PTB-XL+, a comprehensive electrocardiographic feature dataset.

ABSTRACT: Machine learning (ML) methods for the analysis of electrocardiography (ECG) data are gaining importance, substantially supported by the release of large public datasets. However, these current datasets miss important derived descriptors such as ECG features that have been devised in the past hundred years and still form the basis of most automatic ECG analysis algorithms and are critical for cardiologists' decision processes. ECG features are available from sophisticated commercial software but are not accessible to the general public. To alleviate this issue, we add ECG features from two leading commercial algorithms and an open-source implementation supplemented by a set of automatic diagnostic statements from a commercial ECG analysis software in preprocessed format. This allows the com

SUBMITTER: Strodthoff N 

PROVIDER: S-EPMC10183020 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature