Rhythm classifier: artificial intelligence for rhythm classification in insertable cardiac monitor

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Rhythm classifier: artificial intelligence for rhythm classification in insertable cardiac monitor

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

Topic: Artificial Intelligence (Machine Learning, Deep Learning)

Speaker: Mr S. Majumder (Minneapolis, US)

Event: ESC Congress 2024

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About the speaker

Mr Shubha Majumder

Medtronic, Inc., Minneapolis (United States of America)

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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)

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

Speaker: Mr H. Zhang (London, GB)

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Breakthroughs in artificial intelligence-powered cardiac diagnosis and risk prediction

Speakers: Mr S. Majumder, 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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