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Prediction of atrial fibrillation recurrence after ablation: the impact of machine learning and recurrence during the blanking period

1 September 2024 (17:00 - 17:50)
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Congress Presentation Part of: Predicting outcomes after catheter ablation for atrial fibrillation: ablation technique, biomarkers, and machine learning Rhythm Control, Catheter Ablation ESC Professional Premium Access ESC Congress 2024 European Society of Cardiology

About the speaker

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Doctor Joao Almeida

Faculty of Medicine University of Porto, Porto (Portugal)

8 More presentations in this session

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Long-term prognosis in patients undergoing atrial fibrillation ablation
Doctor M. Kiliszek (Warsaw, PL)
Abstract Slides Video
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Biomarkers in early and late period after radiofrequency and pulsed field catheter ablation of atrial fibrillation
Miss B. Stekla (Prague, CZ)
Abstract Slides Video
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Ppulsed field ablation and ultra-high-density mapping for PVI: use of machine learning and data augmentation to guide procedure and identify recurrent tachycardia mechanisms at one-year follow-up
Doctor S. Feickert (Berlin, DE)
Abstract Slides Video
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An in-silico comparison of anatomical and substrate based AF ablation using electro and optical flow mapping
Mr O. Jaffery (London, GB)
Abstract Slides Video
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Secretoneurin plasma levels are decreased after catheter ablation for atrial fibrillation, patients with AF produce lower SN levels than healthy individuals
Associate Professor J. Plasek (Ostrava, CZ)
Abstract Slides Video

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Predicting outcomes after catheter ablation for atrial fibrillation: ablation technique, biomarkers, and machine learning

The Event

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ESC Congress 2024

1 September 2024 17:00 CET
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ESC 365 is supported by

novartis Explore sponsored resources