ESC 365 - Topological Data Analysis for Patient Stratification and Stroke Risk in Atrial Fibrillation

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

Session: Atrial fibrillation and artificial intelligence: the winning couple

Topic: Stroke in Atrial Fibrillation

Speaker: Doctor E. Shahmohamadi (Adelaide, AU)

Event: ESC Congress 2025

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Doctor Elnaz Shahmohamadi

University of Adelaide, Adelaide (Australia)

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7 more presentations in this session

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

Speaker: Doctor T. Uchida (Hofu, JP)

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

Speaker: Professor H. Wang (Shenyang, CN)

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

Speaker: Doctor M. Khan (Stockholm, SE)

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

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ESC Congress 2025

29 August - 1 September 2025

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