Contextual Word Embedding for Biomedical Knowledge Extraction: a Rapid Review and Case Study
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Computer Science Applications,Health Informatics,Information Systems
Link
https://link.springer.com/content/pdf/10.1007/s41666-023-00157-y.pdf
Reference32 articles.
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2. Khurana D, Koli A, Khatter K, Singh S (2022) Natural language processing: state of the art, current trends and challenges. Multimedia Tools Appl. https://doi.org/10.1007/s11042-022-13428-4
3. Naseem U, Musial K, Eklund P, Prasad M (2020) Biomedical named-entity recognition by hierarchically fusing BioBERT representations and deep contextual-level word-embedding. Int Joint Conf Neural Netw (IJCNN) 1–8. https://doi.org/10.1109/IJCNN48605.2020.9206808
4. Aubaid AM, Mishra A (2020) A rule-based approach to embedding techniques for text document classification. Appl Sci 10(11):4009. https://doi.org/10.3390/app10114009
5. Zhang L, Tan J, Han D, Zhu H (2017) From machine learning to deep learning: progress in machine intelligence for rational drug discovery. Drug Discov Today 1680–1685. https://doi.org/10.1016/j.drudis.2017.08.010
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