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Deep learning based prediction of atrial fibrillation incidence from 1-lead ECGs: a model development and validation study

28 August 2023 (08:15 - 09:00)
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Congress Presentation Part of: Allow artificial intelligence to assist with diagnostic heavy lifting Artificial Intelligence ESC Professional Premium Access ESC Congress 2023 European Society of Cardiology

About the speaker

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Mr Jan Bremer

The University Medical Center Hamburg-Eppendorf, Hamburg (Germany)

7 More presentations in this session

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Combining hypothesis-driven ECG indices with machine learning improves ventricular arrhythmic risk prediction in a low-risk population
Doctor J. Ramirez (Zaragoza, ES)
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Electrocardiographic artificial intelligence model for timely detection of preeclampsia
Doctor O. Akbilgic (Winston-Salem, US)
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Performance of survival neural networks in predicting 10-year cardiovascular disease risk in UK and Chinese populations
Ms X. LIU (Beijing, CN)
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The exploratory clinical trial of AI-enabled Holter electrocardiogram for diagnosis of paroxysmal atrial fibrillation from sinus rhythm waveforms
Professor Y. Tamura (Tokyo, JP)
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Artificial intelligence-assisted examination of cardiac health status through electrocardiogram
Mr D. Sung (Taipei, TW)
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Allow artificial intelligence to assist with diagnostic heavy lifting

The Event

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ESC Congress 2023

28 August 2023 08:15 CET
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ESC 365 is supported by

novartis Explore sponsored resources
novo-nordisk Explore sponsored resources