ESC 365 - Artificial intelligence-enhanced electrocardiography predicts 10-year risk of atherosclerotic cardiovascular disease

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

Session: Breakthroughs in artificial intelligence-powered cardiac diagnosis and risk prediction

Topic: Artificial Intelligence (Machine Learning, Deep Learning)

Speaker: Mr H. Zhang (London, GB)

Event: ESC Congress 2024

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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)

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

Speaker: Mr E. Ntalianis (Leuven, BE)

Digitisation of electrocardiographic images enable artificial intelligence-based mortality prediction

Speaker: Doctor K. Patlatzoglou (London, GB)

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

Speaker: Miss D. Wickremasinghe (London, GB)

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

About the event

ESC Congress 2024

30 August - 2 September 2024

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