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国际临床研究杂志

International Journal of Clinical Research

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International Journal of Clinical Research. 2023; 7: (8) ; 10.12208/j.ijcr.20231287 .

Research hotspots and trends of colon polyps based on Web of science database analysis
基于 Web of science 数据库分析的结肠息肉研究热点和趋势

作者: 张秋心, 郑盛 *

大理大学第二附属医院消化内科 云南昆明

*通讯作者: 郑盛,单位:大理大学第二附属医院消化内科 云南昆明;

引用本文: 张秋心, 郑盛 基于 Web of science 数据库分析的结肠息肉研究热点和趋势[J]. 国际临床研究杂志, 2023; 7: (8) : 1-9.
Published: 2023/8/20 17:44:14

摘要

目的 本研究通过分析结肠息肉领域的发文情况、研究热点及研究趋势,为该领域相关人员开展学术研究提供参考。方法 在Web of Science 数据库中检索结肠息肉相关的英文文献(论著或综述),发表日期限定为2013年1月1日-2023年1月1日。利用CiteSpace软件对检索到的文献进行可视化分析,得到论文发文量、关键词共现、突现及聚类等基本信息,并绘制相关可视化图谱。结果 检索获得2012篇文献,结果显示,结肠息肉领域论文数量整体呈上升趋势,关键词共现分析示colorectal cancer(结直肠癌 639次),tumor(肿瘤361次),colonic polyp(结肠息肉325次),colonoscopy(结肠镜检查273次),risk(风险272次),Polyp(息肉265次)。突发性检测强度前10位关键词colorectal cancer(结直肠癌 639次),tumor(肿瘤361次),colonic polyp(结肠息肉325次),colonoscopy(结肠镜检查273次),risk(风险272次),Polyp(息肉265次),这表明他们与该领域的其他关键词有大量的联系。2013-2018年主要涉及有关结肠息肉的内镜检查及诊断方法,然而随着医疗水平的进步及生活方式和饮食习惯的改变,结肠息肉确诊率呈逐渐升高的趋势,关于结肠息肉研究于2020年左右大量涌现,一直延续至2023年,其中结肠息肉治疗手段成为临床研究热点。关于结肠息肉的研究于2013年大量涌现,一直延续到2023年。关键词聚类分析生成12个聚类图谱,研究热点集中于聚类#1代表beta-boswellic acid、聚类#2代表colorectal adenoma、聚类#3代表miniature dachshund、聚类#4代表population-based colonoscopy screening、聚类#5代表gastric adenocarcinoma、聚类#6代表real-world evidence、聚类#7代表hot polypectomy、聚类#8代表serum biomarker、聚类#9代表systematic training、聚类#10代表optical diagnosis、聚类#12代表artificial intelligence、聚类#11代表maligant colorectal polyp、聚类#12代表artificial intelligence、聚类#13代表turkish population、聚类#14代表inflammatory bowel disease、聚类#15代表macc1 level、聚类#16代表hyperplastic colonic polyp。结论 本研究利用Cite space软件对结肠息肉可视化分析,初步揭示该领域发展方向,结果具有重要的价值和意义。

关键词: 结肠息肉;Web of Science;CiteSpace;文献计量学

Abstract

Objective By analyzing the published articles, research hotspots and research trends in the field of colon polyps, this study provides reference for relevant personnel in this field to carry out academic research.
Methods English literatures (treatises or reviews) related to colon polyps were searched in the Web of Science database, and the publication date was limited from 2013 to 2023. Using CiteSpace software to visually analyze the retrieved documents, we can get basic information such as the number of papers published, keyword co-occurrence, emergence and clustering, and draw relevant visual maps.
Results 2012 papers were retrieved, and the results showed that the number of papers in the field of colonic Polyps showed an overall upward trend. Keyword co-occurrence analysis showed that colorectal cancer (639 times), tumor (361 times), colonic polyp (325 times), colonoscopy (273 times), risk (272 times) and polyp (272 times). The top 10 keywords of sudden detection intensity are colorectal cancer (639 times), tumor (361 times), colonic Polyp (325 times), colonoscopy (273 times of colonoscopy), risk (272 times) and polyp (265 times), which shows that they have a lot of connections with other keywords in this field. From 2013 to 2018, it mainly involved the endoscopic examination and diagnosis methods of colon polyps. However, with the progress of medical level and the changes of lifestyle and eating habits, the diagnosis rate of colon polyps showed a gradual increase. A large number of studies on colon polyps emerged around 2020 and continued until 2023, among which the treatment methods of colon polyps became a hot spot in clinical research. Research on colonic polyps emerged in large numbers in 2013 and continued until 2023. Keyword cluster analysis generates 12 cluster maps, The research focuses on cluster #1 for beta-boswellic acid, cluster #2 for colorectal adenoma, cluster #3 for miniature dachshund, cluster #4 for Population-based Colonoscopy Screening and cluster # 5 stands for gastric adenocarcinoma, cluster #6 stands for real-world evidence, cluster #7 stands for hot diversity, cluster #8 stands for serum biomarker, cluster #9 stands for systematic training, cluster #10 stands for optical diagnosis and cluster # 12 stands for artificial intelligence, cluster #11 stands for maligant color polyp, cluster #12 stands for artificial intelligence, cluster #13 stands for turkish population and cluster # 14 stands for imported bowl disease, cluster #15 stands for macc1 level, and cluster #16 stands for hyperplastic colonic polyp.
Conclusion   In this study, Cite space software was used to visually analyze colon polyps, and the development direction of this field was initially revealed. The results have important value and significance.

Key words: Colonic polyps; Web of Science; CiteSpace; Bibliometrics

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