An End-to-End Cardiac Arrhythmia Recognition Method with an Effective DenseNet Model on Imbalanced Datasets Using ECG Signal.
- DOI
- 10.1155/2022/9475162
- Published
- 2022
- Container
- Computational intelligence and neuroscience
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1155/2022/9475162,
title = {An End-to-End Cardiac Arrhythmia Recognition Method with an Effective DenseNet Model on Imbalanced Datasets Using ECG Signal.},
author = {Ullah H and Bin Heyat MB and Akhtar F and Sumbul and Muaad AY and Islam MS and Abbas Z and Pan T and Gao M and Lin Y and Lai D},
year = {2022},
journal = {Computational intelligence and neuroscience},
doi = {10.1155/2022/9475162},
url = {https://doi.org/10.1155/2022/9475162}
}RIS
TY - JOUR TI - An End-to-End Cardiac Arrhythmia Recognition Method with an Effective DenseNet Model on Imbalanced Datasets Using ECG Signal. AU - Ullah H AU - Bin Heyat MB AU - Akhtar F AU - Sumbul AU - Muaad AY AU - Islam MS AU - Abbas Z AU - Pan T AU - Gao M AU - Lin Y AU - Lai D PY - 2022 JO - Computational intelligence and neuroscience DO - 10.1155/2022/9475162 UR - https://doi.org/10.1155/2022/9475162 ER -
APA
H, U., MB, B. H., F, A., Sumbul, AY, M., MS, I., Z, A., T, P., M, G., Y, L., & D, L. (2022). An End-to-End Cardiac Arrhythmia Recognition Method with an Effective DenseNet Model on Imbalanced Datasets Using ECG Signal.. Computational intelligence and neuroscience. https://doi.org/10.1155/2022/9475162
Source records
- pubmed · retrieved 2026-09-26T19:12:02.638Z