CNN-CardioAssistant: Deep Convolutional Neural Network and Recursive Feature Elimination Method for Heart Disease Detection

Abstract

In recent times, we have seen an exponential rise in different chronic diseases due to our unhealthy lifestyles. Cardio disease is the most common and life-threatening among all diseases, which contributes to a very high mortality rate. Accurate detection of cardio disease at an early stage is vital to save the lives of people. Most of the existing cardiovascular disease detection systems suffer from lower performance and efficiency due to redundant attributes, dimensionality curse, imbalance, and noisy datasets. In this work, we proposed a novel convolutional neural networks-based system (CNN-cardioAssistant) that predicts cardiovascular disease in patients. Recursive feature selection (RFE) is employed to select more prominent features from the clinical data of cardio patients. The selected features are then used to train the proposed CNN-CardioAssistant as well as 11 different classifiers i.e., support vector machine (SVM), Random Forest, Decision Tree, logistic regression, Naïve Bayes, K-Nearest Neighbor, XGboost, Multi-layer Perceptron, Gaussian process classifier, Adaboost, and Quadratic discriminant analysis separately for cardio disease prediction. We compared the results of all the methods on three subsets of features i.e., 6,8, and 15 for each dataset. The features selection method provides optimal subsets of features that can reliably be used to predict cardiovascular disease with the highest accuracy. Experimental results on three different cardio datasets i.e., Public Health, Framingham, and Z-Alizadeh sani clearly demonstrate that the proposed CNN-CardioAssistant system has superior performance against the existing state-of-the-art methods.

A Review: Machine Learning and Data Mining Approaches for Cardiovascular Disease Diagnosis and Prediction

“…These are referred to as CVDs, and they are among the deadliest illness in the world. CVDs include heart disorders, vascular diseases of the brain, and blood vessel diseases [4,5].…”