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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-1...

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Detalles Bibliográficos
Autores principales: Wen, Ru, Zhang, Mudan, Xu, Rui, Gao, Yingming, Liu, Lin, Chen, Hui, Wang, Xingang, Zhu, Wenyan, Lin, Huafang, Liu, Chen, Zeng, Xianchun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9996554/
https://www.ncbi.nlm.nih.gov/pubmed/36892649
http://dx.doi.org/10.1007/s00330-023-09498-z
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author Wen, Ru
Zhang, Mudan
Xu, Rui
Gao, Yingming
Liu, Lin
Chen, Hui
Wang, Xingang
Zhu, Wenyan
Lin, Huafang
Liu, Chen
Zeng, Xianchun
author_facet Wen, Ru
Zhang, Mudan
Xu, Rui
Gao, Yingming
Liu, Lin
Chen, Hui
Wang, Xingang
Zhu, Wenyan
Lin, Huafang
Liu, Chen
Zeng, Xianchun
author_sort Wen, Ru
collection PubMed
description 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00330-023-09498-z.
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spelling pubmed-99965542023-03-09 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 Eur Radiol Chest 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00330-023-09498-z. Springer Berlin Heidelberg 2023-03-09 2023 /pmc/articles/PMC9996554/ /pubmed/36892649 http://dx.doi.org/10.1007/s00330-023-09498-z Text en © 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. This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Chest
Wen, Ru
Zhang, Mudan
Xu, Rui
Gao, Yingming
Liu, Lin
Chen, Hui
Wang, Xingang
Zhu, Wenyan
Lin, Huafang
Liu, Chen
Zeng, Xianchun
COVID-19 imaging, where do we go from here? Bibliometric analysis of medical imaging in COVID-19
title COVID-19 imaging, where do we go from here? Bibliometric analysis of medical imaging in COVID-19
title_full COVID-19 imaging, where do we go from here? Bibliometric analysis of medical imaging in COVID-19
title_fullStr COVID-19 imaging, where do we go from here? Bibliometric analysis of medical imaging in COVID-19
title_full_unstemmed COVID-19 imaging, where do we go from here? Bibliometric analysis of medical imaging in COVID-19
title_short COVID-19 imaging, where do we go from here? Bibliometric analysis of medical imaging in COVID-19
title_sort covid-19 imaging, where do we go from here? bibliometric analysis of medical imaging in covid-19
topic Chest
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9996554/
https://www.ncbi.nlm.nih.gov/pubmed/36892649
http://dx.doi.org/10.1007/s00330-023-09498-z
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