ArticleJMIR research protocols2025
Use of Machine Learning to Predict Individual Postprandial Glycemic Responses to Food Among Individuals With Type 2 Diabetes in India: Protocol for a Prospective Cohort Study.
Article in JMIR research protocols, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Artificial Intelligence in Food-Nutrition-Health Research: From Multimodal Data Integration to Precision Intervention.Journal of food science · 2026Review
- Evolution of Biosensors and Current State-of-the-Art Applications in Diabetes Control.Biosensors · 2026Review
- Women's Occupational Tobacco Dust Exposure in Indonesia (T-CHARM): Protocol for a Prospective Cohort Study.JMIR research protocols · 2025Article
- Artificial intelligence in personalized nutrition and food manufacturing: a comprehensive review of methods, applications, and future directions.Frontiers in nutrition · 2025Review
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Authors and funding
4 authors.
Funding
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Abstract
backgroundType 2 diabetes (T2D) is a leading cause of premature morbidity and mortality globally and affects more than 100 million people in the world's most populous country, India. Nutrition is a critical and evidence-based component of effective blood glucose control and most dietary advice emphasizes carbohydrate and calorie reduction. Emerging global evidence demonstrates marked interindividual differences in postprandial glucose response (PPGR) although no such data exists in India and previous studies have primarily evaluated PPGR variation in individuals without diabetes.
objectiveThis prospective cohort study seeks to characterize the PPGR variability among individuals with diabetes living in India and to identify factors associated with these differences.
methodsAdults with T2D and a hemoglobin A
resultsData collection commenced in May 2022, and the results will be ready for publication by September 2025. Results from our study will generate data to facilitate the creation of machine learning models to predict individual PPGR responses and to facilitate the prescription of personalized diets for individuals with T2D.
conclusionsThis study will provide the first large scale examination variability in blood glucose responses to food in India and will be among the first to estimate PPGR variability for individuals with T2D in any jurisdiction.
trial registrationClinical Trials Registry-India CTRI/2022/02/040619; https://tinyurl.com/mrywf6bf. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/59308.
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