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Machine learning-lased prediction of atrial fibrillation in patients with atrial high-rate episodes

31 August 2025 (16:33 - 16:45)
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Congress Presentation Part of: The rise of the machines: digital technology for device therapy Home and Remote Patient Monitoring ESC Professional Premium Access ESC Congress 2025 European Society of Cardiology

About the speaker

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Doctor Amir Askarinejad

Institute of Life Course and Medical Sciences, Liverpool (United Kingdom of Great Britain & Northern Ireland)

3 More presentations in this session

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Ultra-high-frequency ECG outperforms strauss criteria for diagnosing true left bundle branch block in candidates of cardiac resynchronization therapy
Doctor K. Curila (Prague, CZ)
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A multistate model of clinical trajectories of heart failure patients with implantable electronic devices followed with remote monitoring: what outcome implications of alerts and their timing
Doctor D. Mei (Modena, IT)
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Incorporating machine learning into ICD remote monitoring: risk assessment for sustained ventricular arrhythmia after an isolated non-sustained ventricular tachycardia alert.
Doctor R. Campbell (London, GB)
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The rise of the machines: digital technology for device therapy
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The Event

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ESC Congress 2025

31 August 2025 16:33 CET
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ESC 365 is supported by

novartis Explore sponsored resources
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