ECG-based deep learning for detecting epicardial coronary occlusion in acute myocardial infarction

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ECG-based deep learning for detecting epicardial coronary occlusion in acute myocardial infarction

Session: Allow artificial intelligence to assist with diagnostic heavy lifting

Topic: Artificial Intelligence (Machine Learning, Deep Learning)

Speaker: Doctor R. Herman (Aalst, BE)

Event: ESC Congress 2023

Congress Presentation

About the speaker

Doctor Robert Herman

Cardiovascular Research Center Aalst, Aalst (Belgium)

1 presentation

3 followers

7 more presentations in this session

Combining hypothesis-driven ECG indices with machine learning improves ventricular arrhythmic risk prediction in a low-risk population

Speaker: Doctor J. Ramirez (Zaragoza, ES)

Electrocardiographic artificial intelligence model for timely detection of preeclampsia

Speaker: Doctor O. Akbilgic (Winston-Salem, US)

Performance of survival neural networks in predicting 10-year cardiovascular disease risk in UK and Chinese populations

Speaker: Ms X. LIU (Beijing, CN)

The exploratory clinical trial of AI-enabled Holter electrocardiogram for diagnosis of paroxysmal atrial fibrillation from sinus rhythm waveforms

Speaker: Professor Y. Tamura (Tokyo, JP)

Artificial intelligence-assisted examination of cardiac health status through electrocardiogram

Speaker: Mr D. Sung (Taipei, TW)

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Allow artificial intelligence to assist with diagnostic heavy lifting

Speakers: Doctor R. Herman, Doctor J. Ramirez, Doctor O. Akbilgic, Ms X. LIU, Professor Y. Tamura...

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About the event

ESC Congress 2023

25 August - 28 August 2023

Sessions Presentations

Congress

ECG-based deep learning for detecting epicardial coronary occlusion in acute myocardial infarction

About the speaker

Doctor Robert Herman

7 more presentations in this session

Combining hypothesis-driven ECG indices with machine learning improves ventricular arrhythmic risk prediction in a low-risk population

Electrocardiographic artificial intelligence model for timely detection of preeclampsia

Performance of survival neural networks in predicting 10-year cardiovascular disease risk in UK and Chinese populations

The exploratory clinical trial of AI-enabled Holter electrocardiogram for diagnosis of paroxysmal atrial fibrillation from sinus rhythm waveforms

Artificial intelligence-assisted examination of cardiac health status through electrocardiogram

Access the full session

Allow artificial intelligence to assist with diagnostic heavy lifting

About the event

ESC Congress 2023

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