… artificial neural network (ANN) was used. The findings demonstrated that the most accurate
prediction results for cardiovascular illness … , is similar to the k-means algorithm but utilizes …

… method and k-means clustering. The model was validated … [10] proposed a hybrid method
to complete the feature selection by … neural network based data mining in prediction of heart …

… (2016) predicted the pattern of heart disease by applying machine learning to predict heart
disease problems … K-NN classi er performs better than K-means clustering in missing value …

… algorithms with the Artificial Neural Network (ANN) . The … The proposed new technique based
on enhanced K-Means and … This new hybrid method gives 93% accuracy. The advantage …

… heart disease in this study as this method used the tool to minimize Hadoop Map. To conduct
clustering, a customized K-Means … Diagnosis of valvular heart disease through neural net…

… strategy, and K-Means bundling computation decision of the … method for investigating heart
disease using machine learning algorithms. These findings indicate that the better prediction …

… a fuzzy neural network (FNN) and an artificial neural network … a filter to construct a hybrid
method for feature selection. … Smart heart disease prediction system using Improved K-means …

… on using a modular neural network to diagnose heart disease. … There is another way to
predict heart disease using … The researchers used K-means clustering techniques and …

… 86% of accuracy using the hybrid method of SVM and Naïve … neural network approach is
used to predict the heart disease in [9]… , K-means clustering and Random Forest are applied and …