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AI meal photo scanning

How to use a food photograph in Gluchol, check ingredients and portions, and interpret educational blood sugar, cholesterol and dietary salt estimates.

Can a photo tell you how food may affect blood sugar?

A photo can help identify likely foods and support an educational meal estimate. It cannot measure carbohydrate precisely, detect every ingredient, or predict a guaranteed glucose response. Gluchol uses food recognition as an input to its meal-analysis process, not as a substitute for measurement.

How to get a more useful meal entry

Photograph the whole meal in good light. Check the food names, estimated portions and accompanying items before accepting the entry. Add or correct drinks, sauces, dressings and ingredients that are not visible.

A bowl of rice with a sauce can contain very different amounts of carbohydrate, salt and fat depending on serving size and recipe. Correcting those assumptions is more important than assuming that a confident-looking image recognition result is exact.

Read the three outputs separately

Review the glucose-impact estimate alongside cholesterol-related and blood-pressure-related dietary factors. A food can score differently for different reasons. Compare realistic portions rather than selecting an option solely because of one category.

If you use a glucose monitor or follow a clinician's meal plan, keep doing so. Photo-based estimates do not replace those tools or instructions.

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Build a clearer picture of your meals

Explore food choices with Gluchol’s educational estimates, with context for what they can and cannot tell you.