Data Mining Technique for Prediction System of Heart Disease Using Associative Classifications

In this study, several aspects of the human body have been focused upon. This paper attempts to cast light on pre-and post-pathological conditions, man-machine interactions, human mindset, and ethics of AI. The paper emphasizes the cultural impacts of overeating, profuse drinking, and smoking habits. It uplifts the basic necessity of growing awareness schemes. Patients are seeking treatment in health care centers with the following serious pathological conditions and complications (We exclude the COVID-19 pandemic because it has been adequately publicized by media and press): Heart Attack, Stroke Cancer, Fatty liver & liver cirrhosis. Because of being the leading causes of sudden death prediction of heart attack is very important. Our main focus is to determine the best machine learning method. With optimal parameters, we evaluate the Dataset. Model Accuracy for the heart Attack Machine Learning Model was the highest for the Logistic Regression mode land it was 93.41%. On the contrary, the accuracy for Linear Regression Model was 60.10% which was the least.