Prediction of incident atrial fibrillation: A comprehensive evaluation of conventional and artificial intelligence-enhanced approaches
We present the first comprehensive evaluation of methodologies for predicting incident AF. Risk prediction with a model including AIRE-AF and CHARGE-AF resulted in similar performance to more complex models.
Authors
- James S. Ware (ORCID: https://orcid.org/0000-0002-6110-5880)
- Joseph Barker (ORCID: https://orcid.org/0000-0002-5483-9608)
- Konstantinos Patlatzoglou (ORCID: https://orcid.org/0000-0002-5888-8490)
- Libor Pastika (ORCID: https://orcid.org/0000-0001-6892-6553)
- Ewa Sieliwończyk (ORCID: https://orcid.org/0000-0002-8603-7044)
- Daniel B. Kramer (ORCID: https://orcid.org/0000-0003-4241-3586)
- Nicholas S. Peters (ORCID: https://orcid.org/0000-0002-1014-7052)
- Arunashis Sau (ORCID: https://orcid.org/0000-0002-0204-7078)
- Gul Rukh Khattak (ORCID: https://orcid.org/0000-0003-0674-2833)
- Fu Siong Ng (ORCID: https://orcid.org/0000-0002-8681-4368)
- Jonathan W. Waks (ORCID: https://orcid.org/0000-0001-5560-5638)
- Kathryn A. McGurk (ORCID: https://orcid.org/0000-0002-5445-6906)
- Boroumand Zeidaabadi (ORCID: https://orcid.org/0009-0004-0025-9896)
Institutions
- Beth Israel Deaconess Medical Center (US)
- Harvard University (US)
- Imperial College Healthcare NHS Trust (GB)
- Royal Brompton & Harefield NHS Foundation Trust (GB)
- Lung Institute (US)
- MRC London Institute of Medical Sciences (GB)
- Deaconess Hospital (US)
- Imperial College London (GB)
Publication Details
- Journal
- Heart Rhythm
- Published
- 2025-08-22
- DOI
- https://doi.org/10.1016/j.hrthm.2025.08.024
- Citations
- 5
- Primary Topic
- Atrial Fibrillation Management and Outcomes
- Type
- article
- Field-Weighted Citation Impact
- 6.94
Funders
- Pfizer
- National Institute for Health and Care Research
- British Heart Foundation
- Medical Research Council
- NIHR Imperial Biomedical Research Centre