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

Q4 Computer Science Scientific Visualization Pub Date : 2023-12-01 DOI:10.26583/sv.15.5.04
Binu Thomas, Jeena Joseph, Jobin Jose
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引用次数: 0

Abstract

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.
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医学影像分析文献计量学探索性研究:揭示趋势与进步
医学影像分析发展迅速,在研究、诊断和医疗保健规划方面具有诸多优势。由于医学影像技术的进步和各种医学影像数据库的可访问性,我们必须对该领域当前的趋势和发展有足够的了解。本研究利用 VOSviewer 和 Biblioshiny 工具,为医学影像分析中的学术论文文献计量分析提供了研究环境。Scopus 数据库包含 1988 年至 2023 年间提交的 1,973 篇文章,所有文章都已收集并进行了检查。研究的重点是文献计量学的关键要素,如作者身份模式、高被引论文、著名期刊和合作网络。我们的研究成果显示了其跨学科性质。这项文献计量学分析是研究人员、从业人员和决策者的宝贵资源,通过对医学影像分析文献的全面概述,他们可以发现重要趋势,找出知识差距,并探索在这一关键领域取得进一步进展的前景。
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来源期刊
Scientific Visualization
Scientific Visualization Computer Science-Computer Vision and Pattern Recognition
CiteScore
1.30
自引率
0.00%
发文量
20
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