This makes heart disease a major concern to be dealt with. But it is difficult to identify heart disease because of several contributory risk factors, such as diabetes, high blood pressure, high cholesterol, an abnormal pulse rate, and many other factors. Due to such constraints, scientists have turned to modern approaches like Data Mining and Machine Learning to predict the disease. Machine learning (ML) proves to be effective in assisting in making decisions and predictions from the large quantity of data produced by the healthcare industry.

This makes heart disease a major concern to be dealt with. But it is difficult to identify heart disease because of several contributory risk factors, such as diabetes, high blood pressure, high cholesterol, an abnormal pulse rate, and many other factors. Due to such constraints, scientists have turned to modern approaches like Data Mining and Machine Learning to predict the disease. Machine learning (ML) proves to be effective in assisting in making decisions and predictions from the large quantity of data produced by the healthcare industry.

This makes heart disease a major concern to be dealt with. But it is difficult to identify heart disease because of several contributory risk factors, such as diabetes, high blood pressure, high cholesterol, an abnormal pulse rate, and many other factors. Due to such constraints, scientists have turned to modern approaches like Data Mining and Machine Learning to predict the disease. Machine learning (ML) proves to be effective in assisting in making decisions and predictions from the large quantity of data produced by the healthcare industry.