Intelligent application for Heart disease detection using Hybrid Optimization algorithm

Prediction of heart disease is very important because it is one of the causes of death around the world. More- over, heart disease prediction in the early stage plays a main role in the treatment and recovery disease and reduces costs of diagnosis disease and side eects it. Ma- chine learning algorithms are able to identify an eective pattern for diagnosis and treatment of the disease and identify eective factors in the disease. this paper is in- vestigated a new hybrid algorithm of Whale Optimiza- tion and Dragon y algorithm using a machine learning algorithm. the hybrid algorithm employs a Support Vec- tor Machine algorithm for eective Prediction of heart disease. Proposed method is evaluated by Cleveland standard heart disease dataset. The experimental re- sult indicates that the SVM accuracy of 88.89 % and nine features are selected in this respect.