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

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.

“Our study supports the use of artificial intelligence methods for integrating multimodality imaging and clinical data for robust prediction of heart attacks,” he explains. “Our current efforts focus ...

Moreover, the machine learning approach can predict cardiac aging with high accuracy.” The fruit fly model has already been tremendously powerful for understanding the pathophysiological bases for ...

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 researchers leveraged machine-learning-based approaches to develop a prediction tool called the BAN-ADHF score, which showed promising results in accurately predicting diuretic response.

For example, by preventing hospitalizations in cases of just two widespread chronic illnesses — heart disease and diabetes — the United States could save billions of dollars a year.