Visually evaluated performance of two AI algorithms detecting cardiac rhythm

Back

ESC Premium Access

Visually evaluated performance of two AI algorithms detecting cardiac rhythm

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

Topic: Artificial Intelligence (Machine Learning, Deep Learning)

Event: ESC Congress 2024

Congress Presentation

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)

Access the full session

Breakthroughs in artificial intelligence-powered cardiac diagnosis and risk prediction

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

Access

About the event

ESC Congress 2024

30 August - 2 September 2024

Sessions Presentations

Congress

ESC 365 is supported by

Explore sponsored resources