health life sciences medicine
Interpretation of Electrocardiograms (ECG) is increasingly complemented by algorithms. These algorithms are based on large datasets. This ECG database consists of children and adults with congenital heart defects (CHD) including many arrhythmia annotations. This dataset, notable for its manual annotations and inclusion of intracardiac electrograms alongside traditional 12-lead ECGs, offers 1075.85 minutes of recordings (in total 113924 annotated beats) that capture various cardiac rhythms and arrhythmias such as supraventricular tachycardia and ventricular tachycardia. The data were meticulously collected from patients undergoing electrophysiological studies, with subsequent annotations by expert reviewers using the LightWAVE® software. The significance of this database lies in its focus on pediatric arrhythmias and arrhythmias of patients with congenital heart defect areas currently underrepresented in existing datasets, which predominantly feature adult pathologies. This resource aims to enhance algorithmic development for ECG interpretation, leveraging machine learning to improve diagnosis and treatment outcomes in these sensitive groups. The dataset not only serves as a critical tool for developing precision medicine but also sets a precedent for future expansions to include a broader spectrum of congenital heart defects conditions, thereby supporting the evolution of cardiac care through advanced computational techniques.
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Open Data Commons Attribution License v1.0
https://doi.org/10.13026/7a4j-vn37
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Leipzig Heart Center ECG-Database: Arrhythmias in Children and Patients with Congenital Heart Disease was accessed on DATE from https://registry.opendata.aws/leipzig-heart-center-ecg.
arn:aws:s3:::physionet-open/leipzig-heart-center-ecg/us-east-1aws s3 ls --no-sign-request s3://physionet-open/leipzig-heart-center-ecg/