A Review of Machine Learning Algorithms for Predicting Heart Disease | IEEE Conference Publication | IEEE Xplore

A Review of Machine Learning Algorithms for Predicting Heart Disease


Abstract:

One of the most common causes for death in modern society is heart disease. Clinical data analysis has significant challenges in predicting heart disease. It has been sho...Show More

Abstract:

One of the most common causes for death in modern society is heart disease. Clinical data analysis has significant challenges in predicting heart disease. It has been shown that predictions and judgments may be made from the massive amounts of data generated by the healthcare industry by using machine learning (ML). Algorithms based on machine learning have demonstrated remarkable efficacy in generating highly accurate findings, therefore delaying the beginning of heart disease in several people and mitigating its effects in those who are already afflicted. It has aided physicians and medical researchers world- wide in identifying patient patterns that have led to the early diagnosis of cardiac conditions. We have seen the use of ML approaches in a number of sectors in recent IoT advancements. Few studies have examined the use of ML to forecast cardiac illness. In this paper, we provide an innovative approach to enhancing the accuracy of heart disease prediction by utilizing machine learning approaches to identify critical features. For establishing the prediction model, several feature combinations and popular classification techniques are employed.
Date of Conference: 15-16 March 2024
Date Added to IEEE Xplore: 11 April 2024
ISBN Information:
Conference Location: Greater Noida, India

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