Addressing Death from Heart Failure Using RACER Algorithm

Cardiovascular diseases kill about 17 million people all over the world each year. Using medical data, predicting the possibility of death from cardiovascular diseases and heart failure can be challenging and using machine learning techniques are very useful. By analyzing medical records of 299 patients and using RACER algorithm as the base of our model, we provide a model to predict the death event. The accuracy of the proposed model was far more accurate than other previous applied models. The results lead us to believe that RACER can provide better performance for cardiovascular diseases and heart failure.