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Deduction learning for precise noninvasive measurements of blood glucose with a dozen rounds of data for model training
Personalized modeling has long been anticipated to approach precise noninvasive blood glucose measurements, but challenged by limited data for training personal model and its unavoidable outlier predictions. To overcome these long-standing problems, we largely enhanced the training efficiency with t...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9021306/ https://www.ncbi.nlm.nih.gov/pubmed/35444228 http://dx.doi.org/10.1038/s41598-022-10360-3 |