Heterogeneous temporal representation for diabetic blood glucose prediction.

Huang, Yaohui; Ni, Zhikai; Lu, Zhenkun; He, Xinqi; Hu, Jinbo; Li, Boxuan; Ya, Houguan; Shi, Yunxian

Huang, Yaohui; Ni, Zhikai; Lu, Zhenkun; He, Xinqi; Hu, Jinbo; Li, Boxuan; Ya, Houguan; Shi, Yunxian.

Afiliación

Huang Y; College of Electronic Information, Guangxi Minzu University, Nanning, China.
Ni Z; Laboratory of Intelligent Information Processing and Intelligent Medical, Guangxi Minzu University, Nanning, China.
Lu Z; Department of Electronic Science, Xiamen University, Xiamen, China.
He X; College of Electronic Information, Guangxi Minzu University, Nanning, China.
Hu J; Laboratory of Intelligent Information Processing and Intelligent Medical, Guangxi Minzu University, Nanning, China.
Li B; College of Electronic Information, Guangxi Minzu University, Nanning, China.
Ya H; College of Electronic Information, Guangxi Minzu University, Nanning, China.
Shi Y; College of Electronic Information, Guangxi Minzu University, Nanning, China.

Front Physiol ; 14: 1225638, 2023.

Article en En | MEDLINE | ID: mdl-37534367

Palabras clave

continuous glucose monitoring; deep neural network; diabetes mellitus; graph neural network; prediction; time series

Texto completo

Añadir a Mi BVS

Imprimir

XML

PubMed Links

Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Qualitative_research / Risk_factors_studies Idioma: En Revista: Front Physiol Año: 2023 Tipo del documento: Article País de afiliación: China

Texto completo

Añadir a Mi BVS

Imprimir

XML

PubMed Links

Buscar en Google