90% Accuracy for Photoplethysmography-Based Non-Invasive Blood Glucose Prediction by Deep Learning with Cohort Arrangement and Quarterly Measured HbA1c

Previously published photoplethysmography-(PPG) based non-invasive blood glucose (NIBG) measurements have not yet been validated over 500 subjects. As illustrated in this work, we increased the number subjects recruited to 2538 and found that the prediction accuracy (the ratio in zone A of Clarke’s...

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Detalles Bibliográficos
Autores principales: Chu, Justin, Yang, Wen-Tse, Lu, Wei-Ru, Chang, Yao-Ting, Hsieh, Tung-Han, Yang, Fu-Liang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8659475/
https://www.ncbi.nlm.nih.gov/pubmed/34883817
http://dx.doi.org/10.3390/s21237815

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8659475/
https://www.ncbi.nlm.nih.gov/pubmed/34883817
http://dx.doi.org/10.3390/s21237815

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