Cardiovascular diseases, including heart attacks, are a significant global health concern. Early prediction of heart attacks can greatly improve patient outcomes. In this research project, we leverage the power of machine learning, specifically the Gaussian Naive Bayes algorithm, to build a predictive model for heart attack analysis.
The dataset used for this project is the Heart Attack Analysis & Prediction Dataset available on Kaggle. It includes a comprehensive set of health indicators and attributes that are crucial for heart attack prediction.
- If you're interested in diving into the details of our research, you can access the full research paper and explore our work in-depth, please follow this link
- For a comprehensive overview of all our work and to explore our projects in practical aspects, you can access our Google Colab notebook that demonstrates our methodology and analysis.
Special thanks to our team members who contributed to this project:
