Improving Medical Short Text Classification with Semantic Expansion Using Word-Cluster Embedding

Automatic text classification (TC) research can be used for real-world problems such as the classification of in-patient discharge summaries and medical text reports, which is beneficial to make medical documents more understandable to doctors.

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Cite this as

Ying Shen, Qiang Zhang, Jin Zhang, Jiyue Huang, Yuming Lu, Kai Lei (2024). Dataset: Improving Medical Short Text Classification with Semantic Expansion Using Word-Cluster Embedding. https://doi.org/10.57702/dce9da94

DOI retrieved: December 16, 2024

Additional Info

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Created December 16, 2024
Last update December 16, 2024
Defined In https://doi.org/10.48550/arXiv.1812.01885
Author Ying Shen
More Authors
Qiang Zhang
Jin Zhang
Jiyue Huang
Yuming Lu
Kai Lei
Homepage https://arxiv.org/abs/1806.08630