Enhancing The Diagnosis Of Functionally Relevant Coronary Artery Disease With Machine Learning

This article discusses the use of machine learning models in predicting and diagnosing coronary heart disease in patients undergoing stress testing. The models were trained and evaluated on a diverse patient population and compared to the clinical assessment of cardiologists. The results showed that the models were able to accurately predict and diagnose heart disease, even in patients who were typically excluded from stress testing.