Abstract
This Heart disease means any condition that affects to directly heart. Globally, Heart disease is the main reason for death. According to a survey, approximately 17.9 million people died from heart disease in 2019 (representing 32 percent of global deaths). The number of people dying is increasing at an alarming rate every day. So it is necessary to detect and prevent heart disease as soon as possible. Medical experts who work inside the field of coronary heart sickness can predict the rate of coronary heart disorder up to 69%, which is not so useful. Because of the invention of various machine learning techniques, intelligent machines can predict the chance of heart disease up to 84%, which will be helpful to prevent heart disease earlier. In this paper, for picking essential characteristics among all features in the dataset, the univariate feature selection approach was employed. One-of-a-kind machine learning algorithms like K-Nearest Neighbors, Naive Bayes, Decision Tree, Random Forest, Support Vector Machine were used to assess the performance of these algorithms and forecast which one performs best. These machine learning approaches require less time to predict disease with more precision, resulting in the loss of valued lives all around the world.
Highlights
As it is known that the human heart is one of the most essential organs in the human body [12]
A record of 500 patients was used to make a prediction. After applying both the algorithms, Naive Bayes provided an accuracy of 74%, and Support Vector Machines (SVM) provided an accuracy of 94.60%
We’ve used KNN, Naive Bayes, Decision Tree, Random Forest, and SVM set of rules primarily based on their accuracy
Summary
Health is considered as a whole state of physical, mental, and social well-being where there’s an absence of disease and infirmity. If the heart is affected by several diseases, it’ll be harmful to the human body, and sometimes it’ll cause death . Medical professionals can’t get an accurate result of heart disease prediction by following a custom. With the help of machine learning strategies, it’s far feasible to collect information from a massive quantity of information and by training the dataset, the machine can predict the result. It reduces the extra burden on medical professionals. As in the modern world, it can’t be imagined daily lives without technology, machine learning has made life easier by predicting and providing proper guidelines about disease. By using machine learning techniques, millions of lives can be saved by predicting disease quickly and providing quicker service to the patients
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