Computing in cardiology · 2020 · 66 citations · 14 references
MedicineBiomedical EngineeringCardiologyBiomedical Signal ProcessingElectrophysiologyMachine LearningCardiac AssessmentCardiac Signal ProcessingElectrocardiogram AnalysisElectrocardiogram InterpretationElectrocardiographyIntracardiac Electrophysiology12-Lead ElectrocardiographyArrhythmia DetectionArrhythmia RecognitionAutomated Ecg InterpretationComputer-aided Electrocardiogram InterpretationEcg Anomaly DetectionMulti-institutional CollaborationTraining
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.
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PhysioBank, PhysioToolkit, and PhysioNet
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