Back

Electrocardiographic artificial intelligence model for timely detection of preeclampsia

28 August 2023 (08:15 - 09:00)
Organised by: Logo
Congress Presentation Part of: Allow artificial intelligence to assist with diagnostic heavy lifting Electrocardiogram (ECG) and Arrhythmia Analysis ESC Professional Premium Access ESC Congress 2023 European Society of Cardiology

About the speaker

Photo
Professor Oguz Akbilgic

Wake Forest Baptist Medical Center, Winston-Salem (United States of America)

7 More presentations in this session

Presentation thumbnail
Combining hypothesis-driven ECG indices with machine learning improves ventricular arrhythmic risk prediction in a low-risk population
Doctor J. Ramirez (Zaragoza, ES)
Abstract Slides Video
Presentation thumbnail
Performance of survival neural networks in predicting 10-year cardiovascular disease risk in UK and Chinese populations
Ms X. LIU (Beijing, CN)
Abstract Slides Video
Presentation thumbnail
The exploratory clinical trial of AI-enabled Holter electrocardiogram for diagnosis of paroxysmal atrial fibrillation from sinus rhythm waveforms
Professor Y. Tamura (Tokyo, JP)
Abstract Slides Video
Presentation thumbnail
Artificial intelligence-assisted examination of cardiac health status through electrocardiogram
Mr D. Sung (Taipei, TW)
Abstract Slides Video
Presentation thumbnail
ECG-based deep learning for detecting epicardial coronary occlusion in acute myocardial infarction
Doctor R. Herman (Aalst, BE)
Abstract Slides Video

Access the full session

Session thumbnail
Allow artificial intelligence to assist with diagnostic heavy lifting

The Event

Event poster

ESC Congress 2023

28 August 2023 08:15 CET
You may be interested in
thumbnail
Congress Presentation
Artificial intelligence-enhanced electrocardiography predicts 10-year risk of atherosclerotic cardiovascular disease
thumbnail
Congress Session
Spotlight on innovation: top publications in the European Heart Journal - Digital Health 2023-2024
thumbnail
Congress Session
Integration of artificial intelligence in electrocardiography: state of the art

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