Integration of Fuzzy C-Means and Artificial Neural Network with Principle Component Analysis for Heart Disease Prediction
Romana Rahman Ema, Pintu Chandra Shill · 2020
Heart disease is a deadly phenomenon for any human being in the world. If it can be predicted, then it can be prevented by taking precautions. In this paper, we have proposed a new hybrid model based on Fuzzy C-means and Artificial Neural Networks (ANNs) with Principle Component Analysis that is capable to predict heart disease. The Principal Component Analysis is used to select the important features from the dataset. Then Fuzzy C-Means Clustering is used to cluster the extracted data from PCA and finally, Artificial Neural Network is used to predict Cardiovascular Disease. The simulation results confirm the effectiveness of the proposed method not only in terms of accuracy but also in terms of generalizability of the obtained models.