Patient-Specific Data Input
Our system pulls from structured EMR data and patient-reported inputs, including:

1. Medical history and diagnoses (e.g., diabetes, CKD, cardiovascular disease)

2. Lab results (e.g., lipid panels, HbA1c, renal function)

3. Anthropometric data (e.g., BMI, body fat percentage)

4. Lifestyle, cultural, and dietary preferences

5. Food allergies and intolerances

AI-Driven Nutritional Mapping
Using advanced machine learning algorithms, the system cross-references:

1. Current clinical guidelines (ADA, AHA, KDOQI, etc.)

2. Nutritional databases and food composition data

3. Published literature on therapeutic diets and nutrient-disease interactions

Tailored Diet Plans
Clinically-aligned, personalized diet plans are generated to:

1. Support specific treatment goals (e.g., glycemic control, blood pressure reduction, weight loss, inflammation modulation)

2. Adjust macronutrients and micronutrients based on medical conditions

3. Recommend appropriate meal timing, portion sizes, and substitutions

4. Provide culturally appropriate and sustainable meal options