Back

Machine learning based prediction models for outcomes following pulsed field ablation in atrial fibrillation

12 April 2026 (08:00 - 18:30)
Organised by: Logo
Congress Presentation Part of: Poster session (1): supraventricular arrhythmias Artificial Intelligence EHRA Premium Access EHRA 2026 European Heart Rhythm Association (EHRA)

About the speaker

Photo
Doctor Andrea Saglietto

University of Turin, Turin (Italy)

196 More presentations in this session

Presentation thumbnail
Electrocardiographic differentiation of narrow QRS complex tachycardia: validation of the new aVL and aVR criteria and a unifying approach to ECG analysis
Doctor J. Stec (Cracow, PL)
Abstract Slides Video
Presentation thumbnail
Characterization of paroxysmal atrial fibrillation in atrial septal defects: contribution of a left atrial substrate
Doctor N. Ramdat Misier (Rotterdam, NL)
Abstract Slides
Presentation thumbnail
Spatial distribution of effective refractory period in atrial fibrillation patients
Associate Professor A. Loewe (Karlsruhe, DE)
Abstract Slides
Presentation thumbnail
Early onset atrial fibrillation as a marker of inherited cardiomyopathy: lessons from combined imaging and genetic assessment
Doctor V. Rella (Milan, IT)
Abstract Slides Video
Presentation thumbnail
BMI discrepancy and new-onset atrial fibrillation: findings from UK biobank
Doctor J. Choi (Seoul, KR)
Abstract Slides Video

Access the full session

Session thumbnail
Poster session (1): supraventricular arrhythmias

The Event

Event poster

EHRA 2026

12 April 2026 08:00 CET
You may be interested in
thumbnail
Congress Presentation
Machine learning for outcome prediction of atrial fibrillation recurrence after catheter ablation
thumbnail
Congress Presentation
Prediction of long-term arrhythmic recurrence and major adverse cardiovascular events using machine learning in patients undergoing catheter ablation for atrial fibrillation: historical cohort study
thumbnail
Congress Presentation
Predicting PVI Non-Responders using machine learning on left-atrial electroanatomic mapping data

ESC 365 is supported by

novartis Explore sponsored resources

ESC 365 is supported by

novartis Explore sponsored resources