A Novel Study of Predicting Coronary Artery Disease with Data Mining and Machine Learning Algorithms

The prevalence of health problems is rising. Coronary Artery disorders, in particular, are commonplace now. Today, Coronary Artery Disease is the leading cause of death worldwide, especially in poorer nations. Reducing mortality from Coronary Artery infections requires both early detection and ongoing clinical care. However, due to the increased effort and expertise required, thorough and uniform patient checks are just not feasible. The healthcare fields store an enormous amount of data. However, most of it is wasted since it isn't being used effectively. Data storage has the potential to yield positive insights into the realm of future health prediction. The use of data sets and efficient tools to extract information for the scientific investigation of disease or other purposes is still in its infancy. Various information extraction and machine learning methods may be used to sift through the various patient heart variables and extract relevant data. The purpose of this article is to incorporate the latest research on relative outcomes of coronary illness anticipation and to build scientific goals by employing mining of data and classification approaches based on machine learning.