Classification of Alzheimer's Disease Based on Deep Learning of Brain Structural and Metabolic Data.

Wang, Huiquan; Feng, Tianzi; Zhao, Zhe; Bai, Xue; Han, Guang; Wang, Jinhai; Dai, Zongrui; Wang, Rong; Zhao, Weibiao; Ren, Fuxin; Gao, Fei

Wang, Huiquan; Feng, Tianzi; Zhao, Zhe; Bai, Xue; Han, Guang; Wang, Jinhai; Dai, Zongrui; Wang, Rong; Zhao, Weibiao; Ren, Fuxin; Gao, Fei.

Afiliação

Wang H; School of Life Sciences, Tiangong University, Tianjin, China.
Feng T; School of Electrical and Information Engineering, Tiangong University, Tianjin, China.
Zhao Z; School of Electrical and Information Engineering, Tiangong University, Tianjin, China.
Bai X; Department of Radiology, Qilu Hospital of Shandong University, Jinan, China.
Han G; School of Life Sciences, Tiangong University, Tianjin, China.
Wang J; School of Life Sciences, Tiangong University, Tianjin, China.
Dai Z; Westa College, Southwest University, Chongqing, China.
Wang R; School of Life Sciences, Tiangong University, Tianjin, China.
Zhao W; School of Life Sciences, Tiangong University, Tianjin, China.
Ren F; Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China.
Gao F; Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, China.

Front Aging Neurosci ; 14: 927217, 2022.

Article em En | MEDLINE | ID: mdl-35903535

Palavras-chave

Alzheimer's disease; deep learning; feature extraction; magnetic resonance imaging; magnetic resonance spectroscopy

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Front Aging Neurosci Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China

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