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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Detalles Bibliográficos
Autores principales: Yan, Baoyu, Xu, Xiaopan, Liu, Mengwan, Zheng, Kaizhong, Liu, Jian, Li, Jianming, Wei, Lei, Zhang, Binjie, Lu, Hongbing, Li, Baojuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Neuroscience
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7118554/
https://www.ncbi.nlm.nih.gov/pubmed/32292322
http://dx.doi.org/10.3389/fnins.2020.00191

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7118554/
https://www.ncbi.nlm.nih.gov/pubmed/32292322
http://dx.doi.org/10.3389/fnins.2020.00191

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