
Heart Attack Survival Prediction
Heart disease and heart attacks kill millions of people every year in the US and worldwide. Many cases are preventable if monitored appropriately, this is crucial to save lives. This project predicts hospital patient survival after a heart attack using machine learning algorithms like random forest. The application of advanced analytics and causal inference can determine factors critical to heart attacks and heart disease.