Proceedings of the 3rd International Conference on Internet, Education and Information Technology (IEIT 2023)

Visualization Analysis of Current Situation and Trend of TCM Electronic Medical Records Research Based on CiteSpace

Authors
Gang Zhang1, Shuanggui Tian1, *, Ling Lin1
1Hubei University of Chinese Medicine, Wuhan, China
*Corresponding author. Email: sunnytian610@hbtcm.edu.cn
Corresponding Author
Shuanggui Tian
Available Online 4 September 2023.
DOI
10.2991/978-94-6463-230-9_8How to use a DOI?
Keywords
Electronic medical record of TCM; Visual analysis; CiteSpace; research hotspot
Abstract

To explore the research status, hot spots and frontier trends in the field of electronic medical record of traditional Chinese medicine (TCM), and to provide reference for related researchers. Methods: The literatures related to TCM electronic medical records from January 1, 2014 to December 31, 2021 were retrieved from CNKI, Chongqing VIP, Wanfang and Web of Science databases. CiteSpace5.8 and other software were used to visually analyze the number of publications, publishing institutions, authors and keywords of the included literatures in each year. Results: A total of 431 valid Chinese literatures and 49 English literatures were included. The number of published literatures showed a steady upward trend. The key words of 0.1 are “data mining”, “big data”, “traditional Chinese medicine hall”, “curative effect evaluation”, etc., intermediary centrality of English literature & GT; 0.1 included “Traditional Chinese Medicine”, “epidemiology”, “diagnosis” and “cohort study”. The analysis found seven clusters of Chinese keywords and nine clusters of English keywords. Conclusions: In recent years, the field of electronic medical records of traditional Chinese medicine at home and abroad has attracted increasing attention. The research hotspot has gradually shifted from the basic research of standardization of electronic medical records and the construction of information system to the optimization, design and application of data mining algorithm model based on electronic medical records of traditional Chinese medicine. The application research of extracting tacit knowledge, summarizing medication rules, and constructing intelligent auxiliary system of traditional Chinese medicine with functions of auxiliary clinical prediction, diagnosis, treatment, evaluation, etc.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 3rd International Conference on Internet, Education and Information Technology (IEIT 2023)
Series
Atlantis Highlights in Social Sciences, Education and Humanities
Publication Date
4 September 2023
ISBN
978-94-6463-230-9
ISSN
2667-128X
DOI
10.2991/978-94-6463-230-9_8How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - Gang Zhang
AU  - Shuanggui Tian
AU  - Ling Lin
PY  - 2023
DA  - 2023/09/04
TI  - Visualization Analysis of Current Situation and Trend of TCM Electronic Medical Records Research Based on CiteSpace
BT  - Proceedings of the 3rd International Conference on Internet, Education and Information Technology (IEIT 2023)
PB  - Atlantis Press
SP  - 57
EP  - 68
SN  - 2667-128X
UR  - https://doi.org/10.2991/978-94-6463-230-9_8
DO  - 10.2991/978-94-6463-230-9_8
ID  - Zhang2023
ER  -