Natural language processing and its application in the medical field_Chinese Journal of Evidence-Based Medicine

Authors：

HU Jiayuan ¹ , QIU Ruijin ² , SUN Yang ² ,  SHANG Hongcai ²

1. Beijing Hospital of Traditional Chinese Medicine Affiliated to Capital Medical University, Beijing 100010, P. R. China;
2. Key Laboratory of Chinese Internal Medicine of Ministry of Education, Dongzhimen Hospital, Beijing University of Chinese Medicine, Beijing 100700, P. R. China;

Corresponding author：

SHANG Hongcai, Email: shanghongcai@126.com

Keywords：

Natural language processing; Medicine information; Traditional Chinese medicine

DOI：

10.7507/1672-2531.202311178

Video：

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Natural language processing (NLP) is the embodiment of computer intelligence in acquiring knowledge, understanding, processing and expressing consciously and actively. It is the scientific key to promoting the informatization of medical practice and research. This paper reviews the development history and research basis of NLP, and focuses on the current application of NLP and large language models in biomedicine and traditional Chinese medicine (TCM), including the intelligent reading, information extraction and feedback of medical texts and ancient books of TCM, as well as the construction of medical knowledge graph and question-answering system. NLP is the technical support to explore the treasure house of TCM, which is of great practical significance to further promote the development of efficient and high-quality core values of TCM and to improve the service capacity.

Citation： HU Jiayuan, QIU Ruijin, SUN Yang, SHANG Hongcai. Natural language processing and its application in the medical field. Chinese Journal of Evidence-Based Medicine, 2024, 24(10): 1205-1211. doi: 10.7507/1672-2531.202311178 Copy

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2. 冯志伟. 自然语言处理的历史与现状. 中国外语, 2008, (1): 14-22.
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6. 王大鹏. 国内语料库发展现存问题与分析. 渤海大学学报(哲学社会科学版), 2010, 32(3): 137-140.
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44. 聂莉莉, 李传富, 许晓倩, 等. 人工智能在医学诊断知识图谱构建中的应用研究. 医学信息学杂志, 2018, 39(6): 7-12.
45. 赵雪娇. 妇产科知识图谱构建研究与实现. 中国数字医学, 2019, 14(1): 3-5.
46. 张小亮, 王忠民, 王永庆, 等. 基于自然语言处理的临床合理用药知识图谱构建. 中华医学图书情报杂志, 2019, 28(9): 1-5.
47. 王琦, 康亮环, 刘国臻. 基于临床知识图谱的慢性肾病辅助决策模型研究. 邮电设计技术, 2018, (12): 68-71.
48. 黄梦禧, 张青川, 陈龙, 等. 面向医学领域的智能问答APP设计与实现. 软件导刊, 2019, 18(3): 94-99.
49. Demner-Fushman D, Mrabet Y, Ben Abacha A. Consumer health information and question answering: helping consumers find answers to their health-related information needs. J Am Med Inform Assoc, 2020, 27(2): 194-201.
50. Legrand J, Gogdemir R, Bousquet C, et al. PGxCorpus, a manually annotated corpus for pharmacogenomics. Sci Data, 2020, 7(1): 3.
51. Kang MJ, Dykes PC, Korach TZ, et al. Identifying nurses' concern concepts about patient deterioration using a standard nursing terminology. Int J Med Inform, 2020, 133: 104016.
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Chinese Journal of Evidence-Based Medicine

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