Quantitative Identification of Major Depression Based on Resting-State Dynamic Functional Connectivity: A Machine Learning Approach

INTRODUCTION: Developing 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 (SF...

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Détails bibliographiques
Publié dans:Front Neurosci
Auteurs principaux: Yan, Baoyu, Xu, Xiaopan, Liu, Mengwan, Zheng, Kaizhong, Liu, Jian, Li, Jianming, Wei, Lei, Zhang, Binjie, Lu, Hongbing, Li, Baojuan
Format: Artigo
Langue:Inglês
Publié: Frontiers Media S.A. 2020
Sujets:
Neuroscience
Accès en ligne:https://ncbi.nlm.nih.gov/pmc/articles/PMC7118554/
https://ncbi.nlm.nih.gov/pubmed/32292322
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fnins.2020.00191
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