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Machine learning model using heart rate variability for the prediction of vasovagal syncope

30 August 2024 (08:00 - 17:30)
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Congress Presentation Part of: Artificial intelligence innovations in cardiac risk assessment and disease prediction Artificial Intelligence ESC Professional Premium Access ESC Congress 2024 European Society of Cardiology

About the speaker

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Mr Jun Hwan Cho

Chung-Ang University Gwangmyeong hospital, Seoul (Korea (Republic of))

6 More presentations in this session

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The added value of device measured physical activity to the prediction of incident cardiovascular disease.
Mr A. Sturge (Oxford, GB)
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How does lead selection impact diagnosis through AI? Implications for continuous monitoring systems using convolutional neural networks
Professor J. Millet (Valencia, ES)
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Prospective evaluation of an AI algorithm for real-time LVEF assessment in acute coronary syndrome using left coronary angiograms: the CathEF multicenter study
Doctor R. Avram (Montreal, CA)
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Artificial intelligence in cardiology: a machine learning model for supraventricular tachycardia discrimination
Doctor P. Avila Alonso (Madrid, ES)
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Deep learning enables the fully automated quantification of high-resolution cardiac CT images: human in loop for model development
Mr G. Baj (Bern, CH)
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Artificial intelligence innovations in cardiac risk assessment and disease prediction

The Event

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ESC Congress 2024

30 August - 2 September 2024
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ESC 365 is supported by

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