Sparsity-guided multiple functional connectivity patterns for classification of schizophrenia via convolutional network.

Yu, Renping; Pan, Cong; Bian, Lingbin; Fei, Xuan; Chen, Mingming; Shen, Dinggang

Yu, Renping; Pan, Cong; Bian, Lingbin; Fei, Xuan; Chen, Mingming; Shen, Dinggang.

Afiliación

Yu R; School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou, China.
Pan C; School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou, China.
Bian L; School of Biomedical Engineering, ShanghaiTech University, Shanghai, China.
Fei X; School of Artificial Intelligence and Big Data, Henan University of Technology, Zhengzhou, China.
Chen M; School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou, China.
Shen D; School of Biomedical Engineering, ShanghaiTech University, Shanghai, China.

Hum Brain Mapp ; 44(12): 4523-4534, 2023 08 15.

Article en En | MEDLINE | ID: mdl-37318814

Asunto(s)

Esquizofrenia; Humanos; Mapeo Encefálico/métodos; Imagen por Resonancia Magnética/métodos; Vías Nerviosas/diagnóstico por imagen; Encéfalo

Palabras clave

convolutional neural network; multiple sparse patterns learning; resting-state functional MRI; schizophrenia; weighted sparse functional connectivity

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Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Esquizofrenia Límite: Humans Idioma: En Revista: Hum Brain Mapp Asunto de la revista: CEREBRO Año: 2023 Tipo del documento: Article País de afiliación: China

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