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Deep learning in electronic health records to predict incident heart failure by modelling temporal dependencies of antecedent risk factors

17 May 2025 (08:00 - 12:45)
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Congress Presentation Part of: Artificial intelligence and diagnostic tools m-Health & Mobile Apps HFA Premium Access Heart Failure 2025 Heart Failure Association (HFA)

About the speaker

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Miss Sashi Kiran Mahapatra

University of Leeds, Leeds (United Kingdom of Great Britain & Northern Ireland)

5 More presentations in this session

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Evaluating a large language model's ability to recommend guideline-directed medical therapy for heart failure: a pilot study
Mr J. Valk (Enschede, NL)
Abstract Slides Video
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Stratification of patients with heart failure referred to cardiology at higher risk of 1-year heart failure admission or mortality by a machine learning algorithm
Professor J. Gonzalez Juanatey (Santiago de Compostela, ES)
Abstract Slides Video
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Using AI to identify left ventricular ejection fraction from the ECG
Associate Professor M. Ciccarelli (Salerno, IT)
Abstract Slides Video
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Pro-BNP variation as a risk marker of ventricular arrythmias in CRT patients
Doctor L. Sousa Azevedo (Vila Real, PT)
Abstract Slides Video
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Improvement of biomarkers is associated with improved patient quality-of-life measures after heart failure hospitalisation: a sub-study of the Medly-AID randomised controlled trial
Doctor D. Brahmbhatt (Toronto, CA)
Abstract Slides Video

Access the full session

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Artificial intelligence and diagnostic tools

The Event

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Heart Failure 2025

17 May - 20 May 2025
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ESC 365 is supported by

novartis Explore sponsored resources