Published Paper Details:

In medicine, predicting and accurately diagnosing heart disease is a huge problem, and cardiovascular disease predetermine in health services is considered an important problem. In these growing health-care organizations, more expensive surgeries are offered to patients. Recently, heart disease has become a common disease, that is, even though medicine is growing on one side, cardiovascular disease are growing exponentially on other side. The main cause of these diseases is poor lifestyle, alcohol consumption, lack of physical activity and tobacco consumption. Thus, there is a need for a cloud-based framework (CBF) for monitoring health information and predicting it efficiently. Recently, machine learning methods have been used to solve these types of problems. But in this proposed system, to improve the process of predicting patients' health information and cloud-based four steps are also used to improve monitoring. So here are two types of methods used in machine learning to detect and classify heart disease. Then the accuracy of those methods is examined. Evaluation criteria are used to examine their effectiveness.