Prediction of coronary heart disease based on combined reinforcement multitask progressive time-series networks.

Li, Wenqi; Zuo, Ming; Zhao, Hongjin; Xu, Qi; Chen, Dehua

Li, Wenqi; Zuo, Ming; Zhao, Hongjin; Xu, Qi; Chen, Dehua.

Afiliação

Li W; School of Computer Science and Technology, Donghua University, Shanghai, China; Artificial Intelligence Lab, China UnionPay Headquarters, Shanghai, China. Electronic address: liwenqi210@163.com.
Zuo M; Glorious Sun School of Business and Management, Donghua University, Shanghai, China; Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China. Electronic address: zm@rjh.com.cn.
Zhao H; School of Computer Science and Technology, Donghua University, Shanghai, China. Electronic address: zhaohongjin11@163.com.
Xu Q; Glorious Sun School of Business and Management, Donghua University, Shanghai, China. Electronic address: xuqi@dhu.edu.cn.
Chen D; School of Computer Science and Technology, Donghua University, Shanghai, China. Electronic address: chendehua@dhu.edu.cn.

Methods ; 198: 96-106, 2022 02.

Article em En | MEDLINE | ID: mdl-34954350

Assuntos

Doença das Coronárias; Redes Neurais de Computação; Doença das Coronárias/diagnóstico por imagem; Coração; Humanos; Fatores de Tempo

Palavras-chave

Asynchronous advantage actor-critic; Combined reinforcement multitask progressive time-series networks; Coronary heart disease prediction; Hard parameter sharing; Soft parameter sharing

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Redes Neurais de Computação / Doença das Coronárias Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Methods Assunto da revista: BIOQUIMICA Ano de publicação: 2022 Tipo de documento: Article

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