Incidence and severity of aortic stenosis according to machine learning predicted risk of atrial fibrillation

Younis, A., Larvin, H., Kazi, K. et al. (10 more authors) (Accepted: 2025) Incidence and severity of aortic stenosis according to machine learning predicted risk of atrial fibrillation. Scientific Reports. ISSN: 2045-2322 (In Press)

Metadata

Item Type: Article
Authors/Creators:
Dates:
  • Accepted: 11 September 2025
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds)
Funding Information:
Funder
Grant number
British Heart Foundation Accounts Payable - Gloria Sankey
FS/20/12/34789
Depositing User: Symplectic Publications
Date Deposited: 17 Sep 2025 12:25
Last Modified: 17 Sep 2025 12:25
Status: In Press
Publisher: Nature Research
Open Archives Initiative ID (OAI ID):

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