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Early identification of underdiagnosed HFpEF by artificial intelligence from electrocardiogram

21 November 2025 (08:00 - 18:00)
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Congress Presentation Part of: AI in ECG-based risk stratification and disease prediction Artificial Intelligence, Other Open Access ESC Digital & AI Summit 2025 European Society of Cardiology

About the speaker

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Professor Oguz Akbilgic

Wake Forest Baptist Medical Center, Winston-Salem (United States of America)

5 More presentations in this session

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Enhancing pre-test probability models for suspected coronary artery disease using 12-lead electrocardiogram
Mr J. Hennecken (Amsterdam, NL)
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Beyond black-box electrocardiogram analysis: saliency-guided deep learning for differential diagnosis of tachyarrhythmias
Doctor P. Pantelidis (Athens, GR)
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Electrocardiographic sex index applied to children: a proxy assessment for heart maturation
Professor O. Akbilgic (Winston-Salem, US)
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Electrocardiogram-based artificial intelligence to predict incident heart failure risk
Doctor S. Kany (Hamburg, DE)
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Artificial intelligence derived ECG-age as a biomarker of mortality: a systematic review and meta-analysis
Doctor I. Bozzi (Belo Horizonte, BR)
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Access the full session

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AI in ECG-based risk stratification and disease prediction

The Event

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ESC Digital & AI Summit 2025

21 November - 22 November 2025

ESC 365 is supported by

novartis Explore sponsored resources

ESC 365 is supported by

novartis Explore sponsored resources