AI-Powered Carbohydrate Counting for Type 1 Diabetes: Accuracy and Real-World Performance.
Creators
- 1. Department of Clinical Medicine and Surgery and Department of Endocrinology, University of Naples Federico II, Naples, Italy.
- 2. University of Naples Federico II
- 3. Department of Psychology and Health Sciences, Pegaso Telematic University, Naples, Italy.
- 4. Department of Education and Sport Sciences, Pegaso Telematic University, Naples, Italy.
- 5. Unesco Chair for Health Education and Sustainable Development, University of Naples Federico II, Naples, Italy.
Publication Details
Other
Journal:
Diabetes care
Publisher:
American Diabetes Association
ISSN:
19355548
Volume:
48
Pages:
e97-e98
Funding
Financial Support
National Recovery and Resilience Plan (NRRP), Mission 4, Component 2, Investment 1.3, ON Foods Research and Innovation Network on Food and Nutrition Sustainability, Safety and Security Working ON Foods?
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References
Vetrani . Dietary determinants of postprandial blood glucose control in adults w...
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Amorim . Assessing carbohydrate counting accuracy: current limitations and futur...
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American Diabetes Association Professional Practice Committee . Standards of Car...
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Smart . Can children with type 1 diabetes and their caregivers estimate the carb...
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Evert . Factors beyond carbohydrate to consider when determining meantime insuli...
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Scholarly Citations
Cited by other scholarly works
063-379-735-927-953
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