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Explainable machine learning models to improve prediction of incident stroke in atrial fibrillation patients using health records, medical imaging and ECG derived metrics

Congress Presentation

About the speaker

Mr Riccardo Cavarra

London (United Kingdom of Great Britain & Northern Ireland)
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6 more presentations in this session

Predicting postoperative atrial fibrillation after cardiac surgery using machine learning

Speaker: Doctor I. Kim (Seoul, KR)

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AI-driven voice analysis for early fluid overload detection in heart failure: preliminary results from the DHZC cohort of the VAMP-HF study

Speaker: Doctor L. Riehle (Berlin, DE)

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Machine learning modelling to predict heart failure readmission following emergency department presentation: a systems integration opportunity

Speaker: Doctor V. Goel (Melbourne, AU)

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Detection of heart failure with an artificial intelligence-enabled stethoscope in primary care: a multicentre prospective external validation study

Speaker: Doctor M. Kelshiker (London, GB)

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Machine-learning informed subtypes of heart failure and their palliative care trajectories: a population-based cohort study

Speaker: Professor A. Banerjee (London, GB)

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Artificial intelligence in action: implications for atrial fibrillation and heart failure

Speakers: Mr R. Cavarra, Doctor I. Kim, Doctor L. Riehle, Doctor V. Goel, Doctor M. Kelshiker...
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About the event

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ESC Congress 2025

29 August - 1 September 2025

Sessions Presentations