Back

Advancing atrial fibrillation care: deep learning on ECG for comorbidity detection

29 August 2025 (07:00 - 18:00)
Organised by: Logo
Congress Presentation Part of: Precision cardiology: the role of signal processing and artificial intelligence Electrocardiogram (ECG) and Arrhythmia Analysis ESC Professional Premium Access ESC Congress 2025 European Society of Cardiology

About the speaker

Photo
Doctor Yazan Mohsen

Johns Hopkins, Baltimore (United States of America)

7 More presentations in this session

Presentation thumbnail
Validation of an artificial intelligence model for occlusion myocardial infarction identification: initial findings from a Portuguese cohort
Doctor M. Grine (Coimbra, PT)
Abstract Slides Video
Presentation thumbnail
Robust ecg analysis across various racial and ethnic populations: enhancing diversity
Mr J. Francey (Belfast, GB)
Abstract Slides Video
Presentation thumbnail
Biophysics-inspired deep learning for improved denoising in ventricular signals in ischemic cardiomyopathy
Mr S. Ruiperez-Campillo (Zurich, CH)
Abstract Slides Video
Presentation thumbnail
Abnormal P-waves morphology as a marker of atrial abnormality in a population-based cohort of patients with normal P-wave duration.
Doctor M. Baturova (Lund, SE)
Abstract Slides Video
Presentation thumbnail
Can an AI-powered smartphone app estimate moderate pulmonary hypertension by taking a 12-lead ECG of Japanese patients?
Assistant Professor T. Kaihara (Kawasaki, JP)
Abstract Slides Video

Access the full session

Session thumbnail
Precision cardiology: the role of signal processing and artificial intelligence

The Event

Event poster

ESC Congress 2025

29 August - 1 September 2025
You may be interested in
thumbnail
Congress Presentation
Prediction of new-onset atrial fibrillation in patients with hypertrophic cardiomyopathy using artificial intelligence-enhanced electrocardiogram
thumbnail
Congress Presentation
Prediction of atrial fibrillation from the electrocardiogram in the community using deep learning
thumbnail
Congress Presentation
Comparative analysis of classical artificial intelligence and deep learning models for atrial fibrillation detection in electrocardiograms

ESC 365 is supported by

novartis Explore sponsored resources

ESC 365 is supported by

novartis Explore sponsored resources