Prediction of atrial fibrillation admissions in arrhythmia naïve patients from structured electronic health record data
More domains of structured EHR improve the ability to predict incident AF admissions but structured EKG and Echo domains realize the most gain. Although ML models exhibited good discrimination, the precision is poor due to the low event rate.
Authors
- Salah S. Al‐Zaiti (ORCID: https://orcid.org/0000-0002-6862-0658)
- Tanmay Gokhale (ORCID: https://orcid.org/0000-0002-9436-2058)
- Floyd Thoma
- Nirav Bhatt (ORCID: https://orcid.org/0000-0001-9838-6180)
- Suresh Mulukutla (ORCID: https://orcid.org/0000-0001-5060-429X)
- Matthew R. Starr (ORCID: https://orcid.org/0000-0002-3021-5630)
- Samir Saba
- Raul G. Nogueira
- Murat Akçakaya
Institutions
- University of Pittsburgh (US)
- University of Pittsburgh Medical Center (US)
- University of Rochester (US)
Publication Details
- Journal
- BMC Medical Informatics and Decision Making
- Published
- 2025-09-29
- DOI
- https://doi.org/10.1186/s12911-025-03199-x
- Primary Topic
- Atrial Fibrillation Management and Outcomes
- Type
- article
- Field-Weighted Citation Impact
- 0.00