Heart Disease Prediction using Machine Learning

Abstract

The correct prediction of cardiovascular disease can prevent life threats, and incorrect prediction can prove to be fatal at the same time. Heart disease, also known as cardiovascular disease is one of the complex diseases and globally many people suffered from this disease. It is one of the major causes of mortality worldwide, can be mitigated by early heart disease diagnosis. However, the mortality rate can be drastically controlled if the disease is detected at early stage and preventive measures are adopted as soon as possible. In the modern world, there are some revolutionary advancements within the field of medical science and research and this can be no totally different for ECG. Electrocardiogram (ECG) gives useful information about morphological and functional details of heart which is used to predict various cardiac diseases. In this article, we proposed an efficient and accurate system to diagnosis heart disease which is based on machine learning techniques. Raw ECG signal contains useful features which can be used to detect different heart diseases. The various ECG parameters like heart rate, age, sex, cholesterol level, blood pressure, ST interval of ECG signal are used for analysis. Several machine learning (ML) algorithms have been used for cardiovascular disease prediction. Machine Learning is employed across several ranges around the world. The healthcare business isn't any exclusion.