Leveraging Machine Learning Approaches for Predicting Antidepressant Treatment Response Using Electroencephalography (EEG) and Clinical Data

Leveraging Machine Learning Approaches for Predicting Antidepressant Treatment Response Using Electroencephalography (EEG) and Clinical Data

Background: Individuals with major depressive disorder (MDD) vary in their response to antidepressants. However, identifying objective biomarkers, prior to or early in the course of treatment that can predict antidepressant efficacy, remains a challenge.Methods: Individuals with MDD participated in...

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Bibliographic Details
Main Authors: Natalia Jaworska, Sara de la Salle, Mohamed-Hamza Ibrahim, Pierre Blier, Verner Knott
Format: Article
Language:English
Published: Frontiers Media S.A. 2019-01-01
Series:Frontiers in Psychiatry
Subjects:
major depressive disorder (MDD)
antidepressants
biomarker
quantitative EEG
machine learning (ML)
classification and regression trees
Online Access:https://www.frontiersin.org/article/10.3389/fpsyt.2018.00768/full

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https://www.frontiersin.org/article/10.3389/fpsyt.2018.00768/full

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