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Improved individual and population-level HbA1c estimation using CGM data and patient characteristics
Machine learning and linear regression models using CGM and participant data reduced HbA1c estimation error by up to 26% compared to the GMI formula, and exhibit superior performance in estimating the median of HbA1c at the cohort level, potentially of value for remote clinical trials interrupted by...
Autores principales: | Grossman, Joshua, Ward, Andrew, Crandell, Jamie L., Prahalad, Priya, Maahs, David M., Scheinker, David |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8316291/ https://www.ncbi.nlm.nih.gov/pubmed/34127370 http://dx.doi.org/10.1016/j.jdiacomp.2021.107950 |
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