Early prediction of clinical scores for left ventricular reverse remodeling using extreme gradient random forest, boosting, and logistic regression algorithm representations.

Liu, Lu; Qiao, Cen; Zha, Jun-Ren; Qin, Huan; Wang, Xiao-Rui; Zhang, Xin-Yu; Wang, Yi-Ou; Yang, Xiu-Mei; Zhang, Shu-Long; Qin, Jing

Liu, Lu; Qiao, Cen; Zha, Jun-Ren; Qin, Huan; Wang, Xiao-Rui; Zhang, Xin-Yu; Wang, Yi-Ou; Yang, Xiu-Mei; Zhang, Shu-Long; Qin, Jing.

Afiliación

Liu L; Heart Centre, Affiliated Zhongshan Hospital of Dalian University, Dalian, China.
Qiao C; Heart Centre, Affiliated Zhongshan Hospital of Dalian University, Dalian, China.
Zha JR; School of Software Engineering, Dalian University, Dalian, China.
Qin H; Heart Centre, Affiliated Zhongshan Hospital of Dalian University, Dalian, China.
Wang XR; Heart Centre, Affiliated Zhongshan Hospital of Dalian University, Dalian, China.
Zhang XY; Medical College, Dalian University, Dalian, China.
Wang YO; Heart Centre, Affiliated Zhongshan Hospital of Dalian University, Dalian, China.
Yang XM; Heart Centre, Affiliated Zhongshan Hospital of Dalian University, Dalian, China.
Zhang SL; Heart Centre, Affiliated Zhongshan Hospital of Dalian University, Dalian, China.
Qin J; School of Software Engineering, Dalian University, Dalian, China.

Front Cardiovasc Med ; 9: 864312, 2022.

Article en En | MEDLINE | ID: mdl-36061535

Palabras clave

heart failure; heart failure with reduced ejection fraction; left ventricular reverse remodeling; machine learning; prediction model

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Clinical_trials / Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Cardiovasc Med Año: 2022 Tipo del documento: Article País de afiliación: China Pais de publicación: Suiza

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