Abstract
In this paper, a survey is done to introduce the named entity recognition task in Chinese medical text and its practical significance. First, the existing datasets for the named entity recognition task of Chinese medical text are presented, then the survey is given on the algorithms for this task, mainly from the perspectives on matching and sequence labeling. Finally, the future development of named entity recognition in Chinese medical text is discussed.
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Acknowledgements
The authors would like to thank all anonymous reviewers for their constructive suggestions which have resulted in improvement on the presentations. This research is supported by the National Science Foundation of China (grant 61772278, author: Qu, W.; grant number: 61472191, author: Zhou, J. http://www.nsfc.gov.cn/), the National Social Science Foundation of China (grant number:18BYY127, author: Li B. http://www.cssn.cn) and Jiangsu Higher Institutions’ Excellent Innovative Team for Philosophy and Social Science (grant number: 2017STD006, author: Qu, W. http://jyt.jiangsu.gov.cn).
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Zhou, L., Qu, W., Wei, T., Zhou, J., Gu, Y., Li, B. (2021). A Review on Named Entity Recognition in Chinese Medical Text. In: Sun, X., Zhang, X., Xia, Z., Bertino, E. (eds) Advances in Artificial Intelligence and Security. ICAIS 2021. Communications in Computer and Information Science, vol 1422. Springer, Cham. https://doi.org/10.1007/978-3-030-78615-1_4
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