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Extensible artificial intelligence model predicts post-ablation AF recurrence using coronary sinus electrogram

29 August 2020 (00:00 - 00:00)
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Congress Presentation Part of: Predicting and Detecting Atrial Fibrillation Rhythm Control, Catheter Ablation ESC Premium Access ESC Congress 2020

About the speaker

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Mr Kaibin Lin

Zhongshan Hospital Fudan University, Shanghai (China)

5 More presentations in this session

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Prediction of atrial fibrillation by 12-lead electrocardiogram parameters in patients without structural heart disease
Doctor N. Hirota (Tokyo, JP)
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Improving prediction of atrial fibrillation: the impact of polygenic risk scores over conventional risk factors amongst 270,000 individuals in UK Biobank
Mr A. Von Ende (Oxford, GB)
Abstract Slides
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High bodyweight variability and increased risk of atrial fibrillation in patients with type 2 diabetes mellitus
Doctor H. Lee (Seoul, KR)
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Community pharmacy led atrial fibrillation detection and referral service - the Capture AF study
Ms Z. Khanbhai (London, GB)
Abstract Slides
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Screening for atrial fibrillation in subjects aged 65 using a long-term continuous ECG telemonitoring vest: the NOninvasive Monitoring for early detection of atrial fibrillation (NOMED-AF) study
Professor B. Sredniawa (Katowice, PL)
Abstract Slides

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Predicting and Detecting Atrial Fibrillation

The Event

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ESC Congress 2020

29 August - 1 September 2020

ESC 365 is supported by

novartis Explore sponsored resources

ESC 365 is supported by

novartis Explore sponsored resources