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Identifying Internet Addiction and Evaluating the Efficacy of Treatment Based on Functional Connectivity Density: A Machine Learning Study.
Wang, Yang; Qin, Yun; Li, Hui; Yao, Dezhong; Sun, Bo; Gong, Jinnan; Dai, Yu; Wen, Chao; Zhang, Lingrui; Zhang, Chenchen; Luo, Cheng; Zhu, Tianmin.
Afiliação
  • Wang Y; School of Rehabilitation and Health Preservation, Chengdu University of Traditional Chinese Medicine, Chengdu, China.
  • Qin Y; Key Laboratory for NeuroInformation of Ministry of Education, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, China.
  • Li H; School of Medicine, Chengdu University, Chengdu, China.
  • Yao D; Key Laboratory for NeuroInformation of Ministry of Education, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, China.
  • Sun B; Key Laboratory for NeuroInformation of Ministry of Education, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, China.
  • Gong J; Key Laboratory for NeuroInformation of Ministry of Education, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, China.
  • Dai Y; School of Computer Science, Chengdu University of Information Technology, Chengdu, China.
  • Wen C; Department of Chinese Medicine, Chengdu Eighth People's Hospital, Chengdu, China.
  • Zhang L; Department of Rehabilitation, Zigong Fifth People's Hospital, Zigong, China.
  • Zhang C; Department of Medicine, Leshan Vocational and Technical College, Leshan, China.
  • Luo C; Department of Rehabilitation, TCM Hospital of Longquanyi District, Chengdu, China.
  • Zhu T; Key Laboratory for NeuroInformation of Ministry of Education, School of Life Sciences and Technology, University of Electronic Science and Technology of China, Chengdu, China.
Front Neurosci ; 15: 665578, 2021.
Article em En | MEDLINE | ID: mdl-34220426
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Front Neurosci Ano de publicação: 2021 Tipo de documento: Article País de afiliação: China
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Front Neurosci Ano de publicação: 2021 Tipo de documento: Article País de afiliação: China