Estimating Breakfast Characteristics Using Continuous Glucose Monitoring and Machine Learning in Adults With or at Risk of Type 2 Diabetes.
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| Title: | Estimating Breakfast Characteristics Using Continuous Glucose Monitoring and Machine Learning in Adults With or at Risk of Type 2 Diabetes. |
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| Authors: | Pai R; Department of Electrical and Computer Engineering, Rice University, Houston, TX, USA., Barua S; Department of Electrical and Computer Engineering, Rice University, Houston, TX, USA.; Division of Precision Medicine, Department of Medicine, Grossman School of Medicine, New York University, New York City, NY, USA., Kim BS; Department of Electrical and Computer Engineering, Rice University, Houston, TX, USA., McDonald M; Department of Electrical and Computer Engineering, Rice University, Houston, TX, USA., Wierzchowska-McNew RA; Center for Translational Research in Aging and Longevity, Texas A&M University, College Station, TX, USA., Pai A; Department of Electrical and Computer Engineering, Rice University, Houston, TX, USA., Deutz NEP; Center for Translational Research in Aging and Longevity, Texas A&M University, College Station, TX, USA., Kerr D; Center for Health Systems Research, Sutter Health, Santa Barbara, CA, USA., Sabharwal A; Department of Electrical and Computer Engineering, Rice University, Houston, TX, USA. |
| Source: | Journal of diabetes science and technology [J Diabetes Sci Technol] 2026 Mar; Vol. 20 (2), pp. 365-373. Date of Electronic Publication: 2024 Sep 23. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Sage Country of Publication: United States NLM ID: 101306166 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1932-2968 (Electronic) Linking ISSN: 19322968 NLM ISO Abbreviation: J Diabetes Sci Technol Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1932-2968 |
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| DOI: | 10.1177/19322968241274800 |
