Acute cardiac care & resuscitation

Artificial intelligence versus human expertise: Electrocardiogram (ECG)-based detection of occlusive myocardial infarction after cardiac arrest

ResuscitationPublished Diagnostic accuracy study

Authors' conclusion

QoH, despite operating without awareness of the CA-setting and thus likely at a relative disadvantage, and HE showed robust diagnostic accuracy. Due to undifferentiated overdiagnosis, general LLMs remain unsuitable for ECG interpretation.

Study context

Population
Adults resuscitated from cardiac arrest, post-ROSC ECG
Participants
97 adults
Comparison
Queen of Hearts (QoH) vs human experts vs large language model (LLM)-based artificial intelligence (AI) chatbots for ECG detection of occlusive myocardial infarction (OMI) after cardiac arrest
Outcome
AUROC for presence and probability of OMI and acute coronary occlusion (ACO), determined by coronary angiography
Methodological detailssingle-centre
  • Single-centre

Performance

As reported in the abstract

AUROC
Test or modelAUROC acute coronary occlusion (ACO) (TIMI 0)AUROC OMI
QoH0.846 [0.752-0.939]0.745 [0.647-0.843]
Human experts (HE)0.735 [0.622-0.848]0.635 [0.515-0.755]
ChatGPT0.456 [0.319-0.592]0.495 [0.376-0.614]
EKG Analyst0.474 [0.346-0.603]0.626 [0.508-0.743]

AUROC acute coronary occlusion (ACO) (TIMI 0)

QoH0.846 [0.752-0.939]
Human experts (HE)0.735 [0.622-0.848]
ChatGPT0.456 [0.319-0.592]
EKG Analyst0.474 [0.346-0.603]

AUROC OMI

QoH0.745 [0.647-0.843]
Human experts (HE)0.635 [0.515-0.755]
ChatGPT0.495 [0.376-0.614]
EKG Analyst0.626 [0.508-0.743]

Further findings

Threshold-dependent performance (sensitivity/specificity)

Both AI chatbots: high sensitivity at the cost of minimal specificity (ACO / OMI sensitivity)
100 % / 98.36 %
QoH and HE: more even distributions of sensitivity/specificity

Original publication

Artificial intelligence versus human expertise: ECG-based detection of occlusive myocardial infarction after cardiac arrest. Resuscitation. Published 19 November 2025. doi:10.1016/j.resuscitation.2025.110905

Summarised from the published abstract; every number is checked against it

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