Early cancer diagnosis using lab-on-a-chip devices : A bibliometric and network analysis

IF 1.6 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE COLLNET Journal of Scientometrics and Information Management Pub Date : 2021-01-02 DOI:10.1080/09737766.2021.1949949
Luiza Amara Maciel Braga, Fabio Batista Mota
{"title":"Early cancer diagnosis using lab-on-a-chip devices : A bibliometric and network analysis","authors":"Luiza Amara Maciel Braga, Fabio Batista Mota","doi":"10.1080/09737766.2021.1949949","DOIUrl":null,"url":null,"abstract":"In the future, early diagnosis of cancers may be performed using labon-a-chip devices. Yet, very little is known about the research obtained so far, who are the leading institutions, and how they collaborate. We address this gap by mapping the global research on early cancer diagnosis and labs-on-a-chip. Bibliometrics and network analysis were applied to analyze data of 301 articles collected in the Web of Science Core Collection, published between 2010 and 2020. The two most frequent tumor markers are the prostate-specific antigen and the carcinoembryonic antigen; the USA and China are the most relevant countries, and the Chinese Academy of Sciences and the Massachusetts Institute of Technology are the most publishing institutions; they also established the greatest research collaborations. This study identifies research trends on lab-on-a-chip for tumor marker identification, and the most publishing countries and institutions, which can be helpful to stakeholders working on this research topic.","PeriodicalId":10501,"journal":{"name":"COLLNET Journal of Scientometrics and Information Management","volume":"15 1","pages":"163 - 196"},"PeriodicalIF":1.6000,"publicationDate":"2021-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/09737766.2021.1949949","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"COLLNET Journal of Scientometrics and Information Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/09737766.2021.1949949","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}
引用次数: 1

Abstract

In the future, early diagnosis of cancers may be performed using labon-a-chip devices. Yet, very little is known about the research obtained so far, who are the leading institutions, and how they collaborate. We address this gap by mapping the global research on early cancer diagnosis and labs-on-a-chip. Bibliometrics and network analysis were applied to analyze data of 301 articles collected in the Web of Science Core Collection, published between 2010 and 2020. The two most frequent tumor markers are the prostate-specific antigen and the carcinoembryonic antigen; the USA and China are the most relevant countries, and the Chinese Academy of Sciences and the Massachusetts Institute of Technology are the most publishing institutions; they also established the greatest research collaborations. This study identifies research trends on lab-on-a-chip for tumor marker identification, and the most publishing countries and institutions, which can be helpful to stakeholders working on this research topic.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
使用芯片实验室设备进行早期癌症诊断:文献计量学和网络分析
在未来,癌症的早期诊断可能会使用labon-a-chip设备进行。然而,迄今为止所获得的研究,谁是领先的机构,以及他们如何合作,知之甚少。我们通过绘制早期癌症诊断和芯片实验室的全球研究来解决这一差距。本文采用文献计量学和网络分析法对2010年至2020年间发表的301篇Web of Science核心文集进行了数据分析。两种最常见的肿瘤标志物是前列腺特异性抗原和癌胚抗原;美国和中国是最相关的国家,中国科学院和麻省理工学院是最多的出版机构;他们还建立了最伟大的研究合作。本研究确定了芯片实验室肿瘤标志物识别的研究趋势,以及发表最多的国家和机构,可以为从事该研究课题的利益相关者提供帮助。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
COLLNET Journal of Scientometrics and Information Management
COLLNET Journal of Scientometrics and Information Management INFORMATION SCIENCE & LIBRARY SCIENCE-
自引率
0.00%
发文量
11
期刊最新文献
Mapping of top papers in the subject category of Soil Science Mapping global research on expert systems Research trends in the field of natural language processing : A scientometric study based on global publications during 2001-2020 Classic articles in cervical cancer research : A bibliometric analysis Human and algorithmic decision-making in the personnel selection process: A comparative bibliometric on bias
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1