GAN-based novel feature selection approach with hybrid deep learning for heartbeat classification from ECG signal.

Haseena Beegum S, Manju R

Open source

DOI
10.1016/j.compbiolchem.2025.108704
Published
2026 Feb
Container
Computational biology and chemistry
Publisher
Not recorded
Open access
no

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BibTeX

@article{allodium:10.1016/j.compbiolchem.2025.108704,
  title = {GAN-based novel feature selection approach with hybrid deep learning for heartbeat classification from ECG signal.},
  author = {Haseena Beegum S and Manju R},
  year = {2026},
  journal = {Computational biology and chemistry},
  doi = {10.1016/j.compbiolchem.2025.108704},
  url = {https://doi.org/10.1016/j.compbiolchem.2025.108704}
}

RIS

TY  - JOUR
TI  - GAN-based novel feature selection approach with hybrid deep learning for heartbeat classification from ECG signal.
AU  - Haseena Beegum S
AU  - Manju R
PY  - 2026
JO  - Computational biology and chemistry
DO  - 10.1016/j.compbiolchem.2025.108704
UR  - https://doi.org/10.1016/j.compbiolchem.2025.108704
ER  -

APA

S, H. B., & R, M. (2026). GAN-based novel feature selection approach with hybrid deep learning for heartbeat classification from ECG signal.. Computational biology and chemistry. https://doi.org/10.1016/j.compbiolchem.2025.108704

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