Back

Unsupervised machine learning applied to CPETecho for subclassifying heart failure with preserved ejection fraction: a pathophysiological approach.

5 April 2025 (10:57 - 11:06)
Organised by: Logo
Congress Presentation Part of: Artificial intelligence and machine learning applications Pathophysiology and Mechanisms EAPC Premium Access ESC Preventive Cardiology 2025 European Association of Preventive Cardiology (EAPC)

About the speaker

Photo
Ms Stephanie De Schutter

University of Antwerp, Antwerp (Belgium)

3 More presentations in this session

Presentation thumbnail
Optimizing weight loss with AI: a randomized trial of dietary supplement prescriptions in obese patients
Professor E. Pokushalov (San Francisco, US)
Abstract Slides
Presentation thumbnail
Life's essential 8 score and 10-year cardiovascular outcomes in atrial fibrillation: a UK biobank analysis with simulated health gains through lifestyle improvement
Doctor B. Buckley (Liverpool, GB)
Abstract Slides Video
Presentation thumbnail
Polygenic risk scores in dilated cardiomyopathy: associations with arrhythmic events and implications for clinical research
Ms I. Gandin (Trieste, IT)
Abstract Slides Video

Access the full session

Session thumbnail
Artificial intelligence and machine learning applications

The Event

Event poster

ESC Preventive Cardiology 2025

5 April 2025 10:57 CET
You may be interested in
thumbnail
Congress Session
Refining phenotyping in heart failure
thumbnail
Congress Presentation
Machine learning for the diagnosis of HFpEF?
thumbnail
Congress Presentation
Identifying clinical phenotype clusters for coronary artery disease: a novel approach using clustering by unsupervised machine learning

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