Test dataset for: Automatic multi-label ECG diagnosis of impulse or conduction abnormalities in patients with deep learning algorithm: a cohort study

Published: 22 February 2020| Version 1 | DOI: 10.17632/6jd4rn2z9x.1
Ye Yuan,


This test dataset comprised of 828 ECGs, where patients were not included in the training/validation set and each patient only contributed one ECG trace to prevent the overlapping of patients, is constructed to correspond to the training/validation set of this paper. Three board-certified actively-practicing cardiologists, including one board-certified actively-practicing cardiac electrophysiologist, annotated ECGs in this test dataset. Cardiologist committees discussed the records and annotated by consensus, providing an expert standard for model evaluation. The data included standard 10-second, 12-lead ECGs recorded at a sampling rate of 500 Hz using GE-Marquette type 3500 or 5500 ECG machine (General Electrical company, Marquette, WI, USA), 24-hour dynamic 12-lead ECGs recorded by a Holter machine (DMS Holter Company, California, USA), or Electrophysiological monitor (Dong Fang Company, Shanghai, China, only offending ECG data of PSVT). The raw data were stored using the MUSE data management system. The ECGs were classified into 21 specific class rhythms including: normal (N), Sinus Tachycardia (ST), Sinus Bradycardia (SB), Premature Atria contraction (PAC), Atrial Rhythm (AR), Atrial tachycardia (AT), Atrial Flutter (AFlutter), Atrial Fibrillation (AFib), Premature Junctional Contraction (PJC), Junctional Rhythm (JR), Paroxysmal supraventricular tachycardia (PSVT), Premature Ventricular Contraction (PVC), Idioventricular Rhythm (IVR), Ventricular Tachycardia (VT), Artificial Atrial pacing Rhythm (AAPR), Artificial Ventricular pacing Rhythm (AVPR), Left bundle branch block (LBBB), First-degree atrial-ventricular Block (1st Deg AVB), Mobitz I second-degree atrial-ventricular Block (Mobitz I AVB), Wolff-Parkinson-White Syndrome type A (WPW-A) and Wolff-Parkinson-White Syndrome type B (WPW-B)