AI-based derivation of atrial fibrillation phenotypes in the general and critical care populations
This study was funded by the DECIPHER project (LJMU QR-PSF) and the EU project TARGET (10113624).
Authors
- Anil M. Tuladhar (ORCID: https://orcid.org/0000-0002-4815-2834)
- Ian Jones (ORCID: https://orcid.org/0000-0002-3081-0069)
- Iván Olier (ORCID: https://orcid.org/0000-0002-5679-7501)
- Robyn Lotto (ORCID: https://orcid.org/0000-0002-4305-0513)
- Gregory Y.H. Lip (ORCID: https://orcid.org/0000-0002-7566-1626)
- Ryan A. A. Bellfield (ORCID: https://orcid.org/0000-0002-9945-914X)
- Sandra Ortega‐Martorell (ORCID: https://orcid.org/0000-0001-9927-3209)
- Ellen A. Dawson (ORCID: https://orcid.org/0000-0002-5958-267X)
- Guowei Li (ORCID: https://orcid.org/0000-0002-1184-1791)
Institutions
- Radboud University Nijmegen (NL)
- University of Liverpool (GB)
- Radboud University Medical Center (NL)
- Liverpool Heart and Chest Hospital (GB)
- Liverpool John Moores University (GB)
- Aalborg University (DK)
Publication Details
- Journal
- EBioMedicine
- Published
- 2024-08-16
- DOI
- https://doi.org/10.1016/j.ebiom.2024.105280
- Citations
- 10
- Primary Topic
- Atrial Fibrillation Management and Outcomes
- Type
- article
- Field-Weighted Citation Impact
- 4.02
Funders
- Horizon Therapeutics
- European Commission
- Liverpool John Moores University
- HORIZON EUROPE Framework Programme