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Digitisation of electrocardiographic images enable artificial intelligence-based mortality prediction

2 September 2024 (13:00 - 13:50)
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Congress Presentation Part of: Breakthroughs in artificial intelligence-powered cardiac diagnosis and risk prediction Artificial Intelligence ESC Professional Premium Access ESC Congress 2024 European Society of Cardiology

About the speaker

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Doctor Konstantinos Patlatzoglou

Imperial College London, London (United Kingdom of Great Britain & Northern Ireland)

8 More presentations in this session

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Machine learning approach for detection of valvular heart disease through digital cardiac auscultation: results from multi-center prospective cross-sectional study
Professor I. Jung (Yongin, KR)
Abstract Slides Video
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Multivariate time-series clustering of cardiopulmonary exercise test data for cardiovascular risk stratification
Mr E. Ntalianis (Leuven, BE)
Abstract Slides Video
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Scan-rescan variability of AI-enabled cardiac functional assessment from cine CMR
Miss D. Wickremasinghe (London, GB)
Abstract Slides Video
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Artificial intelligence-enhanced electrocardiography predicts 10-year risk of atherosclerotic cardiovascular disease
Mr H. Zhang (London, GB)
Abstract Slides Video
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Visually evaluated performance of two AI algorithms detecting cardiac rhythm
Slides Video

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Breakthroughs in artificial intelligence-powered cardiac diagnosis and risk prediction

The Event

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ESC Congress 2024

2 September 2024 13:00 CET
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