Artificial intelligence-assisted examination of cardiac health status through electrocardiogram

25 August 2023 (07:30 - 18:30)

Organised by:

Sign in for access options

Sign in to view the resources

Sign in for access options

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

25 August - 28 August 2023

You may be interested in

Congress Presentation

Real-world evaluation of an algorithmic machine-learning-guided testing approach in stable chest pain: a multinational, multicohort study

Congress Session

Evolutions in arrythmia and syncope management

Congress Presentation

AI in cardiology: a force for progress? pro

ESC 365 is supported by

novartis

Explore sponsored resources

ESC 365 is supported by

novartis

Explore sponsored resources