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High-dimensional phenotypic matching with artificial intelligence-enhanced ECG to replicate heart failure trial outcomes in real-world data

29 August 2025 (07:00 - 18:00)
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Congress Presentation Part of: What can we learn from artificial intelligence-ECG interpretation? Trial Design ESC Professional Premium Access ESC Congress 2025 European Society of Cardiology

About the speaker

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Doctor Dhruva Biswas

Yale School of Medicine, New Haven (United States of America)

4 More presentations in this session

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Prospective validation of an ensemble deep learning algorithm for detecting structural heart disease using real-world 12-lead electrocardiogram images
Doctor A. Poopak (Tehran, IR)
Abstract Slides Video
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Development of a short-term mortality risk prediction model for patients with QTc prolongation based on 12-lead electrocardiogram
Doctor C. Wang (Beijing, CN)
Abstract Slides Video
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Longitudinal ECG trajectories identify high-risk aortic stenosis phenotypes years prior to TAVR
Doctor M. Segar (Houston, US)
Abstract Slides Video
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ECG-based artificial enhancement for risk stratification of thromboembolic and major adverse cardiac events in atrial fibrillation compared with CHA2DS2-VA scoring
Associate Professor Y. Baek (Incheon, KR)
Abstract Slides Video

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What can we learn from artificial intelligence-ECG interpretation?
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The Event

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ESC Congress 2025

29 August - 1 September 2025
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