University of Arizona
ARTISAN Center · Georgia Tech
Univ. of Arizona × Georgia Tech

Food is the most powerful medicine we have

A personalized, AI-powered tool helping community nutrition programs match patients with healing foods — grounded in evidence, culture, and access.

A
University of Arizona
Tucson, AZ · School of Nutritional Sciences and Wellness
×
Collaboration
GT
ARTISAN Center
Georgia Institute of Technology · Atlanta, GA

How it works

From patient profile to personalized food plan

Care coordinators enter a few key details. The tool handles the rest — surfacing evidence-based food recommendations tailored to each person.

1

Profile the patient

Enter health conditions, dietary restrictions, cultural background, and local food access — nearby stores, food pantries.

2

Match to evidence

Cross-references a curated database of food-condition relationships, drawing on peer-reviewed nutrition science and ARTISAN-developed AI models.

3

Deliver a food plan

Generate a printable, plain-language food plan with specific foods, preparation tips, and culturally familiar recipes — ready to hand to the patient.

4

Track outcomes

Follow up across visits to log adherence, lab values, and patient-reported wellbeing — building a longitudinal picture of what's working.

Features

Designed for the realities of community health work

Built with input from community health workers, dietitians, and the people they serve — a practical field tool, not a clinical ivory tower.

Personalization

Condition-matched recommendations

Foods matched to specific diagnoses — diabetes, hypertension, anemia, obesity, depression — with adjustments for polypharmacy and comorbidities.

Access

Budget and pantry aware

Recommendations stay within realistic budgets and flag which foods are available at food banks, community gardens, or local farmers markets.

Culture

Culturally responsive food lists

Search by cuisine tradition — West African, South Asian, Mexican, Caribbean, Indigenous — to surface familiar ingredients patients will actually cook.

Evidence

Grounded in nutrition science

Every recommendation links to supporting evidence — from the USDA food database to peer-reviewed studies — so care teams can explain the why.

Output

Printable, multilingual plans

Generate plain-language food plans in English, Spanish, and more — formatted for low health literacy and ready to print or share digitally.

AI-Powered

ARTISAN AI model registry

Runs on curated, benchmarked AI models from the ARTISAN center — with an open registry so community programs contribute local food data back.

Who it's for

Meeting people where they are

Food is Medicine serves the full ecosystem of community nutrition programs — wherever the work happens.

Community health centers

FQHCs and free clinics using food prescriptions alongside medical care to address chronic disease in underserved populations.

Food pharmacies

Programs dispensing groceries alongside prescriptions — produce prescriptions, medically tailored meals, and food as a therapeutic intervention.

WIC & nutrition programs

Supplemental nutrition programs supporting infants, children, and pregnant people with evidence-based food guidance matched to individual needs.

School health programs

School nurses and community liaisons supporting students and families navigating food insecurity and diet-related conditions.

Researchers & evaluators

Public health researchers studying dietary interventions — with built-in outcome tracking and data export for analysis.

Community navigators

Promotoras, patient navigators, and CHWs who bridge clinical recommendations to lived reality — with tools that respect cultural context and language.

80%
of chronic disease is influenced by diet and lifestyle factors
3×
higher adherence when recommendations are culturally appropriate
$1 : $7
return on investment for food-as-medicine interventions in community settings
2+
research institutions combining AI, nutrition science, and community health

The team

Research leadership

A collaboration between precision nutrition scientists and AI research engineers — bridging the gap between cutting-edge omics science and community health programs.

University of Arizona
Dr. Sridevi Krishnan
Assistant Professor
School of Nutritional Sciences and Wellness
College of Agriculture, Life & Environmental Sciences

Dr. Krishnan leads a precision nutrition research program at UA focused on quantifying human variability in response to dietary interventions. Her work integrates glycoproteomics, multi-omic systems biology, and machine learning to understand how diet and protein glycosylation interact in metabolic disease — including type 2 diabetes and cardiovascular disease.

Precision Nutrition Glycoproteomics Multi-omics Systems Biology Machine Learning Metabolic Disease
Georgia Institute of Technology
Atlanta, GA
Center for Artificial Intelligence in Science and Engineering
ARTISAN · College of Computing × IDEaS

ARTISAN accelerates advances in science and engineering by integrating cutting-edge AI techniques with large-scale cyberinfrastructure. A joint center between Georgia Tech's College of Computing and the Institute for Data Engineering and Science, ARTISAN brings expertise in AI-driven scientific discovery, interpretable machine learning, and distributed computing systems — including the Nexus supercomputer — to the Food is Medicine project.

AI-Driven Solutions
Specialized ML for protein modeling, metabolomics, and population health
Cyberinfrastructure
Scalable distributed systems powering AI and scientific computing
Interpretable AI
Models that explain their recommendations for clinical trust
Open Registry
Curated, benchmarked AI model registry for community programs
Visit ARTISAN at Georgia Tech

Open Source

Built in the open, for the public good

Food is Medicine is open-source software — free to deploy, adapt, and extend. Community programs retain their data. Contributions of local food knowledge, recipes, and outcome evidence flow back to everyone.

  • MIT licensed — deploy on your own infrastructure, no vendor lock-in
  • HIPAA-conscious architecture — patient data stays with your program
  • Open model registry — contribute local food and outcome data back to the community
  • Active community of dietitians, developers, and community health workers
  • Documented API for integration with EHR and care management systems
View repository →
# Install pip install food-is-medicine # Get personalized recommendations from fim import FoodRecommender rec = FoodRecommender() plan = rec.recommend( conditions=["type2_diabetes", "hypertension"], budget="snap", cuisine_pref="mexican", language="es", registry="artisan-v1" ) plan.export_pdf("patient_plan.pdf") # → Personalized, printable food plan

Get involved

Help us build the nutrition tool community health deserves

Whether you're a dietitian, developer, community health worker, or someone who's lived it — your perspective makes this tool better.