AI Model Reliably Diagnosed Coronary Microvascular Dysfunction

A recent study found that an AI model could “diagnose an elusive form of heart disease within seconds.”

The model was able to detect coronary microvascular dysfunction, which is a “complex condition that requires advanced imaging techniques to diagnose, using a common electrocardiogram.” The model studied here “significantly outperformed AI models in nearly every diagnostic task, including predicting myocardial flow reserve, the gold standard for diagnosing CMVD.”

CMVD affects smaller heart vessels than coronary artery disease. It causes chest pain and increases the risk of heart attack, but it is difficult to diagnose and requires advanced methods, like PET myocardial perfusion imaging, to detect. This AI model utilizes “self-supervised learning” and was trained on “more than 800,000 unlabeled EKG waveforms” and fine-tuned on a “smaller, labeled dataset of PET scans.”

The model was able to predict CMVD across different databases and it “consistently improved diagnostic accuracy of prediction tasks for more common cardiac conditions compared to previous state-of-the-art models.” This holds potential for extending an “EKG’s ability to predict a tougher-to-spot microvascular condition like CMVD.”