A cutting-edge platform designed to assist healthcare professionals in diagnosing glaucoma and accessing the latest research in eye care! Leveraging machine learning and large language models, this platform provides a powerful suite of tools for retinal analysis, disease detection, and personalized insights.

🔬 EyeVanguard is a subscription-based platform for hospitals that integrates modern technology to advance the diagnosis and treatment of glaucoma. The key features include:

1. 📚 Research Hub: Search and access the latest research papers and discoveries in eye research.
2. 🧑‍⚕️ AI-Powered Doctor's Assistant: A custom-built LLM-based agent that assists doctors in analyzing complex eye conditions.
3. 🖼️ Glaucoma Detection: Upload FUNDUS images for precise and quick AI-based analysis of retinal conditions.
4. ⚡ Seamless Integration: Built with React.js for the frontend, Flask for the backend, and PostgreSQL for robust data management.

• LLM Doctor Assistant Bot: Get real-time analysis and recommendations for eye diseases.
• Fundus Image Analysis: Upload retina images for deep analysis and detection using advanced AI models.
• Research Paper Hub: Stay updated with the latest discoveries in ophthalmology.

• Frontend: React.js ⚛️
• Backend: Flask 🐍
• Database: PostgreSQL 🐘
• Machine Learning Models: Trained AI models for FUNDUS image detection.

EyeVanguard/
├── frontend/               # React.js frontend
│   ├── public/             # Public assets and files
│   ├── src/                # Source code for React components
│   │   ├── components/     # UI components
│   │   ├── pages/          # Pages like Home, Research, and Upload
│   │   ├── services/       # API services to interact with backend
│   ├── .env                # Environment variables for frontend
│   ├── package.json        # Node.js dependencies
│   └── README.md           # Frontend-specific README
├── backend/                # Flask backend
│   ├── app/                # Main app folder
│   │   ├── models/         # Machine learning models (FUNDUS detection)
│   │   ├── routes/         # API routes
│   │   ├── services/       # Business logic and LLM bot integration
│   ├── database/           # PostgreSQL database models and migrations
│   ├── .env                # Backend environment variables
│   ├── requirements.txt    # Python dependencies
│   └── README.md           # Backend-specific README
├── models/                 # Pretrained AI models for glaucoma detection
├── docs/                   # Documentation for the project
├── docker-compose.yml      # Docker configuration for containerization
├── README.md               # Main README (you are here!)
└── .gitignore              # Git ignore rules

Follow these instructions to get the project up and running on your local machine.

• Node.js and npm (for the frontend)
• Python 3.x and pip (for the backend)
• PostgreSQL (for the database)

    git clone https://github.com/N-Thander/GlaucomaDetection
    cd GlaucomaDetection

This project is a collaborative effort of:

N-Thander

Vaibhav2002

AbhayShaw01

anwesha2002

This project is licensed under the MIT License. See the LICENSE file for details.

• 🦾 AI-Powered Research Summaries: Summarize key insights from the latest research papers.
• 📊 Advanced Analytics Dashboard: Provide doctors with deep insights into patient data and analysis trends.
• 🔗 Hospital Integration: Seamless integration with hospital databases and systems for patient data exchange.

💡 PS This project is being developed as part of our final year college project. We aim to revolutionize glaucoma detection in hospitals through AI-driven insights and seamless research integration.