Enhanced detection of atrial fibrillation in single-lead electrocardiograms using a Cloud-based artificial intelligence platform
The result of this external validation indicates that the AI platform can match cardiologist-level accuracy in AF detection from 1-lead ECGs. Such tools are promising for AF screening and have the potential to improve accuracy in noncardiology expert health care professional interpretation and trigger further tests for effective patient management.
Authors
- Carlos Lizcano
- Raquel Toribio‐Fernández (ORCID: https://orcid.org/0000-0003-3626-7922)
- José María Lillo-Castellano
- Manuel Marina‐Breysse (ORCID: https://orcid.org/0000-0002-2047-1868)
- Michiel Rienstra (ORCID: https://orcid.org/0000-0002-2581-070X)
- David Jiménez-Virumbrales
- Daniel Corrochano-Diego
- François De Guio (ORCID: https://orcid.org/0000-0003-1809-4175)
Institutions
- University Medical Center Groningen (NL)
- University of Groningen (NL)
- Centro de Investigación en Red en Enfermedades Cardiovasculares (ES)
- Hospital La Paz Institute for Health Research (ES)
- Centro de Investigación Biomédica en Red (ES)
- Spanish National Centre for Cardiovascular Research (ES)
- Hospital Universitario del Henares (ES)
Publication Details
- Journal
- Heart Rhythm
- Published
- 2025-01-10
- DOI
- https://doi.org/10.1016/j.hrthm.2024.12.048
- Citations
- 5
- Primary Topic
- ECG Monitoring and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 6.94
Funders
- Horizon 2020 Framework Programme
- H2020 European Research Council