Cited By
View all- Yu JFeng ZLi JQin YJiang Y(2024)CGCL: A Novel Collaborative Graph Contrastive Learning Network for Chinese NERKnowledge Science, Engineering and Management10.1007/978-981-97-5501-1_13(163-175)Online publication date: 27-Jul-2024
A Survey on Deep Learning for Chinese Medical Named Entity Recognition
Pages 472 - 476
Abstract
At present, how to make full use of medical and health data for exploration and analysis to better support clinical decision-making faces many challenges. This paper aims to summarize and analyze the methods and research status of Chinese medical named entity recognition, and understand the research progress of named entity recognition technology in Chinese electronic medical record text. This paper conducts literature research from multiple perspectives, such as the basic concepts of electronic medical records and named entity recognition, the acquisition of corpus datasets and the named entity recognition algorithm. The research progress of Chinese electronic medical record named entity recognition in recent years is reviewed, and the development trend of electronic medical record named entity recognition in the future Chinese is analyzed.
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Index Terms
- A Survey on Deep Learning for Chinese Medical Named Entity Recognition
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Published In
March 2023
824 pages
ISBN:9781450399029
DOI:10.1145/3594315
Copyright © 2023 ACM.
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 02 August 2023
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- Research-article
- Research
- Refereed limited
Funding Sources
- China University Industry University Research Innovation Fund
- Fujian Province Young and Middle-aged Teacher Education Research Project
- Fujian Province Social Science Foundation Project
- Natural Science Foundation of Fujian Province
Conference
ICCAI 2023
ICCAI 2023: 2023 9th International Conference on Computing and Artificial Intelligence
March 17 - 20, 2023
Tianjin, China
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Cited By
View all- Yu JFeng ZLi JQin YJiang Y(2024)CGCL: A Novel Collaborative Graph Contrastive Learning Network for Chinese NERKnowledge Science, Engineering and Management10.1007/978-981-97-5501-1_13(163-175)Online publication date: 27-Jul-2024
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