FIU Researchers are training AI to detect heart conditions, like aortic stenosis and heart failure, by analyzing heart sound data to improve early diagnosis and risk prediction.

The objective of this project is to build a Machine Learning model to predict whether a patient has heart disease or not, based on clinical features. This is a binary classification task using the ...

This review provides a thorough and organized overview of machine learning (ML) applications in predicting heart disease, covering technological advancements, challenges, and future prospects. As ...

This project focuses on predicting heart disease using the Heart Disease Dataset. It involves data preprocessing, exploratory data analysis (EDA), feature selection, and model training with multiple ...

Abstract The accurate and early detection of coronary heart disease (CHD) is crucial for reducing mortality rates. This study evaluates the predictive performance of three machine learning ...

Introduction: Cardiovascular disease (CVD) is the leading cause of death in patients with chronic kidney disease (CKD). This study aimed to develop CVD risk prediction models using machine learning to ...

A machine learning-based heart disease prediction model (ML-HDPM) that uses various combinations of information and numerous recognized categorization methods.