Prediction of atrial fibrillation over time using artificial intelligence based on ECG features and clinical risk factors

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Prediction of atrial fibrillation over time using artificial intelligence based on ECG features and clinical risk factors

Session: Atrial fibrillation and artificial intelligence: the winning couple

Topic: Diagnostic Methods

Speaker: Doctor M. Khan (Stockholm, SE)

Event: ESC Congress 2025

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Doctor Mashroor Khan

Karolinska University Hospital, Stockholm (Sweden)

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Prediction of long-term arrhythmic recurrence and major adverse cardiovascular events using machine learning in patients undergoing catheter ablation for atrial fibrillation: historical cohort study

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Topological Data Analysis for Patient Stratification and Stroke Risk in Atrial Fibrillation

Speaker: Doctor E. Shahmohamadi (Adelaide, AU)

Statistical shape and appearance modelling of atrial fibrillation: linking left atrial geometry and rotational propagation patterns

Speaker: Doctor A. Sharp (Oxford, GB)

Meta-machine learning for enhanced detection of atrial fibrillation after stroke: FIND-AFDAS

Speaker: Doctor M. Haris (Leeds, GB)

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Atrial fibrillation and artificial intelligence: the winning couple

Speakers: Doctor M. Khan, Doctor T. Uchida, Professor H. Wang, Doctor E. Shahmohamadi, Doctor A. Sharp...

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ESC Congress 2025

29 August - 1 September 2025

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