🩺 AI Healthcare Research Assistant

🌟 Project Overview

The AI Healthcare Research Assistant is an advanced, AI-powered platform designed to revolutionize medical research by providing intelligent insights, accelerating data analysis, and supporting critical decision-making in healthcare.

🚀 Key Features

1. 🔬 Clinical Trials Explorer

• Analyze and discover the latest clinical trials
• Comprehensive research data visualization
• Advanced filtering and search capabilities

2. 🩺 Disease Prediction System

• AI-driven predictive modeling for disease progression
• Machine learning-based risk assessment
• Personalized health insights generation

3. 💊 Treatment Innovation Tracker

• Discover cutting-edge treatment approaches
• Analyze potential medical interventions
• Research-driven treatment strategy development

4. 📚 Medical Literature Review

• Automated comprehensive research summaries
• AI-powered insight extraction
• Cross-referencing medical literature

🛠 Technology Stack

• Frontend: Streamlit
• Backend: Python
• AI Models:
  • OpenRouter LLM
  • Custom Machine Learning Models
• Data Processing: Pandas
• Deployment: Containerized Application

📋 Prerequisites

System Requirements

• Python 3.8+
• pip (Python Package Manager)
• Git

Required Dependencies

• streamlit
• pandas
• openrouter-ai
• python-dotenv
• scikit-learn

🔧 Installation

1. Clone the Repository

https://github.com/DadvaiahPavan/AI-Healthcare-Research-Assistant.git
cd ai-healthcare-research

2. Create Virtual Environment

python -m venv venv
source venv/bin/activate  # On Windows, use `venv\Scripts\activate`

3. Install Dependencies

pip install -r requirements.txt

4. Set Up Environment Variables

Create a .env file in the project root:

OPENROUTER_API_KEY=your_openrouter_api_key

🚀 Running the Application

streamlit run app.py

🔐 Security and Privacy

• All patient data is processed locally
• No personal information is stored or transmitted
• Compliance with medical data protection standards
• Anonymized data processing

🤝 Contributing

Contribution Guidelines

1. Fork the repository
2. Create a feature branch
3. Commit your changes
4. Push to the branch
5. Create a Pull Request

Code of Conduct

• Respect medical research ethics
• Maintain patient data confidentiality
• Provide constructive feedback

📊 Project Structure

ai-healthcare-research/
│
├── app.py                 # Main Streamlit application
├── .env                   # Environment variables
├── requirements.txt       # Project dependencies
│
├── src/                   # Source code
│   ├── drug_discovery.py
│   ├── data_processor.py
│   └── ...
│
├── data/                  # Sample and processed data
│   ├── clinical_trials/
│   └── medical_datasets/
│
└── docs/                  # Documentation
    └── ...

🧪 Testing

Running Tests

python -m pytest tests/

📈 Future Roadmap

• Enhanced machine learning models
• More comprehensive medical databases
• Real-time research updates
• Advanced predictive analytics

📜 License

MIT License

🙏 Acknowledgments

• OpenRouter AI
• Medical Research Community
• Open-source Contributors

📞 Contact

• Project Maintainer: Dadvaiah Pavan
• Email: Pavannetha219@gmail.com
• LinkedIn: https://www.linkedin.com/in/dadvaiah-pavan/

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Disclaimer: This is a research tool and should not replace professional medical advice. Always consult healthcare professionals for medical guidance.