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PTB-XL, a large publicly available electrocardiography dataset

Open access
Wagner, Patrick, Strodthoff, Nils, Bousseljot, Ralf-Dieter, Kreiseler, Dieter, Lunze, Fatima I., Samek, Wojciech, Schaeffter, Tobias·2020·Scientific Data

Abstract

Electrocardiography (ECG) is a key non-invasive diagnostic tool for cardiovascular diseases which is increasingly supported by algorithms based on machine learning. Major obstacles for the development of automatic ECG interpretation algorithms are both the lack of public datasets and well-defined benchmarking procedures to allow comparison s of different algorithms. To address these issues, we put forward PTB-XL , the to-date largest freely accessible clinical 12-lead ECG-waveform dataset comprising 21837 records from 18885 patients of 10 seconds length. The ECG-waveform data was annotated by up to two cardiologists as a multi-label dataset, where diagnostic labels were further aggregated into super and subclasses. The dataset covers a broad range of diagnostic classes including, in particular, a large fraction of healthy records. The combination with additional metadata on demographics, additional diagnostic statements, diagnosis likelihoods, manually annotated signal properties as well as suggested folds for splitting training and test sets turns the dataset into a rich resource for the development and the evaluation of automatic ECG interpretation algorithms.

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Metadata

Authors
Wagner, P., Strodthoff, N., Bousseljot, R.-D., Kreiseler, D., Lunze, F. I., Samek, W., & Schaeffter, T.
Venue
Scientific Data
Published
2020-05-25
Volume
7
Issue
1
Pages
154-154
ISSN
2052-4463 (ISSN-L)
OpenAlex
W3027572331
Cited by
1,315
References
18
Type
data paper
Language
en
Open access
gold

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CoChat. (2026). Citation check: PTB-XL, a large publicly available electrocardiography dataset. https://app.cochat.ai/papers/10.1038/s41597-020-0495-6
The paper
Wagner, P., Strodthoff, N., Bousseljot, R.-D., Kreiseler, D., Lunze, F. I., Samek, W., & Schaeffter, T. (2020). PTB-XL, a large publicly available electrocardiography dataset. Scientific Data. https://doi.org/10.1038/s41597-020-0495-6

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