https://github.com/subhradeep1708/karmatek-2025-organa
Smart Organ & Blood Donation Network - A smart network connecting organ/blood donors with recipients using a scoring algorithm and generative AI for optimized matches and analysis.
https://github.com/subhradeep1708/karmatek-2025-organa
fastapi gemini-api generative-ai nextjs postgresql pydantic python shadcn-ui socket-io sqlalchemy tailwind-css websocket zod-validation zustand-state-management
Last synced: 30 days ago
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Smart Organ & Blood Donation Network - A smart network connecting organ/blood donors with recipients using a scoring algorithm and generative AI for optimized matches and analysis.
- Host: GitHub
- URL: https://github.com/subhradeep1708/karmatek-2025-organa
- Owner: Subhradeep1708
- Created: 2025-02-08T16:07:27.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2025-02-08T16:25:10.000Z (9 months ago)
- Last Synced: 2025-02-08T17:23:01.846Z (9 months ago)
- Topics: fastapi, gemini-api, generative-ai, nextjs, postgresql, pydantic, python, shadcn-ui, socket-io, sqlalchemy, tailwind-css, websocket, zod-validation, zustand-state-management
- Language: TypeScript
- Homepage:
- Size: 4.23 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
🩸 Organa: Smart Organ Donation Network & Notification System 🏥
Connecting donors and recipients through AI-driven precision.
📖 Table of Contents
🔍 Overview
Organa is a platform designed to revolutionize organ and blood donation by intelligently matching donors with recipients.
Using a proprietary scoring algorithm and generative AI, the system analyzes medical data, urgency,
compatibility, and geographic factors to prioritize and optimize life-saving connections.
✨ Features
- 🚀 Smart Matching Algorithm: Prioritizes matches based on medical compatibility, urgency, and logistics.
- 🤖 Generative AI Analysis: Predicts transplant success rates and generates donor-recipient compatibility reports.
- 🩺 Real-Time Donor-Recipient Network: Live updates for blood/organ availability and recipient needs.
- 🔔 Automated Alerts: Notify hospitals, donors, and recipients of critical matches.
- 📊 Analytics Dashboard: Track donation trends, success rates, and system performance.
- 📝 Collects Data to Train Model: Organ and patient data is collected in real-time from hospitals, including details like organ type, condition, blood type, patient medical history, and urgency. This data is crucial for developing a machine learning model to improve matching accuracy.
-
🌐Centralised Network:
The system creates a centralized network that allows hospitals to share available organs with nearby hospitals if they match a patient from their list. This eliminates manual interventions and speeds up the organ-sharing process.
⚙ Screenshots
Home Page
Login Page
Dashboard Preview
Patient Waitlist
New Available Organ Addition Page(Form)
Organ Match Notifications
AI Powered Organ Match Analysis
Organ Data Page (Dark Mode)
⚙ Installation
```
# Clone the repository
git clone https://github.com/Subhradeep1708/Karmatek-2025-Organa
```
### Backend (Python + Fast API)
```
cd backend
# Create A Virtual Environment
python -m venv venv
# Activate The Virtual Env
./venv/Scripts/activate
# Install All the dependencies
pip install -r requirements.txt
# Run the developmen server
uvicorn app.main:app --reload
```
### Frontend (Next.js)
```
cd frontend
# Install Dependencies
bun install
# Configure .env
# Run the development Server
bun run dev
```
### Notification Service
```
cd ws
# Install Dependencies
bun install
# Configure .env
# Run the development Server
bun run dev
```
🚀 Usage
- Register as a donor or recipient with medical credentials.
- The system automatically matches donors/recipients using the scoring algorithm.
- Generative AI analyzes compatibility and generates risk/success reports.
- Receive real-time alerts for matches via email/SMS.
- Access the dashboard to view analytics and manage donations.
👥 Contributing
Contributions are welcome! Follow these steps:
- Fork the repository.
- Create a feature branch (
git checkout -b feature/AmazingFeature). - Commit changes (
git commit -m 'Add AmazingFeature'). - Push to the branch (
git push origin feature/AmazingFeature). - Open a Pull Request.
📜 License
Distributed under the MIT License. See LICENSE for details.
🙏 Acknowledgments
- Generative AI Model: Gemini Flash 1.5
- UI Framework: React, Next.js, ShadCN
📞 Contact
Project Maintainers:
subhradeep1708@gmail.com
GitHub: @Subhradeep1708