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This paper is in the following e-collection/theme issue:

Research Letter (8) New Methods (1799) Decision Support for Health Professionals (2249) Obesity and Nutrition as Public Health Problem (592) Diabetes Self-Management (731) Machine Learning (3199) Artificial Intelligence (4811) Artificial Intelligence in Diabetes Care and Prevention (112)

Published on in Vol 11 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/102715, first published .
Woman using smartphone while preparing fresh vegetables for healthy eating.

Toward Robust AI-Assisted Dietary Assessment for Diabetes Self-Management: Quantifying and Decomposing Large Language Model Prediction Variability From Meal Images

Toward Robust AI-Assisted Dietary Assessment for Diabetes Self-Management: Quantifying and Decomposing Large Language Model Prediction Variability From Meal Images

Authors of this article:

Zhaohua Wang1 Author Orcid Image ;   Daniel Lane1 Author Orcid Image ;   Kayo Waki1, 2 Author Orcid Image
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Zhaohua Wang   1 , MS ;   Daniel Lane   1 , MS, MBA ;   Kayo Waki   1, 2 , MD, MPH, PhD

1 Department of Health and Behavioral Informatics & Therapeutics (HABIT), Graduate School of Medicine, The University of Tokyo, Bunkyo-ku, Tokyo, Japan

2 Department of Diabetes and Metabolic Diseases, The University of Tokyo Hospital, Tokyo, Japan

Corresponding Author:

  • Kayo Waki, MD, MPH, PhD
  • Department of Health and Behavioral Informatics & Therapeutics (HABIT), Graduate School of Medicine
  • The University of Tokyo
  • Faculty of Medicine Bldg. 2, 2nd Floor, 7-3-1 Hongo
  • Bunkyo-ku, Tokyo 113-0033
  • Japan
  • Phone: 81 3-5841-1892 ext 21892
  • Email: kwaki-tky@m.u-tokyo.ac.jp