Organ Bridge
Description:
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Designed ML pipeline matching donors to recipients using TF-IDF + cosine similarity on 15+ clinical features (blood type, urgency, proximity, etc.) — 95% accuracy on 900+ records.
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Full-stack: Backend REST API (Django) + Frontend (Tailwind/HTMX) + ML model serialization.
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Implemented business rules layer (blood type constraints, urgency prioritization) on top of ML scores.
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Achieved sub-second inference time for real-time recommendations in production environment.
Tools:
All the tools that I used in this project:
Django Python Scikit-learn (TF-IDF Cosine Similarity Random Forest) Tailwind CSS HTMX Alpine.js SQLite Jazzmin django-widget-tweaks