Background Machine learning based on clinical characteristics has the potential to predict coronary CT angiography (CCTA) findings and help guide resource utilisation.Methods From the SCOT-HEART ...

Background There is a lack of atrial fibrillation (AF) prediction models tailored for individuals without prior ...

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

Researchers may be able to predict cardiovascular disease -- such as arterial fibrillation and heart failure -- in patients by using artificial intelligence (AI) to examine the genes in their DNA ...

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.

A system that spun out of Stanford is using AI and machine learning to help doctors visualise patients' arteries and spare them invasive tests.

Machine learning, a branch of artificial intelligence, has become more accurate than human medical professionals in predicting incidence of heart attack or death in patients at risk of coronary ...