ESC 365 - Long-term prediction of heart failure using an ECG-based fine-tuned self-supervised neural network model identifies 23 genetic loci implicating electrophysiological mechanisms

ESC2025 Premium Access

Long-term prediction of heart failure using an ECG-based fine-tuned self-supervised neural network model identifies 23 genetic loci implicating electrophysiological mechanisms

Session: Heart failure: prediction and prognosis

Topic: Epidemiology, Prognosis, Outcome

Speaker: Doctor J. Ramirez (Zaragoza, ES)

Event: ESC Congress 2025

Congress Presentation

Add to my library

About the speaker

Doctor Julia Ramirez

University of Zaragoza, Zaragoza (Spain)

1 presentation

0 follower

3 more presentations in this session

The prognostic role of fibrosis-4 score in heart failure with reduced ejection fraction

Speaker: Doctor A. Mohamed (Copenhagen, DK)

Left ventricular filling pressure by artificial intelligence-enabled electrocardiogram, echocardiography, and cardiac catheterization

Speaker: Doctor G. Tsaban (Rochester, US)

Multinational assessment of traditional and AI-electrocardiography based risk prediction for heart failure in prospective cohort studies

Speaker: Doctor A. Pedroso (New Haven, US)

Access the full session

Heart failure: prediction and prognosis

Speakers: Doctor J. Ramirez, Doctor A. Mohamed, Doctor G. Tsaban, Doctor A. Pedroso

About the event

ESC Congress 2025

29 August - 1 September 2025

Sessions Presentations

Congress

ESC 365 is supported by

bristol-myers-squibb

Explore sponsored resources

novartis

Explore sponsored resources