Lifestyle medicine at Loma Linda University Health
Food plans built on the evidence, not guesswork
Enter a patient's conditions, medicines, and allergies. You get a plant-forward eating plan made for them, with a source behind every recommendation.
Try a sample patient
or build your own →Marcus, 54
54-year-old man with prediabetes and high cholesterol; not yet on medication.
Prediabetes
Dyslipidemia / CVD risk
Eleanor, 62
62-year-old woman with type 2 diabetes, hypertension, and stage 3b CKD. Takes lisinopril, metformin, and atorvastatin.
Type 2 diabetes
Hypertension
Chronic kidney disease
Doris, 67
67-year-old woman on warfarin for atrial fibrillation, with hypertension.
Hypertension
Aisha, 45
45-year-old woman managing weight and cholesterol; prefers a vegan diet and has a peanut allergy.
Overweight / obesity
Dyslipidemia / CVD risk
Priya, 32
32-year-old woman, 24 weeks pregnant, with new prediabetes.
Prediabetes
Robert, 70
70-year-old man with stage 4 CKD, hypertension, and type 2 diabetes.
Chronic kidney disease
Hypertension
Type 2 diabetes
A source behind every line
Each recommendation and number traces back to USDA data or a professional guideline. No AI writes the medical advice.
Safety first
We check food and drug interactions, disease limits, and allergies, and step back to a clinician when that is the safer call.
Built around the patient
A plant-forward plan shaped by the patient's conditions, medicines, allergies, and tastes, with room for a clinician to adjust it.
How it works
- 1Pick a sample patient, or enter age, conditions, medicines, allergies, and food preferences.
- 2We pull the matching evidence, set targets across every condition, and sort out anything that conflicts.
- 3You get an eating plan and recipes that fit, with a source behind every line.