Thanks to advances in AI, popular calorie-tracking apps can now use a photo of a meal to estimate the nutritional content of what you're eating. Although these apps are convenient, a new study found that four photo-based apps underestimated the calories and fat content of meals by about a third. Photo-based calorie tracking uses AI image recognition to identify foods in a meal photo and estimate portion sizes. This information is then compared with nutrition databases to calculate estimated calories and nutrients. Photo-based calorie tracking apps are very popular, especially for people trying to manage their health or lose weight. However, the accuracy of many of these apps has not been thoroughly evaluated. Our study helps address this question by looking at whether these apps can reliably estimate calories." Aaron Hengist, postdoctoral visiting fellow with the Intramural Program, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), part of the National Institutes of Health Olivia Charles, a postbaccalaureate intramural research training fellow at NIDDK, will present the findings at NUTRITION 2026, the flagship annual meeting of the American Society for Nutrition, held July 25–28 in National Harbor, Maryland, just outside Washington, D.C. The new research is part of a larger diet study at the NIH Clinical Center examining how the body processes nutrients when a person eats a low-carbohydrate (ketogenic) or standard diet. Meals for this clinical trial are prepared in a controlled metabolic kitchen, a type of research kitchen where ingredients are carefully weighed to the nearest 0.1 gram. To evaluate how well photo-based calorie-tracking apps estimate nutritional content from images, the researchers acquired standardized photos of 102 meals prepared as part of the diet study and then ran them through the MyFitnessPal, LoseIt!, CalAI and Appediet apps. "By using meals prepared in a tightly controlled metabolic kitchen,