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K. Bekelaar

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Open access Feb 2026

Artificial intelligence shows comparable or improved performance to traditional risk models in predicting atrial fibrillation after cryptogenic stroke

In patients with cryptogenic stroke receiving an ICM, the ECG-AI score showed modest discrimination for AF detection, outperforming CHA2DS2-VA and HAVOC, but not Brown ESUS-AF, which indicates a possible role for AI-driven ECG analysis in risk stratification.

F. Wouters, M. Barthels, J. Vranken et al. · 0 citations