A health screening interface built to read like a briefing, not a generic dashboard.
The product combines structured intake, predictive scoring, result review, and longitudinal history in one frontend connected to a FastAPI service and machine learning pipeline.
Workflow
End to end
Assessment, scoring, review, history, and analytics share one UI system.
Model shape
1 + 3
Three disease streams feed one composite signal.
Clinical stance
Supportive
Useful for early interpretation, never a replacement for diagnosis.
Methodology
Training sources and modeling strategy
The frontend is explicit about what informs the predictions so users can judge credibility and fit.
Each disease stream can include multiple candidate models and ensemble logic, with explainability and recommendations layered on top of the prediction workflow.
Technology stack
Current build architecture
The redesign focuses on frontend cohesion, but the interface remains aligned with the actual backend and model workflow.
Frontend
- Next.js 16.1.6
- React 19.2.4
- TypeScript 5.9
- Tailwind CSS
Backend
- FastAPI
- SQLAlchemy
- SQLite or PostgreSQL-backed storage
- scikit-learn model pipeline
Important disclaimer
This is not medical advice
The application is designed for education, exploration, and clinical decision support workflows. It does not diagnose disease and should not be used as a substitute for professional care.
Model limitations