Back

Prediction of atrial fibrillation from the electrocardiogram in the community using deep learning

29 August 2025 (07:00 - 18:00)
Organised by: Logo
Congress Presentation Part of: Risk stratification models: leveraging digital health for better outcomes Deep Learning ESC Professional Premium Access ESC Congress 2025 European Society of Cardiology

About the speaker

Photo
Doctor Luisa C C Brant

Federal University of Minas Gerais, Belo Horizonte (Brazil)

7 More presentations in this session

Presentation thumbnail
Personalized approach to cardiovascular risk stratification: a randomized controlled trial evaluating the effectiveness of an AI-developed diet versus a standard mediterranean diet
Mr B. Rozibaev (Tashkent, UZ)
Abstract Slides Video
Presentation thumbnail
Comparing machine learning models with established risk scores in predicting bleeding and ischaemic stroke in patients with atrial fibrillation undergoing transcatheter aortic valve implantation
Doctor G. Dangas (New York, US)
Abstract Slides
Presentation thumbnail
Leveraging AI and clinical guidelines to identify undiagnosed and under-treated CKD patients for treatment optimisation
Ms A. Veldman (The Hague, NL)
Abstract Slides Video
Presentation thumbnail
Quick and easy multi-pathology cardiovascular disease detection with an artificial intelligence-enabled stethoscope: multi-centre prospective validation study in secondary care
Doctor P. Bachtiger (London, GB)
Abstract Slides Video
Presentation thumbnail
Efficiency of an artificial intelligence powered electrocardiogram model for early detection of occlusion myocardial infarction in acute coronary syndrome: a multicenter cohort study
Doctor C. Militello (Rome, IT)
Abstract Slides Video

Access the full session

Session thumbnail
Risk stratification models: leveraging digital health for better outcomes

The Event

Event poster

ESC Congress 2025

29 August - 1 September 2025
You may be interested in
thumbnail
Congress Presentation
Performance of a deep learning ECG model in predicting atrial fibrillation among patients with implantable loop recorders
thumbnail
Congress Presentation
Predicting incident atrial fibrillation using AI-ECG: enhancing risk stratification for stroke prevention
thumbnail
Congress Presentation
Prediction of new-onset atrial fibrillation in patients with hypertrophic cardiomyopathy using artificial intelligence-enhanced electrocardiogram

ESC 365 is supported by

novartis Explore sponsored resources

ESC 365 is supported by

novartis Explore sponsored resources