Improving clinical abbreviation sense disambiguation using attention-based Bi-LSTM and hybrid balancing techniques in imbalanced datasets.
- DOI
- 10.1111/jep.14041
- Published
- 2024 Oct
- Container
- Journal of evaluation in clinical practice
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1111/jep.14041,
title = {Improving clinical abbreviation sense disambiguation using attention-based Bi-LSTM and hybrid balancing techniques in imbalanced datasets.},
author = {Hosseini M and Rasekh AH and Keshavarzi A},
year = {2024},
journal = {Journal of evaluation in clinical practice},
doi = {10.1111/jep.14041},
url = {https://doi.org/10.1111/jep.14041}
}RIS
TY - JOUR TI - Improving clinical abbreviation sense disambiguation using attention-based Bi-LSTM and hybrid balancing techniques in imbalanced datasets. AU - Hosseini M AU - Rasekh AH AU - Keshavarzi A PY - 2024 JO - Journal of evaluation in clinical practice DO - 10.1111/jep.14041 UR - https://doi.org/10.1111/jep.14041 ER -
APA
M, H., AH, R., & A, K. (2024). Improving clinical abbreviation sense disambiguation using attention-based Bi-LSTM and hybrid balancing techniques in imbalanced datasets.. Journal of evaluation in clinical practice. https://doi.org/10.1111/jep.14041
Source records
- pubmed · retrieved 2026-11-10T09:01:51.792Z