ESC 365 - Prediction of aortic stenosis progression using artificial intelligence: a machine learning model based on echocardiographic data

ESC2025 Premium Access

Prediction of aortic stenosis progression using artificial intelligence: a machine learning model based on echocardiographic data

Session: Young Investigator Award Session in Valvular Heart Disease

Topic: Imaging

Speaker: Doctor E. Itelman (Petah Tikva, IL)

Event: ESC Congress 2025

Congress Presentation

Add to my library

About the speaker

Doctor Edward Itelman

Rabin Medical Center, Petah Tikva (Israel)

0 follower

3 more presentations in this session

Nano drug delivery system using green solvents: a novel safe promise for the treatment of infective endocarditis

Speaker: Miss M. Nazir (Bonn, DE)

Differences of male and female patients undergoing transcatheter edge-to-edge repair for tricuspid regurgitation: Insights from the EuroTR registry

Speaker: Doctor M. Wild (Freiburg, DE)

Sex-specific differences in right heart remodeling and patient outcomes in secondary tricuspid regurgitation

Speaker: Doctor M. Tomaselli (Milan, IT)

Access the full session

Young Investigator Award Session in Valvular Heart Disease

Speakers: Doctor E. Itelman, Miss M. Nazir, Doctor M. Wild, Doctor M. Tomaselli

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