Denoised ECGs from The PhysioNet/Computing in Cardiology Challenge 2020

Authors: Turbé, Hugues; Bjelogrlic, Mina; Namdar, Mehdi; Gaudet-Blavignac, Christophe; Zaghir, Jamil; Goldman, Jean-Philippe; Lokaj, Belinda; +1 Authors

doi: 10.5281/zenodo.6362421 , 10.5281/zenodo.6362422

Denoised ECGs from The PhysioNet/Computing in Cardiology Challenge 2020

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Abstract

This dataset is a denoised version of the CPSC dataset presented in Classification of 12-lead ECGs: The PhysioNet/Computing in Cardiology Challenge 20201. This dataset was used as part of the article A Lightweight and Interpretable Model to classify Bundle Branch Blocks from ECG Signals. 1)Perez Alday, E. A., Gu, A., Shah, A., Liu, C., Sharma, A., Seyedi, S., Bahrami Rad, A., Reyna, M., & Clifford, G. D. (2020). Classification of 12-lead ECGs: The PhysioNet/Computing in Cardiology Challenge 2020 (version 1.0.1). PhysioNet. https://doi.org/10.13026/f4ab-0814.

Related Organizations

University of Geneva
Switzerland
University Hospitals Geneva Medical Center
United States
University Hospitals of Cleveland
United States

Keywords

ECG

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