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Artificial intelligence-enhanced electrocardiography predicts 10-year risk of atherosclerotic cardiovascular disease

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Mr Henry Zhang

London (United Kingdom of Great Britain & Northern Ireland)
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8 more presentations in this session

Machine learning approach for detection of valvular heart disease through digital cardiac auscultation: results from multi-center prospective cross-sectional study

Speaker: Professor I. Jung (Yongin, KR)

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Multivariate time-series clustering of cardiopulmonary exercise test data for cardiovascular risk stratification

Speaker: Mr E. Ntalianis (Leuven, BE)

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Digitisation of electrocardiographic images enable artificial intelligence-based mortality prediction

Speaker: Doctor K. Patlatzoglou (London, GB)

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Scan-rescan variability of AI-enabled cardiac functional assessment from cine CMR

Speaker: Miss D. Wickremasinghe (London, GB)

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Visually evaluated performance of two AI algorithms detecting cardiac rhythm

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Breakthroughs in artificial intelligence-powered cardiac diagnosis and risk prediction

Speakers: Mr H. Zhang, Professor I. Jung, Mr E. Ntalianis, Doctor K. Patlatzoglou, Miss D. Wickremasinghe
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ESC Congress 2024

30 August - 2 September 2024

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