Shinya Suzuki, Jun Motogi, Takuya Umemoto, Naomi Hirota, Hiroshi Nakai, Wataru Matsuzawa, Tsuneo Takayanagi, Akira Hyodo, Keiichi Satoh, Takuto Arita, Naoharu Yagi, Mikio Kishi, Hiroaki Semba, Hiroto Kano, Shunsuke Matsuno, Yuko Kato, Takayuki Otsuka, Takayuki Hori, Minoru Matsuhama, Mitsuru Iida, Tokuhisa Uejima, Yuji Oikawa, Junji Yajima, Takeshi Yamashita
Background: We developed a convolutional neural network (CNN) model to detect atrial fibrillation (AF) using the sinus rhythm ECG (SR-ECG). However, the diagnostic performance of the CNN model based on different ECG leads remains unclear. Methods and Results: In this retrospective analysis of a single-center, prospective cohort study, we identified 616 AF cases and 3,412 SR cases for the modeling dataset among new patients (n=19,170). The modeling dataset included SR-ECGs obtained within 31 days from AF-ECGs in AF cases and SR cases with follow-up ≥1,095 days...
March 8, 2024: Circulation reports