This project provides a comprehensive analysis tool for predicting heart attack risks based on various health indicators. Utilizing a powerful backend developed with Flask, the application processes and analyzes health data, while the React-based frontend offers an intuitive interface for data input, analysis, and visualization.
- Data Input: Allows users to input individual health data for analysis.
- Risk Prediction: Utilizes machine learning models to predict heart attack risks based on input data.
- Data Visualization: Offers various data visualization tools to understand risk factors better.
Follow these instructions to get the project up and running on your local machine for development and testing purposes.
- Python 3.x
- Node.js and npm
- Flask (for the backend)
- React (for the frontend)
-
Clone the Repository
git clone https://github.com/your-username/heart-attack-risk-analysis.git cd heart-attack-risk-analysis -
Set Up the Backend
Navigate to the backend directory and install the required Python packages:
cd backend pip install -r requirements.txtStart the Flask server:
flask run
-
Set Up the Frontend
Navigate to the frontend directory and install the necessary npm packages:
cd ../frontend npm installStart the React development server:
npm start
- Use the frontend interface to input health data for analysis.
- View risk predictions and related health insights based on the provided data.
- Explore various data visualizations to understand the impact of different health indicators on heart attack risk.
Navigate to the backend directory and execute:
python -m unittest
Frontend Tests
Navigate to the frontend directory and execute:
sh
Copy code
npm test
Deployment
Consider containerizing the application with Docker or deploying it to a cloud service like AWS, GCP, or Azure for production environments.
Acknowledgments
Thanks to all open-source libraries and datasets utilized in this project.
Special thanks to medical professionals and data scientists whose insights shaped the development of the risk prediction models.
FAQ
How Can I Contribute?
Fork the repository.
Create a new branch (git checkout -b feature/YourFeature).
Commit your changes (git commit -m 'Add YourFeature').
Push to the branch (git push origin feature/YourFeature).
Open a Pull Request.
Where to Report Issues?
Please use the Issues section for bug reports or feature requests.
Is This Project Open for Research Use?
Yes, this project is licensed under the MIT License, allowing for reuse with proper attribution. Refer to LICENSE.md for more details.
Support
For support, contact us via email at [email protected] or join our dedicated Slack channel.
Project Status
The project is in active development, with ongoing efforts to enhance the prediction models and user interface. Check the Issues section for planned features and known issues.
Contributing
We welcome contributions! Please review our contributing guidelines before submitting pull requests.
Code of Conduct
We strive for a welcoming and inclusive community. Please review our Code of Conduct to ensure respectful interactions.
License
This project is licensed under the MIT License - see the LICENSE file for details.
Contact
Project Maintainer - @YourTwitterHandle - [email protected]
Project Link: https://github.com/your-username/heart-attack-risk-analysis
Acknowledgements
React Documentation
Flask Documentation
Axios on GitHub
Markdown Guide
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent