Abstract: Heart disease is one of the most critical human diseases in the world and affects human life very badly. In heart disease, the heart is unable to push the required amount of blood to other parts of the body. The diagnosis of heart disease through traditional medical history has been considered as not reliable in many aspects. Accurate and on time diagnosis of heart disease is important for heart failure prevention and treatment. So, there is a need of reliable, accurate and feasible system to diagnose such diseases in time for proper treatment. Correct diagnosis and treatment at an early stage can save people from heart disease and its consequences. Machine learning is one of the fast-growing aspects in current world. Machine learning is helpful in detection and diagnosis of various heart disease. The heart disease consists of set of range of disorders affecting the heart. It includes blood vessels problem such as irregular heart beat issues, weak heart muscles, cardio vascular disease and coronary artery disease. It reduces the blood flow through the heart leading to the heart attack. For this kind of work large and authenticated observations related to patient’s health are required. This project proposes a prediction model to predict whether patient have a heart disease or not by using entered symptoms and to give an awareness on heart disease and some useful tips on heart disease. The proposed work predicts the chances of heart disease and classifies patient’s risk level by implementing K-Nearest Neighbour machine learning algorithm. These machine learning algorithms predicts the chances of heart failure with high accuracy.

Keywords: Heart Disease, Machine Learning, K-Nearest Neighbour

PDF | DOI: 10.17148/IJARCCE.2022.11384

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