online Access:https://www.frontiersin.org/article/10.3389/fpsyt.2018.00290/full

Internet

https://www.frontiersin.org/article/10.3389/fpsyt.2018.00290/full

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