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

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..

Medienart:

E-Artikel

Erscheinungsjahr:

2023

Erschienen:

2023

Enthalten in:

Zur Gesamtaufnahme - volume:33

Enthalten in:

European radiology - 33(2023), 5 vom: 09. März, Seite 3133-3143

Sprache:

Englisch

Beteiligte Personen:

Wen, Ru [VerfasserIn]
Zhang, Mudan [VerfasserIn]
Xu, Rui [VerfasserIn]
Gao, Yingming [VerfasserIn]
Liu, Lin [VerfasserIn]
Chen, Hui [VerfasserIn]
Wang, Xingang [VerfasserIn]
Zhu, Wenyan [VerfasserIn]
Lin, Huafang [VerfasserIn]
Liu, Chen [VerfasserIn]
Zeng, Xianchun [VerfasserIn]

Links:

Volltext [lizenzpflichtig]

Themen:

Bibliometrics
COVID-19
CiteSpace
Medical imaging
Treads

RVK:

RVK Klassifikation

Anmerkungen:

© The Author(s), under exclusive licence to European Society of Radiology 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

doi:

10.1007/s00330-023-09498-z

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

OLC2134597836

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