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Application of machine learning techniques to optimise for limited datasets in an AI-ECG model for Brugada classification

31 March 2025 (09:30 - 10:15)
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Congress Presentation Part of: Artificial intelligence and arrhythmias (1) Artificial Intelligence EHRA Premium Access EHRA 2025 European Heart Rhythm Association (EHRA)

About the speaker

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Doctor Keenan Saleh

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

6 More presentations in this session

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Enhancing thromboembolic and major adverse cardiac events risk assessment in atrial fibrillation using AI-driven ECG: a comparative analysis with CHA2DS2-VA scoring
Associate Professor Y. Baek (Incheon, KR)
Abstract Slides Video
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Enhancing atrial fibrillation detection during normal sinus rhythm using self-supervised electrocardiogram foundation model
Associate Professor K. Lee (Gwangju, KR)
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Prediction and classification of aortic stenosis severity based on electrocardiogram with deep learning model
Associate Professor K. Lee (Gwangju, KR)
Abstract Slides Video
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Beyond human accuracy: application of artificial intelligence for establishing syncope diagnosis in daily practice of the syncope unit
Mr S. van Zanten (Delft, NL)
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Artificial intelligence estimated electrocardiographic age trajectory predicts recurrence after atrial fibrillation catheter ablation
Doctor H. Park (Seoul, KR)
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Access the full session

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Artificial intelligence and arrhythmias (1)

The Event

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EHRA 2025

31 March 2025 09:30 CET
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ESC 365 is supported by

novartis Explore sponsored resources