Back

Towards precision medicine in valvular heart diseases: a systematic review of predictive multimodal machine learning models.

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

About the speaker

Photo
Doctor Valentine Ojonugwa Idakwo

Ludwig Maximilians University, Munich (Germany)

3 More presentations in this session

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
Presentation thumbnail
AI foundation model for pathogenic gene variant prediction in dilated cardiomyopathy
Assistant Professor F. Tjong (Amsterdam, NL)
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
Deep learning-enabled electrocardiogram assessment of valvular heart disease
13 December 2024
thumbnail
Congress Presentation
Mapping the landscape of multimodal and multi-omics AI/ML in cardiovascular disease: a visual framework for innovation
22 November 2025
thumbnail
Congress Presentation
Machine learning model including left ventricular strain analysis for sudden cardiac death prediction in hypertrophic cardiomyopathy.
10 May 2023
thumbnail
Congress Presentation
Comparing machine learning models with established risk scores in predicting bleeding and ischaemic stroke in patients with atrial fibrillation undergoing transcatheter aortic valve implantation
31 August 2025

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