Artificial intelligence-assisted examination of cardiac health status through electrocardiogram

28 August 2023 (08:15 - 09:00)

Organised by:

Video

Sign in for access options

Abstract

Slides

About the speaker

Mr Dian-Yo Sung

Wego High School, Taipei (Taiwan)

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

Electrocardiographic artificial intelligence model for timely detection of preeclampsia

Doctor O. Akbilgic (Winston-Salem, US)

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

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

Congress Presentation

Preventing unnecessary echocardiograms in de novo patients referred to the cardiology outpatient clinic using electrocardiogram-based deep learning

Congress Session

What can we learn from artificial intelligence-ECG interpretation?

Congress Presentation

Use of artificial intelligence for diagnosis of heart failure: echo

ESC 365 is supported by

novartis

Explore sponsored resources

ESC 365 is supported by

novartis

Explore sponsored resources