Identification of the Framingham Risk Score by an Entropy-Based Rule Model for Cardiovascular Disease.

Chen, You-Shyang; Cheng, Ching-Hsue; Chen, Su-Fen; Jhuang, Jhe-You

Chen, You-Shyang; Cheng, Ching-Hsue; Chen, Su-Fen; Jhuang, Jhe-You.

Afiliação

Chen YS; Department of Information Management, Hwa Hsia University of Technology, New Taipei City 235, Taiwan.
Cheng CH; Department of Information Management, National Yunlin University of Science and Technology, Douliou, Yunlin 64002, Taiwan.
Chen SF; National Museum of Marine Science & Technology, Keelung City 202010, Taiwan.
Jhuang JY; Department of Information Management, National Yunlin University of Science and Technology, Douliou, Yunlin 64002, Taiwan.

Entropy (Basel) ; 22(12)2020 Dec 13.

Article em En | MEDLINE | ID: mdl-33322122

Palavras-chave

Framingham risk attributes; Framingham risk score (FRS); applications of medicine; cardiovascular disease; entropy-based rule model; machine learning techniques

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies / Etiology_studies / Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2020 Tipo de documento: Article

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