An AI-powered web application that helps users understand possible health issues from medical images using the Google Gemini API.
Warning
Disclaimer: This tool is for educational and informational purposes only. Always consult a qualified doctor before making any medical decisions.
👉 disease-identifier.streamlit.app
- 📤 Upload medical images (JPG or PNG)
- 🤖 AI-based disease analysis powered by Google Gemini
- 📋 Generates a structured report including:
- Detailed Analysis
- Findings Report
- Recommendations
- Treatment Suggestions
- ⚡ Fast and interactive UI built with Streamlit
User uploads image
↓
Streamlit Interface
↓
Gemini API processes image
↓
AI generates response
↓
Structured output shown to user
| Layer | Technology |
|---|---|
| Frontend / UI | Streamlit |
| Backend | Python |
| AI Model | Google Gemini API |
| Deployment | Streamlit Cloud |
- Python 3.x installed
- Streamlit installed
1. Clone the repository
git clone https://github.com/fizaayesha/disease_identifier.git
cd disease_identifier2. Create and activate a virtual environment
python -m venv venv- On Linux / Mac:
source venv/bin/activate - On Windows:
venv\Scripts\activate
3. Install dependencies
pip install -r requirements.txt4. Add your API key
Create a .streamlit/secrets.toml file and add:
GOOGLE_API_KEY = "your-google-api-key"5. Run the application
streamlit run app.pyContributions are welcome! 🚀
- Fork the repository
- Create a new branch:
git checkout -b feature/your-feature-name - Make your changes
- Commit and push:
git commit -m "Add your message"→git push origin feature/your-feature-name - Open a Pull Request
For detailed guidelines, check the CONTRIBUTING.md file.
New to open source? Start with beginner-friendly tasks:
- 🎨 Improving UI/UX
- ⏳ Adding loading indicators
- ✅ Adding input validation
- 🛡️ Improving error handling
Find these tasks under issues labeled good-first-issue.
This project is open source. See the LICENSE file for details.