The heart is a significant organ of the human body. Life is reliant on the proper functioning of the heart. Most of the time is difficult to analyze a patient as a heart patient. For this purpose, data mining can be used to recognize a hidden clinical dataset. In this paper, we study to find ways to optimize the K-Means algorithm by overcoming its drawbacks which may help create a heart disease predicting system by applying it. Here, we present a study on the advanced data mining techniques and hybrid algorithms that could be used to optimize the K-Means and increase the prediction accuracy of the system of Heart disease prediction.
