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SSPNet: An interpretable 3D-CNN for classification of schizophrenia using phase maps of resting-state complex-valued fMRI data.

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第一作者： Qiu-Hua,Lin

第一单位： School of Information and Communication Engineering, Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116024, China. Electronic address: qhlin@dlut.edu.cn.

作者： Qiu-Hua,Lin ^[1] ; Yan-Wei,Niu ^[2] ; Jing,Sui ^[3] ; Wen-Da,Zhao ^[2] ; Chuanjun,Zhuo ^[4] ; Vince D,Calhoun ^[5]

作者单位： School of Information and Communication Engineering, Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116024, China. Electronic address: qhlin@dlut.edu.cn. ^[1] School of Information and Communication Engineering, Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116024, China. ^[2] State Key Laboratory of Brain Cognition and Learning, Beijing Normal University, Beijing, 100875, China. ^[3] Department of Psychiatry, The Fourth Center Hospital of Tianjin, Tianjin Medical University Affiliated Fourth Center Hospital, Tianjin 300140, China. ^[4] Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, USA. ^[5]

关键词 Complex-valued fMRI data Convolutional neural network Grad-CAM Interpretability Saliency map Spatial source phase

医学主题词脑(Brain);人类(Humans);磁共振成像(Magnetic Resonance Imaging);精神分裂症(Schizophrenia)

DOI 10.1016/j.media.2022.102430

PMID 35397470

发布时间 2024-11-28

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准确一般字义偏差语意偏离译文作用小提交