ArticleEuropean heart journal. Digital health2025
Artificial intelligence-estimated electrocardiographic sex as a recurrence predictor after atrial fibrillation catheter ablation.
Article in European heart journal. Digital health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Prediction of Atrial Fibrillation Risk Through the Integration of Genetic Information and Artificial Intelligence-Based Electrocardiogram Data.Journal of arrhythmia · 2026Article
- Artificial intelligence-enabled electrocardiographic 'sex discrepancy' as a predictor of atrial fibrillation recurrence: contextualising the findings of parkEuropean heart journal. Digital health · 2026Article
- Hormonal Atrial Fibrillation: Pathophysiological Mechanisms That Trigger and Sustain the Arrhythmic Circuits.Biomedicines · 2025Review
- Dynamic changes of artificial intelligence estimated electrocardiographic age and sex predicts recurrence after atrial fibrillation catheter ablation.Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2025Article
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Authors and funding
13 authors.
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Abstract
Aims: We explored whether artificial intelligence (AI)-enabled electrocardiographic (ECG) sex discrepancy would predict atrial fibrillation (AF) recurrence after catheter ablation for paroxysmal AF. Methods and results: The AI-ECG sex prediction model was developed from the MIMIC-IV and externally validated on CODE-15% (AUC 0.89) and UK Biobank (AUC 0.92) cohorts. After validation, we estimated AI-ECG sex from pre-procedural sinus rhythm ECGs among paroxysmal AF patients scheduled for catheter ablation using data from a pooled AF ablation cohort ( Conclusion: Pre-procedural ECG sex discrepancy has a prognostic value for AF recurrence after catheter ablation for paroxysmal AF in women.
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