Quantitative Identification of Major Depression Based on Resting-State Dynamic Functional Connectivity: A Machine Learning Approach
IntroductionDeveloping a machine learning-based approach which could provide quantitative identification of major depressive disorder (MDD) is essential for the diagnosis and intervention of this disorder. However, the performances of traditional algorithms using static functional connectivity (SFC)...
Main Authors: | , , , , , , , , , |
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Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2020-03-01
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Series: | Frontiers in Neuroscience |
Subjects: | |
Online Access: | https://www.frontiersin.org/article/10.3389/fnins.2020.00191/full |