Published 2023 | Version v1
Journal article

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

  • 1. Department of Medical Imaging, Guizhou Provincial People Hospital, No.83, East Zhongshan Road, Nanming District, 550000, Guiyang City, Guizhou Province (China)
  • 2. Department of Radiology, Southwest Hospital, Army Medical University (Third Military Medical University), 30 Gao Tan Yan St, 400038, Chongqing (China)
  • 3. Medical College, Guizhou University, 550000, Guizhou (China)
  • 4. Guizhou Medical University, 550000, Guiyang, Guizhou Province (China)
  • 5. College of Life Science, Guizhou University, 550000, Guiyang, Guizhou Province (China)
  • 6. Department of Respiratory Medicine, Guizhou Provincial People Hospital, 550000, Guiyang City, Guizhou Province (China)
  • 7. Medical Department, Yidu Cloud (Beijing) Technology Co., Ltd., 100191, Beijing (China)

Description

We conducted a systematic and comprehensive bibliometric analysis of COVID-19-related medical imaging to determine the current status and indicate possible future directions. This 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. The 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. This 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. We conducted a systematic and comprehensive bibliometric analysis of COVID-19-related medical imaging from 1 January 2020 to 30 June 2022. Research trends and leading topics included assessment of initial COVID-19-related clinical imaging features, differential diagnosis using AI technology and model interpretability, diagnosis systems construction, COVID-19 vaccination, complications, and predicting prognosis. Future trends in COVID-19-related imaging are likely to involve a 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.

Availability note (English)

Available from: http://dx.doi.org/10.1007/s00330-023-09498-z

Additional details

Identifiers

Publishing Information

Journal Title
European Radiology (Internet)
Journal Volume
33
Journal Issue
5
Journal Page Range
p. 3133-3143
ISSN
1432-1084
CODEN
EURAE3