Detection of Cardiovascular Diseases with CNN-LSTM Based Model Using Different Evaluation Parameters

Abstract

– Heart diseases are one of the most common diseases in the world. Many deaths can be prevented with early detection of heart disease. In addition, patient care costs decrease with early diagnosis. There is a shortage of specialists in many places and the diagnosis of heart disease cannot be made early. In order to make early diagnosis of heart diseases, computer-aided systems should be developed and used for automatic diagnosis. In this study, a CNN-LSTM based model was developed to detect heart diseases. In order to compare the performances of the developed model, seven various machine learning classifiers that have been utilized in the literature were used. When the results obtained in the proposed CNN-LSTM based model and different classifiers are compared, it is seen that higher success rates are obtained in the proposed CNN-LSTM based model.