Evaluation of Cardiovascular Disease Prediction Using Decision making trial and Evaluation Laboratory Method

Predict a patient with heart disease Classify like Logistic Regression and KNN Different algorithms of machine learning We used How to improve the accuracy of this model Very useful for controlling what can be used approach was used predicting myocardial infarction in any given individual. The most important behavior for heart disease and stroke Risk factors include unhealthy diet, physical inactivity Temperament, tobacco use and alcohol harm result in Effects of behavioral risk factors are high Blood pressure, increased blood glucose, increased blood In fat and overweight and obesity manifested in persons. Alternative: Abnormal TG, Abnormal TC, Abnormal LDL, Abnormal HDL And extraordinary FPG. Evaluation Preference: Abnormal TG, Abnormal TC, Abnormal LDL, Abnormal HDL And extraordinary FPG. From the result it is seen that Abnormal HDL and is got the first rank whereas is the Abnormal TG got is having the lowest rank. The value of the dataset for Range of Cardiovascular Disease Prediction in DEMATEL Method shows that it results in Abnormal HDL and top ranking.