Back

Identification of at-risk populations for cardiac amyloidosis: a multimodal machine learning development and validation study

31 August 2025 (09:27 - 09:45)
Organised by: Logo
Congress Presentation Part of: Digital innovations in clinical practice Machine Learning ESC Professional Premium Access ESC Congress 2025 European Society of Cardiology

About the speaker

Photo
Doctor Clemens Spielvogel

Medical University of Vienna, Vienna (Austria)

4 More presentations in this session

Presentation thumbnail
State-of-the-art lecture on digital innovations in clinical practice
Professor P. Vardas (Heraklion, GR)
Slides Video
Presentation thumbnail
A health economic evaluation of the TriageHF Plus clinical care pathway for device-based remote monitoring of heart failure
Doctor J. Taylor (Manchester, GB)
Abstract Slides Video
Presentation thumbnail
Insight into pill-in-pocket oral anticoagulation therapy with continuous monitoring of atrial fibrillation using a patient-level computational model
Mr M. Cai (Maastricht, NL)
Abstract Slides Video
Presentation thumbnail
Cardiovascular synchronisation to music : blood pressure entrainment to expressive musical structures
Miss N. Cotic (London, GB)
Abstract Slides Video

Access the full session

Session thumbnail
Digital innovations in clinical practice
Video

The Event

Event poster

ESC Congress 2025

31 August 2025 09:27 CET
You may be interested in
thumbnail
Congress Presentation
Detection and risk stratification of cardiac amyloidosis patients by integration of imaging and non-imaging data using a machine learning approach
thumbnail
Congress Presentation
Targeted deployment of AI-ECG for efficient screening of transthyretin amyloid cardiomyopathy using deep learning representations of longitudinal electronic health records
thumbnail
Congress Session
Transthyretin cardiac amyloidosis

ESC 365 is supported by

novartis Explore sponsored resources

ESC 365 is supported by

novartis Explore sponsored resources