Back

Predicting PVI Non-Responders using machine learning on left-atrial electroanatomic mapping data

13 April 2026 (11:30 - 12:15)
Organised by: Logo
Congress Presentation Part of: Atrial fibrillation postablation follow-up Epidemiology, Prognosis, Outcome EHRA Premium Access EHRA 2026 European Heart Rhythm Association (EHRA)

About the speaker

Photo
Doctor Yazan Mohsen

Johns Hopkins, Baltimore (United States of America)

6 More presentations in this session

Presentation thumbnail
Prediction of sinus rhythm maintenance using clinical parameters following atrial fibrillation ablation with pulsed-field and radiofrequency energy
Mr S. Hassouna (Prague, CZ)
Abstract Slides Video
Presentation thumbnail
Unsupervised machine learning stratifies AF patients into phenotypes linked to post-PVI recurrence
Doctor Y. Mohsen (Baltimore, US)
Abstract Slides Video
Presentation thumbnail
Determinants of AF burden reduction as indicator of successful catheter ablation of atrial fibrillation: data of the ISOLATION study
Miss Z. Habibi (Maastricht, NL)
Abstract Slides Video
Presentation thumbnail
Optimal blanking period following atrial fibrillation catheter ablation: a systematic review and diagnostic meta-analysis of over 28,000 patients
Doctor A. Askarinejad (Liverpool, GB)
Abstract Slides Video
Presentation thumbnail
Is repeat ablation for atrial fibrillation using pulsed field energy as effective as the initial procedure? Objective evaluation using continuous monitoring
Doctor D. Musat (Paramus, US)
Abstract Slides Video

Access the full session

Session thumbnail
Atrial fibrillation postablation follow-up

The Event

Event poster

EHRA 2026

13 April 2026 11:30 CET
You may be interested in
thumbnail
Congress Presentation
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
thumbnail
Congress Presentation
Unsupervised machine learning of multimodal data to identify atrial fibrillation subgroups likely to benefit from pulmonary vein isolation
thumbnail
Congress Presentation
Predicting atrial fibrillation recurrence after catheter ablation using an artificial intelligence-enabled electrocardiogram algorithm

ESC 365 is supported by

novartis Explore sponsored resources

ESC 365 is supported by

novartis Explore sponsored resources