AI outsmarts manual efforts

A research presented at ESC Acute Cardio Vascular Care 2026, the annual Congress of the Association for Accute Cardio Vascular Care (ACVC), a branch of the European Society of Cardiology (ESC) revealed that Artificial Intelligence (AI) based method for interpreting ECGs performed better than standard approaches in detecting occlusive myocardial infarction (MI)

ST elevation myocardial infarction (STEMI), a kind of heart attack caused by occlusion in a coronary artery to those patients who are down with suspected acute coronary syndrome (ACS), a specific change on an ECG which are also called ST elevation. It requires immediate percutaneous coronary intervention to restore the blood flow in the heart.

Those patients who doesn’t have an ST elevation cause of chest pain can be less certain and they need to go for further tests to confirm if the MI is caused by occlusion.

The research included 1490 patients with an average age of 63 and out of them 42% were females. In that research, 1382 patients are diagnosed with no occlusive MI and only 108 patients, with a meagre 7% are detected by that.

The AI method correctly identified obstructive MI in 84% of the cases. Sensitivity was 77%, specificity was 99%, with negative predictive value being 98%. With false negatives and positive being 2&1 percent respectively.