Comparison of ECG-based neural networks for predicting atrial fibrillation across subgroups in the population

3 April 2025 (08:00 - 19:00)

Organised by:

Sign in to view the resources

Sign in for access options

About the speaker

Mr Benjamin Holderied

Bioinformatik, Greifswald (Germany)

6 More presentations in this session

Presentation thumbnail

A machine learning approach predicts response to physical exercise training using pulse wave analysis

Doctor B. Schmitz (Ennepetal, DE)

Abstract Slides

Presentation thumbnail

Defining two dimensional transthoracic echocardiographic aorta dimension reference ranges in healthy subjects: a machine learning based model

Doctor A. Carbone (Naples, IT)

Abstract Slides

Presentation thumbnail

Developing a personalized communication model using data-driven personas and clusters to enhance FH pediatric screening

Ms B. Cucos (Bucharest, RO)

Abstract Slides

Presentation thumbnail

Evaluating the feasibility of the AI-powered Calcount smart diet smartphone application among healthcare workers in a pilot study

Ms K. Kuliesiute (Vilnius, LT)

Abstract Slides

Presentation thumbnail

Development of the CARE-DM model to predict the risk of cardiovascular disease in older adults with type 2 diabetes

Ms V. Aponte Ribero (Bern, CH)

Abstract Slides

Access the full session

Session thumbnail

Artificial intelligence and machine learning in risk prediction, prevention and care

The Event

Event poster

ESC Preventive Cardiology 2025

3 April - 5 April 2025

You may be interested in

Congress Presentation

Interactive discussion and Q&A

Congress Session

EHRA Myths - Device-detected atrial fibrillation

Congress Presentation

Device-detected or clinically diagnosed atrial fibrillation: the same decision for oral anticoagulation therapy - discussion

ESC 365 is supported by

novartis

Explore sponsored resources

ESC 365 is supported by

novartis

Explore sponsored resources