Classification of 12-lead ECGs: the PhysioNet/Computing in Cardiology Challenge 2020
Matthew A. Reyna, Erick Andres Perez Alday, Annie Gu, Chengyu Liu, Salman Seyedi, Ali Bahrami Rad, Andoni Elola, Qiao Li, Ashish Sharma, Gari D. Clifford
Abstract
The PhysioNet/Computing in Cardiology Challenge 2020 focused on the identification of cardiac abnormalities in 12-lead electrocardiogram (ECG) recordings. A total of 66,361 recordings with clinical diagnoses were sourced from five hospital systems in four countries. We shared 43,101 annotated recordings publicly and withheld the remaining recordings for validation and testing.
Topics & Concepts
Computer scienceLead (geology)Internal medicineCardiologyMedicineGeologyGeomorphologyECG Monitoring and AnalysisPhonocardiography and Auscultation TechniquesCardiac electrophysiology and arrhythmias