Enhancing Origin Prediction: Deep Learning Model for Diagnosing Premature Ventricular Contractions with Dual-Rhythm Analysis Focused on Cardiac Rotation.
Kazutaka NakasoneMakoto NishimoriMasakazu ShinoharaMitsuru TakamiKimitake ImamuraTaku NishidaAkira ShimaneYasushi OginosawaYuki NakamuraYasuteru YamauchiRyudo FujiwaraHiroyuki AsadaAkihiro YoshidaKaoru TakamiTomomi AkitaTakayuki NagaiPhilipp SommerMustapha El HamritiHiroshi ImadaLuigi PannoneAndrea SarkozyGian Battista ChierchiaCarlos De AsmundisKunihiko KiuchiKen-Ichi HirataKoji FukuzawaPublished in: Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology (2024)
Our deep learning-based model, incorporating both PVC and SR morphologies, resulted in a higher prediction accuracy for PVC origin. Considering SR is particularly important for predicting right-sided origin in patients with counterclockwise rotation.