Back

AI foundation model for pathogenic gene variant prediction in dilated cardiomyopathy

31 August 2026 (11:15 - 12:00)
Organised by: Logo
Congress Presentation Part of: Artificial intelligence and big data for cardiovascular care Deep Learning ESC2026 Premium Access ESC Congress 2026 European Society of Cardiology

About the speaker

Photo
Assistant Professor Fleur Tjong

Amsterdam University Medical Centre (AUMC), Amsterdam (Netherlands (The))

3 More presentations in this session

Presentation thumbnail
Towards precision medicine in valvular heart diseases: a systematic review of predictive multimodal machine learning models.
Doctor V. Idakwo (Munich, DE)
Abstract Slides Video
Presentation thumbnail
Geographic variation in long-term health outcomes following myocardial infarction in England
Doctor M. Hall (Leeds, GB)
Abstract Slides Video
Presentation thumbnail
A novel AI-derived digital biomarker for monitoring disease progression in ATTR-CM: first-in-trial use of a computer vision AI-ECG algorithm within a phase 3 pivotal randomized controlled trial
Doctor R. Khera (New Haven, US)
Abstract Slides Video

Access the full session

Session thumbnail
Artificial intelligence and big data for cardiovascular care

The Event

Event poster

ESC Congress 2026

31 August 2026 11:15 CET
You may be interested in
thumbnail
Congress Presentation
Machine learning-based phenotyping and risk assessment of hypertrophic cardiomyopathy - linking ECGs, morphology and genotypes
10 December 2021
thumbnail
Congress Presentation
Clinical profile of the index case with idiopathic dilated cardiomyopathy requested genetic study.
29 June 2021
thumbnail
Congress Presentation
Accurate detection of dilated cardiomyopathy onset through machine learning predictions from ECG data
30 August 2024
thumbnail
Congress Presentation
Artificial intelligence to assist the echocardiographic identification of transthyretin cardiac amyloidosis
30 August 2024

ESC 365 is supported by

novartis Explore sponsored resources
novo-nordisk Explore sponsored resources

ESC 365 is supported by

novartis Explore sponsored resources
novo-nordisk Explore sponsored resources