Healthcare AI · 2021
Heart Disease Prediction in Hospital Management
Academic Capstone · B.E. Computer Engineering
01
Problem
Hospital workflows and clinical risk screening lived in disconnected systems with limited predictive support.
02
Challenge
Integrate an AI heart-disease prediction model into a full Django hospital management system without breaking operational UX.
03
Solution
Built an AI-based prediction module inside a Django HMS covering patients, workflows, and clinical data surfaces.
04
Impact
Showcased end-to-end product thinking—from ML model to production-shaped hospital software—well before that pairing became a job requirement.
Approach
- 01
Trained and validated a heart-disease risk classifier on a standard clinical dataset before integration work began.
- 02
Designed the Django data model so patient records, appointments, and prediction outputs shared a single operational schema.
- 03
Built the prediction module as a workflow step inside patient intake rather than a separate standalone tool.
- 04
Tested the combined system for both model behavior and standard hospital-management functionality.
Outcomes
- Working prediction module embedded directly in patient workflows, not a standalone script
- Full-stack Django hospital management system covering patients, staff, and records
- End-to-end delivery from trained model to usable application UI
- Early proof point for the healthcare-AI thread that later informed consulting engagements