Now days, cases of heart disease are increasing very rapidly. It is very important to predict any such diseases in early stage. This is a quite difficult task. It should be perform efficiently and correctly. The research paper point on the patients, which are more likely to having a heart disease by using various medical attributes. We have designed a heart disease prediction system model using machine learning which predict patient likely to have heart disease or not with the use of its past medical history. We used the random forest machine-learning algorithm to predict patient with heart disease. The accuracy of proposed model was high and able to predict of having a heart disease or not using random forest classifier, which showed good accuracy. The given heart disease prediction system is easy to use and reduce the cost of diagnosis. KEYWORDS: Heart disease prediction, Machine Learning, Random Forest, Decision Tree.
• Hardware: Processor: i3 ,i5 RAM: 4GB Hard disk: 16 GB • Software: operating System : Windws2000/XP/7/8/10 Anaconda,jupyter,spyder,flask Frontend :-python Backend:- MYSQL
₹10000 (INR)
NON IEEE -2021