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.

Journal: JMIR research protocols
PMID:

Abstract

BACKGROUND: Type 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.

Authors

  • Niteesh K Choudhry
    Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA.
  • Shweta Priyadarshini
    Decipher Health, Delhi, India.
  • Jaganath Swamy
    Decipher Health, Delhi, India.
  • Mridul Mehta
    Decipher Health, Delhi, India.