Heart Disease Prediction Model using Genetic Algorithm and Support Vector Machine

Heart disease has been one of the leading causes of mortality for individuals all around the world in recent years. The prognosis of heart disease would be difficult due to various risk factors such as diabetes, high blood pressure, improper pulse rate, and high cholesterol. Accurate and prompt identification of heart disease is necessary to prevent and treat heart failure. Machine learning techniques highly assist in the development of prediction models for heart disease and its early identification. Feature selection strategies are also used to identify features that are critical to achieve higher accuracy. The proposed model employs the Genetic algorithm to select suitable characteristics, and it also demonstrated that it outperforms the existing models that employ traditional feature selection methods.