Toward Robust AI-Assisted Dietary Assessment for Diabetes Self-Management: Quantifying and Decomposing Large Language Model Prediction Variability From Meal Images
- DOI
- 10.2196/102715
- Published
- 2026-09-04
- Container
- JMIR Diabetes
- Publisher
- JMIR Publications Inc.
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.2196/102715,
title = {Toward Robust AI-Assisted Dietary Assessment for Diabetes Self-Management: Quantifying and Decomposing Large Language Model Prediction Variability From Meal Images},
author = {Zhaohua Wang and Daniel Lane and Kayo Waki},
year = {2026},
journal = {JMIR Diabetes},
doi = {10.2196/102715},
url = {https://doi.org/10.2196/102715}
}RIS
TY - JOUR TI - Toward Robust AI-Assisted Dietary Assessment for Diabetes Self-Management: Quantifying and Decomposing Large Language Model Prediction Variability From Meal Images AU - Zhaohua Wang AU - Daniel Lane AU - Kayo Waki PY - 2026 JO - JMIR Diabetes DO - 10.2196/102715 UR - https://doi.org/10.2196/102715 ER -
APA
Wang, Z., Lane, D., & Waki, K. (2026). Toward Robust AI-Assisted Dietary Assessment for Diabetes Self-Management: Quantifying and Decomposing Large Language Model Prediction Variability From Meal Images. JMIR Diabetes. https://doi.org/10.2196/102715
Source records
- crossref · retrieved 2026-09-25T00:00:06.808Z