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Development of a short-term mortality risk prediction model for patients with QTc prolongation based on 12-lead electrocardiogram

Session: What can we learn from artificial intelligence-ECG interpretation?
Topic: Deep Learning
Speaker: Doctor C. Wang (Beijing, CN)
Event: ESC Congress 2025

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Doctor Chenyuan Wang

Beijing (China)
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4 more presentations in this session

Prospective validation of an ensemble deep learning algorithm for detecting structural heart disease using real-world 12-lead electrocardiogram images

Speaker: Doctor A. Poopak (Tehran, IR)

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Longitudinal ECG trajectories identify high-risk aortic stenosis phenotypes years prior to TAVR

Speaker: Doctor M. Segar (Houston, US)

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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

Speaker: Associate Professor Y. Baek (Incheon, KR)

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

Speaker: Doctor D. Biswas (New Haven, US)

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What can we learn from artificial intelligence-ECG interpretation?

Speakers: Doctor C. Wang, Doctor A. Poopak, Doctor M. Segar, Associate Professor Y. Baek, Doctor D. Biswas
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ESC Congress 2025

29 August - 1 September 2025

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