Identifying Internet Addiction and Evaluating the Efficacy of Treatment Based on Functional Connectivity Density: A Machine Learning Study

Identifying Internet Addiction and Evaluating the Efficacy of Treatment Based on Functional Connectivity Density: A Machine Learning Study

Although mounting neuroimaging studies have greatly improved our understanding of the neurobiological mechanism underlying internet addiction (IA), the results based on traditional group-level comparisons are insufficient in guiding individual clinical practice directly. Specific neuroimaging biomar...

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Bibliographic Details
Main Authors: Yang Wang, Yun Qin, Hui Li, Dezhong Yao, Bo Sun, Jinnan Gong, Yu Dai, Chao Wen, Lingrui Zhang, Chenchen Zhang, Cheng Luo, Tianmin Zhu
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-06-01
Series:Frontiers in Neuroscience
Subjects:
internet addiction
cognitive behavior therapy
support vector classification
support vector regression
biomarker
Online Access:https://www.frontiersin.org/articles/10.3389/fnins.2021.665578/full

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https://www.frontiersin.org/articles/10.3389/fnins.2021.665578/full

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