Difference of Precision in Atrial Fibrillation Prediction by Convolutional Neural Network Model Using Sinus Rhythm Electrocardiogram According to Risk Profiles
Background: Artificial intelligence–enhanced electrocardiograms (AI-ECGs) can identify atrial fibrillation (AF) from sinus-rhythm ECGs, but a positive result is not always immediately confirmed. We evaluated AI-ECG performance in subgroups with different pretest probabilities of AF.
Authors
- Takayuki Otsuka (ORCID: https://orcid.org/0000-0002-8337-8572)
- Oikawa Yuji
- Takuto Arita (ORCID: https://orcid.org/0000-0002-5692-4769)
- Junji Yajima (ORCID: https://orcid.org/0000-0002-8380-8106)
- Takeshi Yamashita (ORCID: https://orcid.org/0000-0002-2544-8464)
- Naomi Hirota (ORCID: https://orcid.org/0000-0003-1184-4228)
- Jun Motogi
- Mikio Kishi
- Hiroto Kano
- Takuya Umemoto
- Naoharu Yagi (ORCID: https://orcid.org/0000-0001-7492-6373)
- Tokuhisa Uejima
- Shunsuke Matsuno
- Tsuneo Takayanagi
- Yuko Kato
- Shinya Suzuki
Institutions
- Nihon Kohden (Japan) (JP)
Publication Details
- Journal
- Circulation Reports
- Published
- 2026-11-06
- DOI
- https://doi.org/10.1253/circrep.cr-26-0299
- Primary Topic
- ECG Monitoring and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00