Cognitive Challenges Are Better in Distinguishing Binge From Nonbinge Drinkers: An Exploratory Deep-Learning Study of fMRI Data of Multiple Behavioral Tasks and Resting State.

Li, Guangfei; Zhang, Zhao; Chen, Yu; Wang, Wuyi; Bi, Jinbo; Tang, Xiaoying; Li, Chiang-Shan R

Li, Guangfei; Zhang, Zhao; Chen, Yu; Wang, Wuyi; Bi, Jinbo; Tang, Xiaoying; Li, Chiang-Shan R.

Affiliation

Li G; Department of Biomedical Engineering, Faculty of Environment and Life Sciences, Beijing University of Technology, Beijing, China.
Zhang Z; Department of Biomedical Engineering, School of Life Sciences, Beijing Institute of technology, Beijing, China.
Chen Y; Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut, USA.
Wang W; Department of Biomedical Engineering, School of Life Sciences, Beijing Institute of technology, Beijing, China.
Bi J; Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut, USA.
Tang X; Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut, USA.
Li CR; Department of Computer Science and Engineering, University of Connecticut, Storrs, Connecticut, USA.

J Magn Reson Imaging ; 57(3): 856-868, 2023 03.

Article in En | MEDLINE | ID: mdl-35808911

Subject(s)
Key words

alcohol use disorder; binge drinking; gamble; interpretability; neural network

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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Binge Drinking / Deep Learning Type of study: Prognostic_studies Limits: Humans / Male Language: En Journal: J Magn Reson Imaging Journal subject: DIAGNOSTICO POR IMAGEM Year: 2023 Document type: Article Affiliation country: China Country of publication: Estados Unidos

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