COVID-19 imaging, where do we go from here? Bibliometric analysis of medical imaging in COVID-19

被引:8
|
作者
Wen, Ru [1 ,2 ,3 ]
Zhang, Mudan [4 ]
Xu, Rui [3 ]
Gao, Yingming [5 ]
Liu, Lin [6 ]
Chen, Hui [2 ]
Wang, Xingang [2 ]
Zhu, Wenyan [7 ]
Lin, Huafang [7 ]
Liu, Chen [2 ]
Zeng, Xianchun [3 ]
机构
[1] Guizhou Univ, Med Coll, Guiyang 550000, Guizhou, Peoples R China
[2] Third Mil Med Univ, Army Med Univ, Southwest Hosp, Dept Radiol, 30 Gao Tan Yan St, Chongqing 400038, Peoples R China
[3] Guizhou Prov People Hosp, Dept Med Imaging, 83 East Zhongshan Rd, Guiyang 550000, Guizhou, Peoples R China
[4] Guizhou Med Univ, Guiyang 550000, Guizhou, Peoples R China
[5] Guizhou Univ, Coll Life Sci, Guiyang 550000, Guizhou, Peoples R China
[6] Guizhou Prov People Hosp, Dept Resp Med, Guiyang 550000, Guizhou, Peoples R China
[7] Yidu Cloud Beijing Technol Co Ltd, Med Dept, Beijing 100191, Peoples R China
关键词
COVID-19; Medical imaging; Bibliometrics; CiteSpace; Treads; EMERGING TRENDS; IMPACT;
D O I
10.1007/s00330-023-09498-z
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
ObjectivesWe conducted a systematic and comprehensive bibliometric analysis of COVID-19-related medical imaging to determine the current status and indicate possible future directions.MethodsThis research provides an analysis of Web of Science Core Collection (WoSCC) indexed articles on COVID-19 and medical imaging published between 1 January 2020 and 30 June 2022, using the search terms "COVID-19" and medical imaging terms (such as "X-ray" or "CT"). Publications based solely on COVID-19 themes or medical image themes were excluded. CiteSpace was used to identify the predominant topics and generate a visual map of countries, institutions, authors, and keyword networks.ResultsThe search included 4444 publications. The journal with the most publications was European Radiology, and the most co-cited journal was Radiology. China was the most frequently cited country in terms of co-authorship, with the Huazhong University of Science and Technology being the institution contributing with the highest number of relevant co-authorships. Research trends and leading topics included: assessment of initial COVID-19-related clinical imaging features, differential diagnosis using artificial intelligence (AI) technology and model interpretability, diagnosis systems construction, COVID-19 vaccination, complications, and predicting prognosis.ConclusionsThis bibliometric analysis of COVID-19-related medical imaging helps clarify the current research situation and developmental trends. Subsequent trends in COVID-19 imaging are likely to shift from lung structure to function, from lung tissue to other related organs, and from COVID-19 to the impact of COVID-19 on the diagnosis and treatment of other diseases.
引用
收藏
页码:3133 / 3143
页数:11
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