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Updated: Jun 10, 2026
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Estimate the Cognitive Load Using Electrocardiographic Measure: A Human-AI Collaborative Task
Published on: December 5, 2025
Pilot Study Comparing Emergency Physician and Artificial Intelligence-supported Interpretations of Electrocardiograms
1Maltepe University Faculty of Medicine, Department of Emergency Medicine, Istanbul, Türkiye.
The Western Journal of Emergency Medicine
|June 8, 2026
Summary
Artificial intelligence (AI) showed 90% agreement with an emergency physician for common electrocardiogram (ECG) interpretations. However, AI's recommendations for complex cases require further investigation before independent use.
Area of Science:
- Medical Diagnostics
- Artificial Intelligence in Medicine
- Cardiology
Background:
- AI tools are increasingly explored for medical applications.
- Effectiveness of AI in emergency electrocardiogram (ECG) interpretation is under-investigated.
- This pilot study evaluates AI diagnostic performance against an experienced emergency physician.
Purpose of the Study:
- To evaluate the diagnostic performance of AI interpretation of ECGs.
- To compare AI results with those of an experienced emergency physician.
- To assess AI's concordance in common critical ECG conditions.
Main Methods:
- Sourced 20 critical condition ECG cases from academic repositories.
- Used ChatGPT-4 and an experienced emergency physician as interpreters.
- Analyzed ECGs across rhythm, heart rate, axis, ST/T changes, diagnosis, and management recommendations.
Main Results:
- 90% agreement (18/20 cases) between AI and physician interpretation (Cohen kappa = 0.80).
- 100% concordance for myocardial infarction, arrhythmias, conduction disorders, and hyperkalemia.
- Zero concordance for fusion beats and torsades de pointes, with critical management recommendation discrepancies.
Conclusions:
- AI demonstrated moderate diagnostic concordance for common ECG findings.
- Discrepancies in complex cases and management recommendations necessitate larger studies.
- AI should be an adjunct tool, enhancing but not replacing human clinical judgment for definitive ECG interpretation.
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