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Enhancing the selection of heart failure patients for invasive procedures: how machine learning can predict the diagnostic yield of endomyocardial biopsy

30 August 2024 (09:50 - 10:00)
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Congress Presentation Part of: Get out your crystal ball: predicting heart failure events using models Invasive Haemodynamic Monitoring ESC Professional Premium Access ESC Congress 2024 European Society of Cardiology

About the speaker

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Doctor Christian Basile

Karolinska Institute, Stockholm (Sweden)

4 More presentations in this session

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Development and validation of a predicting model for risk of rehospitalization within 30 days in heart failure patients with preserved ejection fraction
Professor Y. Zhu (Xiangtan, CN)
Abstract Slides Video
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Machine learning to improve the performance of natriuretic peptides across age groups for the diagnosis of acute heart failure
Mr D. Perez Vicencio (Edinburgh, GB)
Abstract Slides Video
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High prevalence of cardiotropic viruses in endomyocardial biopsies from patients with inflammatory cardiomyopathy demonstrated by a novel targeted NGS approach
Doctor C. Baumeier (Berlin, DE)
Abstract Slides Video
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Predicting heart failure in cancer survivors: use of polygenic risk vs clinical score
Doctor C. Soh (Melbourne, AU)
Abstract Slides Video

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Get out your crystal ball: predicting heart failure events using models
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The Event

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ESC Congress 2024

30 August 2024 09:50 CET
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