Data

ECG Arrhythmia Dataset for Cardiovascular Disease Detection

Central Queensland University

Melvin Yashnil Ramkhelawan (Aggregated by)

Viewed: [[ro.stat.viewed]] Cited: [[ro.stat.cited]] Accessed: [[ro.stat.accessed]]

ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.25946/32249334.v1&rft.title=ECG Arrhythmia Dataset for Cardiovascular Disease Detection&rft.identifier=10.25946/32249334.v1&rft.publisher=Central Queensland University&rft.description=The ECG image data were prepared from the MIT-BIH Arrhythmia Database and the PTB Diagnostic ECG Database. These datasets provide ECG recordings associated with normal and abnormal cardiac conditions. ECG recordings were converted into ECG images and organised into a six-class arrhythmia classification dataset comprising 123,998 images.&rft.creator=Melvin Yashnil Ramkhelawan&rft.date=2026&rft_rights= https://creativecommons.org/licenses/by-sa/4.0/&rft_subject=Artificial intelligence not elsewhere classified&rft_subject=Neural networks&rft_subject=Health systems&rft_subject=Preventative health care&rft_subject=quantum machine learning&rft_subject=cardiovascular disease&rft_subject=healthcare&rft_subject=early detection&rft_subject=predictive analytics&rft_subject=ECG&rft_subject=Artificial intelligence (AI)&rft.type=dataset&rft.language=English Access the data

Access data via landing page
https://doi.org/10.259...

Cite Saved to MyRDA Save to MyRDA

Licence & Rights:

Other view details

Cc By-sa 4.0

https://creativecommons.org/licenses/by-sa/4.0/

Access:

Open

Full description

The ECG image data were prepared from the MIT-BIH Arrhythmia Database and the PTB Diagnostic ECG Database. These datasets provide ECG recordings associated with normal and abnormal cardiac conditions. ECG recordings were converted into ECG images and organised into a six-class arrhythmia classification dataset comprising 123,998 images.

This dataset is part of a larger collection

Click to explore relationships graph

Subjects

User Contributed Tags

Identifiers

DOI : 10.25946/32249334.V1