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Deep learning-based detection of paroxysmal atrial fibrillation from sinus rhythm electrocardiograms and its association with stroke risk

28 August 2026 (12:15 - 13:00)
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Congress Presentation Part of: Atrial fibrillation: phenotyping and risk prediction Stroke in Atrial Fibrillation ESC2026 Premium Access ESC Congress 2026 European Society of Cardiology

About the speaker

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Mr Yeongyeon Na

Seoul (Korea (Republic of))

6 More presentations in this session

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Dynamic changes in liver fibrosis and the risk of death and bleeding in non-cirrhotic patients with atrial fibrillation treated with NOACs.
Doctor T. Bucci (Perugia, IT)
Abstract Slides Video
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Untargeted-metabolomics identifies key metabolites for atrial fibrosis and recurrence of atrial fibrillation indication across populations
Doctor M. Chu (Nanjing, CN)
Abstract Slides Video
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Identification of new atrial fibrillation phenotypes from insertable cardiac monitor recordings using unsupervised machine learning
Doctor E. Flo Lenz (Trondheim, NO)
Abstract Slides Video
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The prognostic value of sinus rhythm restoration in patients hospitalized for atrial fibrillation
Doctor A. Samaras (Thessaloniki, GR)
Abstract Slides Video
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Head-to-head comparison of CHADS₂, CHA₂DS₂-VASc, CHA₂DS₂-VA, HAS-BLED, and HELT-E₂S₂ scores in edoxaban treated atrial fibrillation patients: a 2-year analysis from the ETNA-AF Global program
Doctor C. Wang (Taipei, TW)
Abstract Slides Video

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Atrial fibrillation: phenotyping and risk prediction

The Event

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ESC Congress 2026

28 August 2026 12:15 CET
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ESC 365 is supported by

novartis Explore sponsored resources
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