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Atrial fibrillation burden and risk of new development through artificial intelligence analysis of an electrocardiogram in hospitalized patients with heart failure and preserved ejection fraction

29 August 2020 (11:17 - 11:27)
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Congress Presentation Part of: Machine Learning Approaches to ECG Interpretation: State of the Art Electrocardiogram (ECG) and Arrhythmia Analysis ESC Premium Access ESC Congress 2020

About the speaker

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Professor Frederik Hendrik Verbrugge

University Hospital (UZ) Brussels, Brussels (Belgium)

3 More presentations in this session

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State-of-the-art lecture in Machine learning approaches to ECG interpretation.
Professor B. Rodriguez (Oxford, GB)
Slides Video
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Distinguishing sinus rhythm from atrial fibrillation on single-lead ECGs using a deep neural network
Miss M. Oudkerk Pool (Amsterdam, NL)
Abstract Slides Video
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Artificial intelligence methodology: multi-label classification of abnormal EKG records
Doctor S. Mehta (Miami, US)
Abstract Slides Video

Access the full session

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Machine Learning Approaches to ECG Interpretation: State of the Art

The Event

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ESC Congress 2020

29 August 2020 11:17 CET
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