PTB-XL, a large publicly available electrocardiography dataset
By Patrick Wagner, Nils Strodthoff, R. Bousseljot, D. Kreiseler, F. Lunze, Wojciech Samek, Tobias Schaeffter. Scientific Data, 2020
1,521 citations recorded by the source corpus.
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. Measurement(s) electrocardiography • cardiovascular system Technology Type(s) 12 lead electrocardiography Factor Type(s) presence of co-occurring diseases Sample Characteristic - Organism Homo sapiens Measurement(s) electrocardiography • cardiovascular system Technology Type(s) 12 lead electrocardiography Factor Type(s) presence of co-occurring diseases Sample Characteristic - Organism Homo sapiens Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.12098055
Subfields: Cardiology and Cardiovascular Medicine, Cognitive Neuroscience, Pulmonary and Respiratory Medicine
View Paper: https://www.semanticscholar.org/paper/f4b5dfa199eecc0a60b82886b53472531fe6dfa9
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Cardiology and Cardiovascular Medicine
Citations in the corpus
- Classification of 12-lead ECGs: the PhysioNet/Computing in Cardiology Challenge 2020 (2020, methodology): “This source includes two public databases: the PTB Diagnostic ECG Database [2] and the PTB-XL [18], a large publicly available electrocardiography dataset.”
- Explainable Artificial Intelligence Applications in Cyber Security: State-of-the-Art in Research (2022, neutral): “[127] PTB-XL 2020 171 This 10-second-long 12-lead ECG-waveform dataset has 21837 records from 18885 patients.”
- ECGTwin: Personalized ECG Generation Using Controllable Diffusion Model (2025, unknown): “A detailed introduction to PTB-XL is provided in Appendix C. Notably, the most significant difference between the MIMIC-IV-ECG and PTB-XL datasets lies in the distribution and language of clinical text reports associated with each ECG record.”