Health Risk Prediction System
Full-stack ML/DL/QML app for early health-risk inference
RoleDesigner & sole engineer
PeriodFeb 2025 — Mar 2025
StackPython, Flask, TensorFlow, Keras, QML
Categoryml, systems
Problem
Early risk signals in patient data go unflagged without manual review.
Approach
- Built a full-stack application for early health-risk prediction, comparing classical ML, deep learning, and quantum ML (QML) approaches
- Implemented a secure Flask backend managing 100+ user records with authentication and role-based access
- Automated risk inference and reporting to cut manual analysis effort
Pipeline
User input
Flask API
ML / DL / QML inference
Risk report
Outcomes
Model accuracy~85%
Manual analysis effort cut~60%
User records managed100+