ESC 365 - 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

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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

Session: Machine Learning Approaches to ECG Interpretation: State of the Art

Topic: Electrocardiogram (ECG) and Arrhythmia Analysis

Speaker: Professor F. Verbrugge (Brussels, BE)

Event: ESC Congress 2020

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About the speaker

Professor Frederik Hendrik Verbrugge

University Hospital (UZ) Brussels, Brussels (Belgium)

13 presentations

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3 more presentations in this session

State-of-the-art lecture in Machine learning approaches to ECG interpretation.

Speaker: Professor B. Rodriguez (Oxford, GB)

Distinguishing sinus rhythm from atrial fibrillation on single-lead ECGs using a deep neural network

Speaker: Miss M. Oudkerk Pool (Amsterdam, NL)

Artificial intelligence methodology: multi-label classification of abnormal EKG records

Speaker: Doctor S. Mehta (Miami, US)

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Machine Learning Approaches to ECG Interpretation: State of the Art

Speakers: Professor F. Verbrugge, Professor B. Rodriguez, Miss M. Oudkerk Pool, Doctor S. Mehta

About the event

ESC Congress 2020

29 August - 1 September 2020

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