BULLTZ's diet program generation utilizes the principles of nutrigenomics, first calculating the basal metabolism based on the user's physical examination data or self-reported indicators (e.g., body fat rate of 28%), and then combining it with the training consumption to build a dynamic calorie model. The system database contains the nutritional composition of 6000+ ingredients and 200 dietary pattern characteristics, and the intelligent matching not only takes into account the macro-nutritional ratios (e.g., ketogenic diet to keep carbohydrates <5%), but also learns the preferences recorded in the user's dietary logs (e.g., lactose intolerance markers). The solution output presents three innovative forms: visual nutrition clock (recommended nutrient intake ratio for each time period), intelligent food substitution (braised pork replaced with rosemary roasted chicken thighs), and scenario-based purchasing list (recommended by 3-day dosage).
In practice, the system will continuously track 10 key indicators: including micronutrient intake adequacy, dietary fiber compliance, and postprandial blood sugar fluctuation prediction. When users eat out, they only need to upload a photo of the menu, and the AI can give the best choice suggestions within 3 seconds (e.g. "Recommended choice is grilled salmon in the third item, with a protein quality score of 92/100″). Clinical data shows that after 12 weeks of use, the optimization of the user's dietary structure is 2.3 times higher than that of a regular calorie calculator.
This answer comes from the articleBULLTZ: Artificial Intelligence Personal Fitness AppsThe
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