Latent representation of intracardiac electrograms using an AI-based autoencoder for rhythm classification

29 August 2025 (07:00 - 18:00)

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About the speaker

Mr Long Lin

University Carlos III of Madrid, Madrid (Spain)

6 More presentations in this session

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Artificial intelligence for prediction of major arrhythmic events in dilated cardiomyopathy

Doctor M. Coriano' (London, GB)

Abstract Slides Video

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Impact of arrhythmias on the performance of a deep learning model for predicting echocardiographic abnormalities from electrocardiograms

Doctor G. Fujiki (Tokyo, JP)

Abstract Slides Video

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Development of deep learning models for predicting atrial fibrillation occurrence using real world hand-held mobile electrocardiograms

Mr Y. Na (Seoul, KR)

Abstract Slides Video

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Prediction of new-onset atrial fibrillation in patients with hypertrophic cardiomyopathy using artificial intelligence-enhanced electrocardiogram

Doctor Z. Xiao (Shanghai, CN)

Abstract Slides Video

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Identifying optimal electrocardiogram lead combinations for artificial intelligence

Mr M. Nakayama (Boston, US)

Abstract Slides Video

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Data meets diagnostics: use of artificial intelligence in arrhythmias

The Event

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ESC Congress 2025

29 August - 1 September 2025

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ESC 365 is supported by

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