Multi-level semantic fusion network for Chinese medical named entity recognition-Reference-Cited by-同舟云学术

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Multi-level semantic fusion network for Chinese medical named entity recognition

Published:2022-09 Issue: Volume:133 Page:104144
ISSN:1532-0464
Container-title:Journal of Biomedical Informatics
language:en
Short-container-title:Journal of Biomedical Informatics

Author:

Shi Jintong,Sun Mengxuan,Sun Zhengya,Li Mingda,Gu Yifan,Zhang Wensheng

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Publisher

Elsevier BV

Subject

Health Informatics,Computer Science Applications

Reference42 articles.

1. Guillaume Lample, Miguel Ballesteros, Sandeep Subramanian, Kazuya Kawakami, Chris Dyer, Neural architectures for named entity recognition, in: Conference of the North American Chapter of the Association for Computational Linguistics (HLT-NAACL), 2016, pp. 260–270.

2. Dianbo Sui, Yubo Chen, Kang Liu, Jun Zhao, Shengping Liu, Leverage lexical knowledge for Chinese named entity recognition via collaborative graph network, in: Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), 2019, pp. 3830–3840.

3. Chen Jia, Yuefeng Shi, Qinrong Yang, Yue Zhang, Entity enhanced BERT pre-training for Chinese NER, in: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), 2020, pp. 6384–6396.

4. Cross domains adversarial learning for Chinese named entity recognition for online medical consultation;Wen;J. Biomed. Inform.,2020

5. Chinese medical named entity recognition based on multi-granularity semantic dictionary and multimodal tree;Wang;J. Biomed. Inform.,2020

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