Hybrid feature engineering for resource-efficient Arrhythmia detection in electrocardiogram signals: An interpretable, separability-driven framework
- DOI
- 10.1016/j.compbiomed.2026.111933
- Published
- 2026-10
- Container
- Computers in Biology and Medicine
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.compbiomed.2026.111933,
title = {Hybrid feature engineering for resource-efficient Arrhythmia detection in electrocardiogram signals: An interpretable, separability-driven framework},
author = {Moirangthem Tiken Singh and Manibhushan Yaikhom and Rabinder Kumar Prasad},
year = {2026},
journal = {Computers in Biology and Medicine},
doi = {10.1016/j.compbiomed.2026.111933},
url = {https://doi.org/10.1016/j.compbiomed.2026.111933}
}RIS
TY - JOUR TI - Hybrid feature engineering for resource-efficient Arrhythmia detection in electrocardiogram signals: An interpretable, separability-driven framework AU - Moirangthem Tiken Singh AU - Manibhushan Yaikhom AU - Rabinder Kumar Prasad PY - 2026 JO - Computers in Biology and Medicine DO - 10.1016/j.compbiomed.2026.111933 UR - https://doi.org/10.1016/j.compbiomed.2026.111933 ER -
APA
Singh, M. T., Yaikhom, M., & Prasad, R. K. (2026). Hybrid feature engineering for resource-efficient Arrhythmia detection in electrocardiogram signals: An interpretable, separability-driven framework. Computers in Biology and Medicine. https://doi.org/10.1016/j.compbiomed.2026.111933
Source records
- crossref · retrieved 2026-09-26T02:46:44.052Z