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

Session: The rise of the machines: digital technology for device therapy
Topic: Home and Remote Patient Monitoring
Speaker: Doctor A. Askarinejad (Liverpool, GB)
Event: ESC Congress 2025

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Doctor Amir Askarinejad

Liverpool (United Kingdom of Great Britain & Northern Ireland)
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3 more presentations in this session

Ultra-high-frequency ECG outperforms strauss criteria for diagnosing true left bundle branch block in candidates of cardiac resynchronization therapy

Speaker: 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

Speaker: 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.

Speaker: Doctor R. Campbell (London, GB)

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The rise of the machines: digital technology for device therapy

Speakers: Doctor A. Askarinejad, Doctor K. Curila, Doctor D. Mei, Doctor R. Campbell
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About the event

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ESC Congress 2025

29 August - 1 September 2025

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