Back

Predicting incident atrial fibrillation from sinus rhythm electrocardiograms using deep learning: a meta-analysis with horizon stratification

31 August 2026 (08:15 - 09:00)
Organised by: Logo
Congress Presentation Part of: Electrocardiographic signatures of conduction disease and arrhythmia: from mechanisms to clinical outcomes Electrocardiography (ECG) ESC2026 Premium Access ESC Congress 2026 European Society of Cardiology

About the speaker

Photo
Doctor Ibrahim Antoun

University of Leicester, Leicester (United Kingdom of Great Britain & Northern Ireland)

5 More presentations in this session

Presentation thumbnail
Electrocardiographic analysis of LV septum and lateral wall activation indicates LV systolic dysfunction and symptoms beyond apical rocking in left bundle branch block patients
Doctor L. Oprean (Bucharest, RO)
Abstract
Presentation thumbnail
Systematic analysis of outcomes and pathways related to idiopathic left bundle branch block
Professor R. Zhang (Dalian, CN)
Abstract
Presentation thumbnail
Prognostic significance of right and left bundle branch block in the general population: findings from a city health study
Doctor J. Senftinger (Davos Wolfgang, CH)
Abstract
Presentation thumbnail
Frequency and outcomes of arrhythmias and conduction system abnormalities using real-world handheld single-lead ECGs: A VITAL-AF trial analysis
Doctor E. Patt (Boston, US)
Abstract
Presentation thumbnail
Arrhythmias as the dominant phenotype of early cardiovascular events after liver transplantation
Doctor C. Huerta (Dallas, US)
Abstract

Access the full session

Session thumbnail
Electrocardiographic signatures of conduction disease and arrhythmia: from mechanisms to clinical outcomes

The Event

Event poster

ESC Congress 2026

31 August 2026 08:15 CET
You may be interested in
thumbnail
Congress Presentation
Artificial intelligence models using sinus rhythm electrocardiography for proactive atrial fibrillation screening: a comprehensive systematic review
4 April 2025
thumbnail
Congress Presentation
P-wave duration and interatrial block as predictors of new-onset atrial fibrillation: A systematic review and meta-analysis
16 April 2023
thumbnail
Congress Presentation
A systematic review of risk prediction models for incident heart failure in the community
22 May 2023
thumbnail
Congress Presentation
Explainable electrocardiogram-based deep learning predicts ventricular arrhythmias after cardiac resynchronisation therapy.
28 August 2026

ESC 365 is supported by

novartis Explore sponsored resources
novo-nordisk Explore sponsored resources

ESC 365 is supported by

novartis Explore sponsored resources
novo-nordisk Explore sponsored resources