[关键词]
[摘要]
目的 基于CiteSpace工具,对中医药治疗肺癌的文献进行知识图谱可视化分析,探索中医药治疗肺癌的发展状况。方法 在中国知网中检索2009年-2018年中医药治疗肺癌的相关文献,应用CiteSpace3.9.R6软件对作者、机构、关键词绘制知识图谱并进行分析。结果 共纳入文献1050篇,近10年发文量较为稳定。研究学者440位,以徐振晔等为代表;研究机构为352家,以上海中医药大学附属龙华医院为代表;关键词为140个,频次最高的为非小细胞肺癌,聚类显示研究主要包括中医药治疗肺癌临床疗效观察、名老中医诊治肺癌规律分析、生物学机制研究及中西医结合治疗肺癌等方向。应用数据挖掘技术于该领域是目前研究主流,且持续性可观。结论 近10年我国中医药治疗肺癌领域正处于蓬勃发展时期,中医药治疗肺癌具有独特优势,通过图谱初步直观展现了该领域发展脉络、研究热点及前沿趋势,为科研人员提供研究方向。
[Key word]
[Abstract]
Objective To conduct a visualization analysis on the knowledge graph of traditional Chinese medicine (TCM) in treating lung cancer based on CiteSpace and explore the developments of TCM treatment for lung cancer.Methods Researches on TCM treatment for lung cancer from 2009 to 2018 in China Knowledge Network Database(CNKI) were retrieved and then analyzed by using CiteSpace3.9.R6. Knowledge graphs were made about the authors, institutions and keywords of those researches.Results A total of 1050 pieces of research were retrieved. The number of documents issued in the past decade is relatively stable. There were 440 researchers, represented by Xu Zhenye, etc. There were 352 research institutes, represented by Longhua Hospital affiliated to Shanghai University of Traditional Chinese Medicine. There were 140 keywords of which the highest frequency was non-small cell lung cancer. Clustering results mainly involved the observation of clinical efficacy of TCM in treating lung cancer, the analysis of diagnosis and treatment regularity of lung cancer by famous TCM experts, the biological mechanism research and the combination of TCM and western medicine in treating lung cancer. The application of data mining technology was currently the mainstream of research in this field, and it was of continuous sustainability.Conclusion In the past ten years, TCM treatment for lung cancer has been in vigorous development in China. TCM has unique advantages in treating lung cancer. The map is a preliminary visual representation of the development of the field, research hotspots and frontier trends, providing directions for future researches.
[中图分类号]
R273
[基金项目]