The Maternal Health Risk Predictor is a machine learning-based web application designed to assess and predict maternal health risks during pregnancy. This project aims to provide a valuable tool for healthcare professionals and expectant mothers to monitor and manage pregnancy-related health risks effectively.
- Predicts maternal health risk intensity based on various input parameters.
- User-friendly web interface for entering patient data.
Link to dataset used: [https://www.kaggle.com/datasets/drmbsharma/maternal-health-risk-data-set?rvi=1].
- Python
- Streamlit
- Machine Learning (Scikit-Learn)
- HTML/CSS for UI design
- Enter the patient's demographic and health data.
- Click the "Predict" button to receive a risk assessment.
- Explore additional information about the dataset.
Disclaimer: While the model's training accuracy is 95%, it may produce incorrect predictions during real-time use. Always consult with healthcare professionals for accurate assessments and advice.
Contributions and enhancements to this project are welcome! Feel free to fork the repository, make improvements, and submit pull requests.