Nutrisha combines generative AI with MeldRx's FHIR platform to prevent adverse food-health interactions and provide personalized nutrition guidance, demonstrating significant potential for improving patient outcomes through smart dietary recommendations.

Inspiration

I am personally interested in nutrition and helping people get better at following advice from their doctors!

What it does

📅 Smart Diet Planning

  • Health-Aware Recommendations: Automatically considers:
    • Active health conditions
    • Current medications
    • Recent lab results
    • Dietary restrictions
    • Food allergies

🔍 AI-Powered Food Analysis

  • Intelligent Image Recognition: Upload meal photos for:
    • Precise nutritional breakdown
    • Medication interaction warnings
    • Health condition considerations
    • Smart portion recommendations

🎨 User Experience

  • Intuitive interface with light/dark modes
  • Seamless health data integration
  • Real-time recommendations

Healthcare Impact

  • Prevention of adverse food-medication interactions
  • Improved medication timing compliance
  • Enhanced dietary adherence through personalization
  • Accessible nutrition guidance for patients with complex health conditions

Predictive Accuracy

  • Limited to the underlying accuracy of gpt-4o-mini
  • Limited to the underlying accuracy of the FHIR resources

How we built it

Starting from MeldRx's React template, I implemented the SMART on FHIR launch flow. Next, I wrote FHIR queries to get the necessary data and filtered it for relevant parts (like diabetes condition, weight, height Observations). Then, I started to experiment with generating nutrition plans from this data using OpenAI's API. Lastly, I explored using the Vision API to analyze images of meals.

System Diagram

Diagram

🔬 Advanced Integration Features

  1. Comprehensive FHIR Integration

    • Utilizes 6 critical FHIR resources for complete health context
    • Real-time synchronization with health records
    • Intelligent processing of clinical data for dietary impact
  2. State-of-the-Art AI Implementation

    • OpenAI gpt-4o-mini for intelligent diet planning
    • OpenAI gpt-4o-mini for real-time food analysis
    • Custom prompt engineering with structured JSON schema responses
    • Advanced vision-language modeling for food recognition
  3. Predictive Healthcare Features

    • Anticipates medication-food interactions
    • Predicts nutritional needs based on lab trends
    • Suggests preventive dietary modifications

Challenges we ran into

Many! The MeldRx React template took some modification to get started. I made many API requests and had to ask for an increase. The OpenAI calls were tricky to figure out because I used structured outputs - and the responses were deeply nested.

Accomplishments that we're proud of

Getting it working and submitting!

What we learned

I did not know about SNOMED, LONIC, or ICD-10 before starting this project. I learned a lot about FHIR and OpenAI's models.

What's next for Nutrisha

Saving and exporting diet plans.

Built With

Share this project:

Updates