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Electrocardiographic aging based on artificial intelligence and the risk of heart failure and its subtypes: a multi-national study

28 August 2026 (13:15 - 14:00)
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Congress Presentation Part of: State-of-the-art in artificial intelligence for electrocardiography research Electrocardiogram (ECG) and Arrhythmia Analysis ESC2026 Premium Access ESC Congress 2026 European Society of Cardiology

About the speaker

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Doctor Seyong Chung

Yonsei University, Seoul (Korea (Republic of))

4 More presentations in this session

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Improving ECG diagnostic performance under ambulatory noise with scalable long-range state-space denoising modelling
Doctor S. Ruiperez-Campillo (Zurich, CH)
Abstract Slides
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Deep learning detection of cardiac amyloidosis from ECG images: validation across diverse clinical and prospective cohorts
Mr P. Croon (New Haven, US)
Abstract Slides
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Reliability of snapshot AI-ECG predictions: test-retest reproducibility across seven prediction tasks in three hospital cohorts
Doctor H. Aggour (London, GB)
Abstract Slides
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Reinforcement learning with GSPO enables vision language model (VLM) to detect structural heart disease from 12-lead electrocardiography
Mr W. Wong (Hong Kong, HK)
Abstract Slides

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State-of-the-art in artificial intelligence for electrocardiography research

The Event

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ESC Congress 2026

28 August 2026 13:15 CET
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