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

1 September 2025 (14:15 - 15:00)

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About the speaker

Doctor Elnaz Shahmohamadi

University of Adelaide, Adelaide (Australia)

7 More presentations in this session

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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

Doctor T. Uchida (Hofu, JP)

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A first step towards proactive atrial fibrillation management using ai prediction in a 10-120 minute window

Professor H. Wang (Shenyang, CN)

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

Doctor M. Khan (Stockholm, SE)

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

Doctor A. Sharp (Oxford, GB)

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

Doctor M. Haris (Leeds, GB)

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Atrial fibrillation and artificial intelligence: the winning couple

The Event

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ESC Congress 2025

1 September 2025 14:15 CET

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ESC 365 is supported by

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