Blood pressure stratification using photoplethysmography and light gradient boosting machine.

Hu, Xudong; Yin, Shimin; Zhang, Xizhuang; Menon, Carlo; Fang, Cheng; Chen, Zhencheng; Elgendi, Mohamed; Liang, Yongbo

Hu, Xudong; Yin, Shimin; Zhang, Xizhuang; Menon, Carlo; Fang, Cheng; Chen, Zhencheng; Elgendi, Mohamed; Liang, Yongbo.

Afiliación

Hu X; School of Life and Environmental Sciences, Guilin University of Electronic Technology, Guilin, China.
Yin S; School of Life and Environmental Sciences, Guilin University of Electronic Technology, Guilin, China.
Zhang X; School of Electronic Engineering and Automation, Guilin University of Electronic Technology, Guilin, China.
Menon C; Biomedical and Mobile Health Technology Lab, ETH Zurich, Zurich, Switzerland.
Fang C; School of Life and Environmental Sciences, Guilin University of Electronic Technology, Guilin, China.
Chen Z; School of Life and Environmental Sciences, Guilin University of Electronic Technology, Guilin, China.
Elgendi M; Guangxi Colleges and Universities Key Laboratory of Biomedical Sensors and Intelligent Instruments, Guilin, China.
Liang Y; Guangxi Engineering Technology Research Center of Human Physiological Information Noninvasive Detection, Guilin, China.

Front Physiol ; 14: 1072273, 2023.

Article en En | MEDLINE | ID: mdl-36891146

Palabras clave

Optuna-tuned LightGBM; blood pressure monitoring; hypertension evaluation; machine learning; photoplethysmography; wearable devices

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Texto completo: 1 Bases de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies / Screening_studies Idioma: En Revista: Front Physiol Año: 2023 Tipo del documento: Article País de afiliación: China

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