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AI ECGs Beat Doctors in Heart Attack Detection
21 Mar
Summary
- AI interpretation of ECGs showed superior accuracy in detecting occlusive myocardial infarction.
- Human ECG interpretation correctly identified occlusive MI in only 42% of cases.
- The AI method correctly identified obstructive MI in 84% of cases, outperforming humans.
An artificial intelligence (AI) based method for interpreting electrocardiograms (ECGs) has shown greater effectiveness in detecting occlusive myocardial infarction (MI) than conventional approaches. The study, presented at ESC Acute CardioVascular Care 2026, focused on patients exhibiting symptoms of acute coronary syndrome but lacking ST elevation on their initial ECG.
This AI-ECG algorithm correctly identified obstructive MI in 84% of cases. It achieved a sensitivity of 77%, specificity of 99%, and a negative predictive value of 98%. Human interpretation of the same ECGs, however, only correctly identified occlusive MI in 42% of instances. These findings suggest AI interpretation is a valuable tool for improving early detection and management of occlusive MI in patients without ST elevation.
