Enhancing COVID-19 Classification Accuracy with a Hybrid SVM-LR Model.
- DOI
- 10.3390/bioengineering10111318
- Published
- 2023 Nov 15
- Container
- Bioengineering (Basel, Switzerland)
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.3390/bioengineering10111318,
title = {Enhancing COVID-19 Classification Accuracy with a Hybrid SVM-LR Model.},
author = {Nordin NI and Mustafa WA and Lola MS and Madi EN and Kamil AA and Nasution MD and K Abdul Hamid AA and Zainuddin NH and Aruchunan E and Abdullah MT},
year = {2023},
journal = {Bioengineering (Basel, Switzerland)},
doi = {10.3390/bioengineering10111318},
url = {https://doi.org/10.3390/bioengineering10111318}
}RIS
TY - JOUR TI - Enhancing COVID-19 Classification Accuracy with a Hybrid SVM-LR Model. AU - Nordin NI AU - Mustafa WA AU - Lola MS AU - Madi EN AU - Kamil AA AU - Nasution MD AU - K Abdul Hamid AA AU - Zainuddin NH AU - Aruchunan E AU - Abdullah MT PY - 2023 JO - Bioengineering (Basel, Switzerland) DO - 10.3390/bioengineering10111318 UR - https://doi.org/10.3390/bioengineering10111318 ER -
APA
NI, N., WA, M., MS, L., EN, M., AA, K., MD, N., AA, K. A. H., NH, Z., E, A., & MT, A. (2023). Enhancing COVID-19 Classification Accuracy with a Hybrid SVM-LR Model.. Bioengineering (Basel, Switzerland). https://doi.org/10.3390/bioengineering10111318
Source records
- pubmed · retrieved 2026-09-26T12:49:15.918Z