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Big data analysis of endovascular treatment of intracranial aneurysms: a bibliometric analysis of the top 100 most cited articles
Background The impact of a literature report on a particular subject can be measured by its number of citations. Objective The purpose of this study was to evaluate the characteristics of the literature reports in the field of endovascular treatment of intracranial aneurysms (IAs) by analyzing the...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Thieme Revinter Publicações Ltda.
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9800165/ https://www.ncbi.nlm.nih.gov/pubmed/36580955 http://dx.doi.org/10.1055/s-0042-1758650 |
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author | Zhang, Shuai Liu, Dong Wang, Jiao Lv, Ming |
author_facet | Zhang, Shuai Liu, Dong Wang, Jiao Lv, Ming |
author_sort | Zhang, Shuai |
collection | PubMed |
description | Background The impact of a literature report on a particular subject can be measured by its number of citations. Objective The purpose of this study was to evaluate the characteristics of the literature reports in the field of endovascular treatment of intracranial aneurysms (IAs) by analyzing the top 100 most cited articles. It should be noted that the focus of this study is to describe the bibliometric characteristics. Methods This bibliometric analysis dedicated only to endovascular treatment of IAs in our study. We searched the top 100 most cited articles in the field of endovascular treatment of IAs using the search tool of the Web of Science (WOS). We evaluated the characteristics of these high-impact publications, including publication year, category, journal, author's country, etc. Results The top 100 most cited articles were cited 281.3 times, on average. The United States has published the most articles every year compared with other countries. These highly cited articles are mostly published in the Journal of Neurosurgery. Eighty-six of the top 100 most cited articles were clinical studies. Conclusion The bibliometric analysis provides insight over the development and the growing trend in endovascular treatment of IAs. This study can help researchers better understand the global overview of this field, and it also provides leads about promising areas of future research and potential collaborations. |
format | Online Article Text |
id | pubmed-9800165 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Thieme Revinter Publicações Ltda. |
record_format | MEDLINE/PubMed |
spelling | pubmed-98001652023-01-09 Big data analysis of endovascular treatment of intracranial aneurysms: a bibliometric analysis of the top 100 most cited articles Zhang, Shuai Liu, Dong Wang, Jiao Lv, Ming Arq Neuropsiquiatr Background The impact of a literature report on a particular subject can be measured by its number of citations. Objective The purpose of this study was to evaluate the characteristics of the literature reports in the field of endovascular treatment of intracranial aneurysms (IAs) by analyzing the top 100 most cited articles. It should be noted that the focus of this study is to describe the bibliometric characteristics. Methods This bibliometric analysis dedicated only to endovascular treatment of IAs in our study. We searched the top 100 most cited articles in the field of endovascular treatment of IAs using the search tool of the Web of Science (WOS). We evaluated the characteristics of these high-impact publications, including publication year, category, journal, author's country, etc. Results The top 100 most cited articles were cited 281.3 times, on average. The United States has published the most articles every year compared with other countries. These highly cited articles are mostly published in the Journal of Neurosurgery. Eighty-six of the top 100 most cited articles were clinical studies. Conclusion The bibliometric analysis provides insight over the development and the growing trend in endovascular treatment of IAs. This study can help researchers better understand the global overview of this field, and it also provides leads about promising areas of future research and potential collaborations. Thieme Revinter Publicações Ltda. 2022-12-29 /pmc/articles/PMC9800165/ /pubmed/36580955 http://dx.doi.org/10.1055/s-0042-1758650 Text en Academia Brasileira de Neurologia. This is an open access article published by Thieme under the terms of the Creative Commons Attribution 4.0 International License, permitting copying and reproduction so long as the original work is given appropriate credit ( https://creativecommons.org/licenses/by/4.0/ ) https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Zhang, Shuai Liu, Dong Wang, Jiao Lv, Ming Big data analysis of endovascular treatment of intracranial aneurysms: a bibliometric analysis of the top 100 most cited articles |
title | Big data analysis of endovascular treatment of intracranial aneurysms: a bibliometric analysis of the top 100 most cited articles |
title_full | Big data analysis of endovascular treatment of intracranial aneurysms: a bibliometric analysis of the top 100 most cited articles |
title_fullStr | Big data analysis of endovascular treatment of intracranial aneurysms: a bibliometric analysis of the top 100 most cited articles |
title_full_unstemmed | Big data analysis of endovascular treatment of intracranial aneurysms: a bibliometric analysis of the top 100 most cited articles |
title_short | Big data analysis of endovascular treatment of intracranial aneurysms: a bibliometric analysis of the top 100 most cited articles |
title_sort | big data analysis of endovascular treatment of intracranial aneurysms: a bibliometric analysis of the top 100 most cited articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9800165/ https://www.ncbi.nlm.nih.gov/pubmed/36580955 http://dx.doi.org/10.1055/s-0042-1758650 |
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