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Electrocardiographic artificial intelligence model for timely detection of preeclampsia

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

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Professor Oguz Akbilgic

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

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)
Abstract Slides Video
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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)
Abstract Slides Video
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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)
Abstract Slides Video
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Artificial intelligence-assisted examination of cardiac health status through electrocardiogram
Mr D. Sung (Taipei, TW)
Abstract Slides Video
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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

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Allow artificial intelligence to assist with diagnostic heavy lifting

The Event

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ESC Congress 2023

25 August - 28 August 2023
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