Resting-State Functional Connectivity Patterns Predict Acupuncture Treatment Response in Primary Dysmenorrhea

Resting-State Functional Connectivity Patterns Predict Acupuncture Treatment Response in Primary Dysmenorrhea

Primary dysmenorrhea (PDM) is a common complaint in women throughout the menstrual years. Acupuncture has been shown to be effective in dysmenorrhea; however, there are large interindividual differences in patients’ responses to acupuncture treatment. Fifty-four patients with PDM were recruited and...

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Bibliographic Details
Main Authors: Siyi Yu, Mingguo Xie, Shuqin Liu, Xiaoli Guo, Jin Tian, Wei Wei, Qi Zhang, Fang Zeng, Fanrong Liang, Jie Yang
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-09-01
Series:Frontiers in Neuroscience
Subjects:
functional connectivity
primary dysmenorrhea
machine learning
multivariate pattern analyses
acupuncture
Online Access:https://www.frontiersin.org/article/10.3389/fnins.2020.559191/full

Internet

https://www.frontiersin.org/article/10.3389/fnins.2020.559191/full

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