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COVID-19 imaging, where do we go from here? Bibliometric analysis of medical imaging in COVID-19.
Wen, Ru; Zhang, Mudan; Xu, Rui; Gao, Yingming; Liu, Lin; Chen, Hui; Wang, Xingang; Zhu, Wenyan; Lin, Huafang; Liu, Chen; Zeng, Xianchun.
  • Wen R; Medical College, Guizhou University, Guizhou, 550000, People's Republic of China.
  • Zhang M; Department of Radiology, Southwest Hospital, Army Medical University (Third Military Medical University), 30 Gao Tan Yan St, 400038, Chongqing, People's Republic of China.
  • Xu R; Department of Medical Imaging, Guizhou Provincial People Hospital, No.83, East Zhongshan Road, Nanming District, Guizhou Province, 550000, Guiyang City, People's Republic of China.
  • Gao Y; Guizhou Medical University, Guiyang, Guizhou Province, 550000, People's Republic of China.
  • Liu L; Department of Medical Imaging, Guizhou Provincial People Hospital, No.83, East Zhongshan Road, Nanming District, Guizhou Province, 550000, Guiyang City, People's Republic of China.
  • Chen H; College of Life Science, Guizhou University, Guiyang, Guizhou Province, 550000, People's Republic of China.
  • Wang X; Department of Respiratory Medicine, Guizhou Provincial People Hospital, Guiyang City, Guizhou Province, 550000, People's Republic of China.
  • Zhu W; Department of Radiology, Southwest Hospital, Army Medical University (Third Military Medical University), 30 Gao Tan Yan St, 400038, Chongqing, People's Republic of China.
  • Lin H; Department of Radiology, Southwest Hospital, Army Medical University (Third Military Medical University), 30 Gao Tan Yan St, 400038, Chongqing, People's Republic of China.
  • Liu C; Medical Department, Yidu Cloud (Beijing) Technology Co., Ltd., Beijing, 100191, People's Republic of China.
  • Zeng X; Medical Department, Yidu Cloud (Beijing) Technology Co., Ltd., Beijing, 100191, People's Republic of China.
Eur Radiol ; 33(5): 3133-3143, 2023 May.
Article in English | MEDLINE | ID: covidwho-2286543
ABSTRACT

OBJECTIVES:

We conducted a systematic and comprehensive bibliometric analysis of COVID-19-related medical imaging to determine the current status and indicate possible future directions.

METHODS:

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.

RESULTS:

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.

CONCLUSIONS:

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. Key Points • 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.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Artificial Intelligence / COVID-19 Type of study: Diagnostic study / Prognostic study / Systematic review/Meta Analysis Topics: Vaccines Limits: Humans Language: English Journal: Eur Radiol Journal subject: Radiology Year: 2023 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Artificial Intelligence / COVID-19 Type of study: Diagnostic study / Prognostic study / Systematic review/Meta Analysis Topics: Vaccines Limits: Humans Language: English Journal: Eur Radiol Journal subject: Radiology Year: 2023 Document Type: Article