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Prediction of atrial fibrillation from the electrocardiogram in the community using deep learning

31 August 2025 (08:15 - 09:00)
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Congress Presentation Part of: Risk stratification models: leveraging digital health for better outcomes Deep Learning ESC Professional Premium Access ESC Congress 2025 European Society of Cardiology

About the speaker

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Doctor Luisa C C Brant

Federal University of Minas Gerais, Belo Horizonte (Brazil)

7 More presentations in this session

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Personalized approach to cardiovascular risk stratification: a randomized controlled trial evaluating the effectiveness of an AI-developed diet versus a standard mediterranean diet
Mr B. Rozibaev (Tashkent, UZ)
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Comparing machine learning models with established risk scores in predicting bleeding and ischaemic stroke in patients with atrial fibrillation undergoing transcatheter aortic valve implantation
Doctor G. Dangas (New York, US)
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Leveraging AI and clinical guidelines to identify undiagnosed and under-treated CKD patients for treatment optimisation
Ms A. Veldman (The Hague, NL)
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Quick and easy multi-pathology cardiovascular disease detection with an artificial intelligence-enabled stethoscope: multi-centre prospective validation study in secondary care
Doctor P. Bachtiger (London, GB)
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Efficiency of an artificial intelligence powered electrocardiogram model for early detection of occlusion myocardial infarction in acute coronary syndrome: a multicenter cohort study
Doctor C. Militello (Rome, IT)
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Access the full session

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Risk stratification models: leveraging digital health for better outcomes

The Event

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ESC Congress 2025

31 August 2025 08:15 CET
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