AI-Powered Lab Result Analysis
A fullstack web application that explains medical lab results in an understandable way for non-medical users. The focus is not on using AI as a buzzword, but on integrating it in a controlled, transparent, and technically sound manner into a real-world application.
-
Core Concept:
Clear Data → Clean API → Controlled AI Output
Many people receive lab reports but struggle to understand them. Medical terminology, reference ranges, and risk assessments are often difficult for laypeople to interpret. -
Features:
- 🧠 AI-based explanation of lab values
- ⚠️ Risk level assessment with recommendations (not medical diagnosis)
- 🧾 Structured result presentation in a clear card-based UI
- 📊 History & trend visualization for repeated measurements
- 📄 PDF export of analysis results
- 🔐 Privacy-friendly processing – no permanent storage of sensitive data
-
Technical Focus:
- Clearly defined API contract between frontend and backend
- Prompt engineering for structured, predictable JSON responses
- Backend validation & parsing of AI outputs
- Separation of business logic, AI logic, and presentation layer
- Frontend-ready API design for easy extensibility
- Backend: Java, Spring Boot, REST API, OpenAI API
- Frontend: React, Vite
- Infrastructure: Docker, Render (Backend), Vercel (Frontend)
- Tools: Git, GitHub, Postman
Project Goal:
Demonstrate how AI can be meaningfully, responsibly, and controllably integrated into a real
software solution — not as an end in itself, but as a supporting tool within a stable
architecture.
Disclaimer: This application is for informational purposes only. It does not replace medical diagnosis, consultation, or treatment. For health-related questions, always consult qualified medical professionals.