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Explainable electrocardiogram-based deep learning predicts ventricular arrhythmias after cardiac resynchronisation therapy.

28 August 2026 (12:15 - 13:00)
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Congress Presentation Part of: Artificial intelligence and digital phenotyping in arrhythmia risk prediction and cardiac resynchronisation Cardiac Resynchronisation Therapy (CRT) ESC2026 Premium Access ESC Congress 2026 European Society of Cardiology

About the speaker

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Miss Cheyenne Sin Lin Chiu

University Medical Center Utrecht, Utrecht (Netherlands (The))

6 More presentations in this session

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Temporal risk of heart failure hospitalisation during multisensor alert state: a self-controlled case series analysis of 1.7 million ambulatory person days
Doctor L. Witten Davodian (Copenhagen, DK)
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Risk of heart failure hospitalisation stratified by multisensor alert severity by implantable cardiac devices
Doctor L. Witten Davodian (Copenhagen, DK)
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Inducibility of clinical ventricular tachycardia by pre-ablation noninvasive programmed stimulation predicts favorable outcomes after catheter ablation
Doctor A. Kashiwa (Niigata, JP)
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Defining the QRS threshold for LOT-CRT benefit: a conduction pattern specific analysis
Doctor B. Bakst (Browns Mills, US)
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Predictors of left ventricular ejection fraction improvement following conduction system and biventricular resynchronization: a subanalysis of the PhysioSync-HF trial
Doctor I. Bitencourt (Porto Alegre, BR)
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Artificial intelligence and digital phenotyping in arrhythmia risk prediction and cardiac resynchronisation

The Event

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ESC Congress 2026

28 August 2026 12:15 CET
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