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Utilizing unsupervised machine learning to uncover novel phenogroups within the broad QRS complex

30 August 2024 (11:05 - 11:15)
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Congress Presentation Part of: New insights from the ECG: screening and prediction Electrocardiography (ECG) ESC Professional Premium Access ESC Congress 2024 European Society of Cardiology

About the speaker

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Miss Mehak Gurnani

National Heart and Lung Institute Imperial College, London (United Kingdom of Great Britain & Northern Ireland)

5 More presentations in this session

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The impact of QRS complex fragmentation status before and after cardiac resynchronization therapy with defibrillator implantation: Is it a predictor of arrhythmic events?
Doctor L. De Miguel (Madrid, ES)
Abstract Slides Video
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Predicting atrial fibrillation from ECG characteristics
Doctor C. Binding (Copenhagen, DK)
Abstract Slides Video
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ECG as a screening tool for detection of significant functional mitral regurgitation in patients with left bundle branch block
Doctor O. Andrei (Bucharest, RO)
Abstract Slides Video
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Predicting 1-year atrial fibrillation risk from a patch-based ambulatory ECG monitoring without atrial fibrillation
Doctor E. Hytopoulos (US)
Abstract Slides Video
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Clinical validation of the 2021 European Society of Cardiology guidelines on pre-existing right bundle branch block patients undergoing transcatheter aortic valve replacement
Mr M. Salis (Basel, CH)
Abstract Slides Video

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New insights from the ECG: screening and prediction
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The Event

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ESC Congress 2024

30 August 2024 11:05 CET
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