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

Session: Data meets diagnostics: use of artificial intelligence in arrhythmias
Topic: Deep Learning
Speaker: Doctor G. Fujiki (Tokyo, JP)
Event: ESC Congress 2025

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Doctor Goro Fujiki

The University of Tokyo Hospital, Tokyo (Japan)
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Artificial intelligence for prediction of major arrhythmic events in dilated cardiomyopathy

Speaker: Doctor M. Coriano' (London, GB)

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

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

Speaker: Doctor Z. Xiao (Shanghai, CN)

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

Speaker: Mr L. Lin (Madrid, ES)

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Identifying optimal electrocardiogram lead combinations for artificial intelligence

Speaker: Mr M. Nakayama (Boston, US)

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Data meets diagnostics: use of artificial intelligence in arrhythmias

Speakers: Doctor G. Fujiki, Doctor M. Coriano', Mr Y. Na, Doctor Z. Xiao, Mr L. Lin...
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ESC Congress 2025

29 August - 1 September 2025

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