| 基于文献计量学对我国临床试验用药品管理研究现状的数据挖掘 |
| 投稿时间：2024-04-11 修订日期：2024-09-18 点此下载全文 |
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| 基金项目:北京市科学技术委员会“北京医药临床试验服务后补助工作”经费（Z211100002921053） |
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| 中文摘要:目的：基于文献计量学方法对我国试验用药品管理领域的文献进行数据挖掘,明确该领域的发展现状与研究热点。方法：在中国知网(CNKI)等中文文献数据库中,以“试验”、“药品”、“管理”为检索词,用“and”或“和”连接,从文献中提取文献题名、作者姓名、作者单位、中文、中文关键词、发表年限、期刊名称等内容,根据CNKI文献可视化分析系统、CiteSpace等软件进行聚类分析并绘制网状知识图谱。结果：我国试验用药品管理领域的文献最早发表于1994年,至2022年共计发表140篇,其中有20篇文献得到了相关基金资助,关键词共现频次最高的是“受试者”,刊载文献最多的媒介为《中国药学年鉴》。结论：现阶段我国试验用药品管理领域的文献数量较少且质量较低,作者间的合作也不紧密、交流较少,各基金项目对此领域的资助力度也有所欠缺,以上因素导致该领域的整体发展水平较低、发展速度较为缓慢。 |
| 中文关键词:临床试验 药品 管理 文献计量学 数据挖掘 |
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| The Data Mining of Current Research Status of Clinical Trial Drug Management in China |
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| Abstract:Objective: Based on bibliometric methods, data mining was conducted on the literature in the field of experimental drug management in China to clarify the current development status and research hotspots in this field. Method: In Chinese literature databases such as China National Knowledge Infrastructure (CNKI), search terms such as "experiment", "drug", and "management" were used to connect with "and" or "and". The title, author name, author affiliation, Chinese abstract, Chinese keywords, publication period, journal name, and other content of the literature were extracted from the literature. Cluster analysis was performed using CNKI literature visualization analysis system, CiteSpace and other software, and a network knowledge map was drawn. Result: The literature in the field of experimental drug management in China was first published in 1994, and a total of 140 articles were published by 2022. Among them, 20 articles were supported by relevant funds, and the keyword co-occurrence frequency was highest among "subjects". The most frequently published medium was the Chinese Pharmacological Yearbook. Conclusion: At present, the quantity and quality of literature in the field of experimental drug management in China are relatively small, and the cooperation and communication among authors are not close. The funding from various fund projects in this field is also lacking. These factors lead to a lower overall development level and slower development speed in this field. |
| keywords:Clinical trials Medicines Management Bibliometrics Data mining |
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