For cardiac disease prediction, this paper examines feature selection approaches such
Particle Swarm Optimization (PSO) and the Chi-square test with XGBoost. We analyze their …

Heart disease is a prevalent and life-threatening medical condition that continues to pose a
significant global health challenge. Early and accurate prediction of heart disease can …

In today's world, heart disease is the leading cause of death globally. Researchers have
proposed various methods aimed at improving the accuracy and efficiency of the clinical …

Over the years, researchers have developed several expert systems to help cardiologists
improve the diagnostic process by predicting heart diseases early on. Most of the available …

In today's world, heart disease is the leading cause of death globally. Researchers have
proposed various methods aimed at improving the accuracy and efficiency of the clinical …

In addressing the critical challenge of early and accurate heart failure diagnosis, this study
explores the application of five machine learning models, including XGBoost, Decision Tree …

Heart disease is among the most prevalent medical conditions globally, and early diagnosis
is vital to reducing the number of deaths. Machine learning (ML) has been used to predict …

This study aims to develop an advanced heart disease prediction model using machine
learning techniques to address the global health challenge of early identification and …

With the development of information and technology, especially with the boom in big data,
healthcare support systems are becoming much better. However, an early diagnosis is not …

Cardiovascular diseases are one of the most common causes of death in the world. At this
point, early diagnosis of heart diseases is critically important. The aim of this study is to …