Prediction of Heart Disease Using Genetic Algorithm

Abstract

Medical practitioners depend on medical diagnosis systems for detection, diagnosis, and treatment of various diseases in recent years. Genetic algorithms play a vital role as an essential optimization approach for problems involving classification in machine learning. Genetic algorithms can also achieve a high level of prediction and accuracy. Coronary heart disorder is a major heart disorder that narrows the blood vessels that supply oxygen to the heart. In this paper, we analyze and predict heart diseases among patients using genetic algorithms. The heart disease data set from the UCI machine learning repository data set is used. The proposed method utilizes the data set on heart disease available at the UCI machine learning repository and provides better classification accuracy and prediction among the patients with various heart disorders. Implementation is carried out using Python language.