Effective Prediction Of Cardiovascular Diseases Using Machine Learning


The field of bio sciences has advanced to a larger extent and has generated large amounts of information from Electronic Health Records. This has given rise to the acute need for knowledge generated from this enormous amount of data. Data mining methods and machine learning play a major role in this aspect of bio sciences. Heart is a condition in which the heart are damaged and cannot filter blood as they always do. Early detection of heart disease can improve the quality of life to a greater extent. This calls for a good prediction algorithm to predict heart disease at an earlier stage. Literature shows a wide range of machine learning algorithms employed for the prediction of heart disease. We use data pre processing, data transformation, and various classifiers to predict heart disease and propose the best Prediction framework for heart disease. The results of the framework show promising results of better prediction at an early stage of heart disease. The heart disease prediction and also the covid detection are also developed in the interface the input should be given according to the requirement. The correct prediction of heart disease can prevent life threats, and incorrect prediction can prove to be fatal at the same time

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