Explorative Bibliometric Study of Medical Image Analysis: Unveiling Trends and Advancements

被引：0

作者：

Thomas B. ^{[1
,2
]}

Joseph J. ^{[1
,2
]}

Jose J. ^{[2
]}

机构：

[1] Department of Computer Applications, Marian College Kuttikkanam Autonomous, Kerala, Idukki

[2] Marian College Kuttikkanam Autonomous, Kerala, Idukki

来源：

Scientific Visualization | 2023年 / 15卷 / 05期

关键词：

Artificial Intelligence; Bibliometric analysis; Biblioshiny; Deep Learning; Machine Learning; Medical Image Analysis; VOSviewer;

D O I：

10.26583/sv.15.5.04

中图分类号：

学科分类号：

摘要：

Medical image analysis has quickly advanced, with several advantages for research, diagnosis, and healthcare planning. We must have enough knowledge of current trends and developments in this field due to improvements in medical imaging technology and the accessibility of a wide range of medical image databases. This work covers the research environment for bibliometric analysis of academic articles as part of medical image analysis, utilizing the tools VOSviewer and Biblioshiny. The Scopus database contains 1, 973 articles submitted between 1988 and 2023; all have been gathered and examined. The study has focused on the key bibliometric elements, such as authorship patterns, highly cited papers, prestigious journals, and collaborative networks. The outcomes of our inquiry demonstrate its interdisciplinary nature. This bibliometric analysis is a valuable resource for researchers, practitioners, and decision-makers, allowing them to identify significant trends, identify knowledge gaps, and explore prospects for further advancements in this critical field by providing a comprehensive overview of the literature on medical image analysis. © 2023 National Research Nuclear University. All rights reserved.

引用

页码：35 / 49

页数：14

共 18 条

[1]

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[2]

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[3]

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[4]

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[8]

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[9]

Yu Y., Li Y., Zhang Z., Gu Z., Zhong H., Zha Q., Yang L., Zhu C., Chen E., A bibliometric analysis using VOSviewer of publications on COVID-19, Annals of Translational Medicine, 8, 13, (2020)

[10]

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