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Predicting postoperative atrial fibrillation after cardiac surgery using machine learning

29 August 2025 (16:15 - 17:00)
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Congress Presentation Part of: Artificial intelligence in action: implications for atrial fibrillation and heart failure Machine Learning ESC Professional Premium Access ESC Congress 2025 European Society of Cardiology

About the speaker

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Doctor In Jung Kim

Seoul National University Hospital, Seoul (Korea (Republic of))

6 More presentations in this session

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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
Doctor L. Riehle (Berlin, DE)
Abstract Slides Video
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Machine learning modelling to predict heart failure readmission following emergency department presentation: a systems integration opportunity
Doctor V. Goel (Melbourne, AU)
Abstract Slides Video
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Detection of heart failure with an artificial intelligence-enabled stethoscope in primary care: a multicentre prospective external validation study
Doctor M. Kelshiker (London, GB)
Abstract Slides Video
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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
Mr R. Cavarra (London, GB)
Abstract Slides Video
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Machine-learning informed subtypes of heart failure and their palliative care trajectories: a population-based cohort study
Professor A. Banerjee (London, GB)
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Artificial intelligence in action: implications for atrial fibrillation and heart failure

The Event

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ESC Congress 2025

29 August 2025 16:15 CET
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novartis Explore sponsored resources