ArticleFrontiers in nutrition2026
Comparative accuracy of automated carbohydrate estimation using NutriDish and ChatGPT-5 against dietitian-derived reference values.
Article in Frontiers in nutrition, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Accurate carbohydrate estimation is critical for insulin dosing in individuals with diabetes on multiple daily injections. Conventional methods such as visual estimation and food exchange systems are inconsistent, particularly in multicultural Asian settings where portion sizes vary and nutritional labeling is limited. NutriDish is an AI-powered system designed to automates carbohydrate estimation from food images. Objective: This study compared the accuracy of carbohydrate estimates generated by NutriDish and ChatGPT-5 against reference values established by a dietitian using weighed food portions. Methods: Between July and August 2025, food items were collected from hawker centers, food courts, restaurants, and homes, supermarkets, and convenience stores across Singapore to capture the region's diverse culinary landscape. Items were classified as simple foods or composite meals. NutriDish and ChatGPT-5 independently estimated carbohydrate content, while a dietitian established reference values using weighing portions and a validated nutrient database. Accuracy was assessed using Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), proportion of estimates within ± 10 g of the reference value, and Bland-Altman analysis. Results: Across 150 food items, NutriDish achieved significantly lower MAE [5.9 ± 5.3 g (median: 4.1 g, IQR: 1.0-9.0) vs. 8.7 ± 7.4 g (median: 6.0 g, IQR: 3.0-13.4); Conclusion: NutriDish demonstrated good agreement with dietitian-derived carbohydrate estimates, highlighting its potential to aid carbohydrate counting in individuals treated with insulin. Future studies should evaluate real-world clinical usability, integration into diabetes self-management ecosystems and impact on long-term glycemic control.
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