Back

Neural network-derived electrocardiographic features have prognostic significance and important phenotypic and genotypic associations

28 August 2023 (08:48 - 09:06)
Organised by: Logo
Congress Presentation Part of: The latest in cardiovascular diagnostics supported by artificial intelligence Artificial Intelligence ESC Professional Premium Access ESC Congress 2023 European Society of Cardiology

About the speaker

Photo
Doctor Libor Pastika

Imperial College London, London (United Kingdom of Great Britain & Northern Ireland)

4 More presentations in this session

Presentation thumbnail
State-of-the-art lecture on artificial intelligence in cardiology
Professor U. Landmesser (Berlin, DE)
Slides Video
Presentation thumbnail
Artificial intelligence-derived ECG bio-index as a tool for predicting the prognosis of patients with ST-segment elevation myocardial infarction underwent primary percutaneous coronary intervention
Assistant Professor K. Jeon (Seongnam, KR)
Abstract Slides Video
Presentation thumbnail
Validation of a novel cuffless photoplethysmography-based wristband for measuring blood pressure according to the regulatory standard
Doctor E. Ronner (Delft, NL)
Abstract Slides Video
Presentation thumbnail
Reducing the burden of inconclusive smart-device single-lead ECG tracings via a novel atificial intelligence algorithm
Mr S. Weidlich (Basel, CH)
Abstract Slides Video

Access the full session

Session thumbnail
The latest in cardiovascular diagnostics supported by artificial intelligence
Video

The Event

Event poster

ESC Congress 2023

28 August 2023 08:48 CET
You may be interested in
thumbnail
Congress Session
The latest in cardiovascular diagnostics supported by artificial intelligence
thumbnail
Congress Session
What can we learn from artificial intelligence-ECG interpretation?
thumbnail
Congress Session
New insights from the ECG: screening and prediction

ESC 365 is supported by

novartis Explore sponsored resources

ESC 365 is supported by

novartis Explore sponsored resources