数字中医药（英文）2022，Vol.5Issue(1)：93-102,10.DOI:10.1016/j.dcmed.2022.03.010
基于文献计量学的《傅青主女科》研究现状可视化分析
Visualization analysis of the research status of FU Qingzhu's Obstetrics and Gynecology based on bibliometrics
摘要
Abstract
Objective This study examined the research status and development process of FU Qingzhu's Obstetrics and Gynecology (Fu Qing Zhu Nv Ke,《傅青主女科》, FQZNK) in the past 40 years with bibliometrics and visual analysis.Methods Retrieved all related literature in the research field of FQZNK from the domestic and foreign databases: China National Knowledge Infrastructure (CNKI), China Science and Technology Journal Database (VIP), Wanfang Database, and Web of Science (WOS) core database, including Science Citation Index Expanded (SCIE), Social Sciences Citation Index (SSCI), and Arts & Humanities Citation Index (A&HCI). The search range was from January 1, 1980 to March 10, 2021. In addition, bibliometrics and CiteSpace 5.7.R2 software were used to analyze literature types, published journals, cited literature, the number of author publica-tions, co-author networks, co-institution networks, keyword co-occurrence networks, keyword clusters, and keyword bursts. Results A total of 678 valid records were included in the final dataset. Literature types, high publication journals, highly cited literature, high-yield institutions, high-yield research teams, and high-productivity scholars in this research field were found through bibliometrics. Liter-ature types can be divided into four categories, among which 451 are theoretical studies on academic thoughts of FQZNK, accounting for 66.5％ of the included journals. The Journal of Shanxi Traditional Chinese Medicine had the largest volume of published articles (61), ac-counting for 9.0％ of the total number of the included journals. The most cited literature was ZHOU Mingxin's article "Using the quantitative method to discuss author's authenticity and formula characteristics of FU Qingzhu's Obstetrics and Gynecology", which was cited 94 times. Hunan University of Chinese Medicine, the institution with the most publications, published 45 articles, and YOU Zhaoling, the most published author, published 33 articles. Moreover, it was found that most high-yield researchers came from high-yield institutions and that Hun-an University of Chinese Medicine had the most research on FQZNK. Keyword co-occur-rence analysis revealed that the keyword "FQZNK" had the highest frequency (597 times) and the highest centrality (1.00). Keyword cluster analysis used the Log-Likelihood Ratio (LLR) al-gorithm to form eleven important clusters:#0 treatment aiming at its root causes, #1 gynecopathy, #2 Siwu Decoction (四物汤), #3 FU Qingzhu, #4 post-partum, #5 infertility, #6 dysmenorrhea, #7 sterility, #8 coordinate the heart and kidney, #9 Danggui Buxue Decoction (当归补血汤), and #10 treatment. It was found that the prescriptions of FQZNK were studied mainly before 2000, the theoretical studies were mainly conducted before 2010, and its clinic-al application was mainly explored from 2010 until now. Diseases such as dysmenorrhea, morbid vaginal discharge, infertility, metrorrhagia, and polycystic ovarian syndrome (PCOS) have recently become popular topics in this field.Conclusion The current study provides more scientific, accurate, and comprehensive sci-entific support for further research and development of traditional Chinese medicine (TCM) in FQZNK. With this foundation, people can use burst detection to ascertain the current hot-spots in research, get their development trends, and forecast future research directions. In ad-dition, infertility, morbid vaginal discharge, flooding, and PCOS treatments based on TCM syndrome differentiation are currently popular research topics for FQZNK.关键词
《傅青主女科》/科学知识图谱/可视化分析/文献计量学/CiteSpace/妇科病/不孕症Key words
FU Qingzhu's Obstetrics and Gynecology (Fu Qing Zhu Nv Ke,《傅青主女科》)/Scientific knowledge graph/Visualization analysis/Bibliometrics/CiteSpace/Gynecopathy/Infertility引用本文复制引用
田赛男,彭清华,陈亦男,兰聪颖,晏峻峰..基于文献计量学的《傅青主女科》研究现状可视化分析[J].数字中医药（英文）,2022,5(1):93-102,10.基金项目
National Key R&D Program of China?Science and Tech-nology Innovation 2030?"New Generation of Artificial Intelligence"Major Project(2018AAA0102100),Post-graduate Research Innovation Project of Hunan Province(CX2018B465),and 2011 Digital Chinese Medicine Innov-ation Research Platform of Hunan Digital Chinese Medi-cine Collaborative Innovation Center. （2018AAA0102100）
