Building a model for predicting metabolic syndrome using artificial intelligence based on an investigation of whole-genome sequencing.

Hsu, Nai-Wei; Chou, Kai-Chen; Wang, Yu-Ting Tina; Hung, Chung-Lieh; Kuo, Chien-Feng; Tsai, Shin-Yi

Hsu, Nai-Wei; Chou, Kai-Chen; Wang, Yu-Ting Tina; Hung, Chung-Lieh; Kuo, Chien-Feng; Tsai, Shin-Yi.

Afiliação

Hsu NW; Department of Medicine, Mackay Medical College, New Taipei City, Taiwan.
Chou KC; Department of Laboratory Medicine, MacKay Memorial Hospital, Taipei City, Taiwan.
Wang YT; Department of Laboratory Medicine, MacKay Memorial Hospital, Taipei City, Taiwan.
Hung CL; Department of Medicine, Mackay Medical College, New Taipei City, Taiwan.
Kuo CF; Institute of Biomedical Sciences, Mackay Medical College, New Taipei City, Taiwan.
Tsai SY; Department of Medicine, Mackay Medical College, New Taipei City, Taiwan.

J Transl Med ; 20(1): 190, 2022 04 28.

Article em En | MEDLINE | ID: mdl-35484552

Assuntos

Inteligência Artificial; Síndrome Metabólica; Ritmo Circadiano; Humanos; Síndrome Metabólica/genética; Redes Neurais de Computação; Sequenciamento Completo do Genoma

Palavras-chave

Circadian rhythm; Deep learning; Metabolic syndrome; Whole-genome sequencing

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Síndrome Metabólica Idioma: En Ano de publicação: 2022 Tipo de documento: Article

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PubMed Links

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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Inteligência Artificial / Síndrome Metabólica Idioma: En Ano de publicação: 2022 Tipo de documento: Article