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

30 August 2024 (08:00 - 17:30)
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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

Access the full session

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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

30 August - 2 September 2024
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ESC 365 is supported by

novartis Explore sponsored resources