SHENG-NAN CHANGTseng, Yu-HengYu-HengTsengJIEN-JIUN CHENChiu, Fu-ChunFu-ChunChiuTsai, Chin-FengChin-FengTsaiJUEY-JEN HWANGYI-CHIH WANGCHIA-TI TSAI2023-05-312023-05-312022-12-140949-2321https://scholars.lib.ntu.edu.tw/handle/123456789/631559Ventricular premature complex (VPC) is a common arrhythmia in clinical practice. VPC could trigger ventricular tachycardia/fibrillation or VPC-induced cardiomyopathy in susceptible patients. Existing screening methods require prolonged monitoring and are limited by cost and low yield when the frequency of VPC is low. Twelve-lead electrocardiogram (ECG) is low cost and widely used. We aimed to identify patients with VPC during normal sinus rhythm (NSR) using artificial intelligence (AI) and machine learning-based ECG reading.en12-Lead electrocardiogram; Artificial intelligence; Convolutional neural network; Ventricular premature complexjournal article10.1186/s40001-022-00929-z365178412-s2.0-85143816580WOS:000899184300001