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

Session: Risk stratification models: leveraging digital health for better outcomes
Topic: Deep Learning
Speaker: Doctor L. Brant (Belo Horizonte, BR)
Event: ESC Congress 2025

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About the speaker

Doctor Luisa C C Brant

Federal University of Minas Gerais, Belo Horizonte (Brazil)
2 presentations
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7 more presentations in this session

Personalized approach to cardiovascular risk stratification: a randomized controlled trial evaluating the effectiveness of an AI-developed diet versus a standard mediterranean diet

Speaker: 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

Speaker: 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

Speaker: 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

Speaker: 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

Speaker: Doctor C. Militello (Rome, IT)

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Access the full session

Risk stratification models: leveraging digital health for better outcomes

Speakers: Doctor L. Brant, Mr B. Rozibaev, Doctor G. Dangas, Ms A. Veldman, Doctor P. Bachtiger...
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About the event

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ESC Congress 2025

29 August - 1 September 2025

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