Knowledge Graph Modeling in Healthcare: A Bibliometric Analysis

M. Furqon, Nina Fadilah Najwa, Deny Hermansyah, Mohammad Zarkasi
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引用次数: 0

Abstract

Healthcare issues are currently the most researched issues worldwide. Many healthcare researchers collaborate with non-healthcare researchers to improve the quality of healthcare. The knowledge graph is a widely used computer science and mathematics approach to solve healthcare issues. It can model the relationship between events to build new knowledge. Hence, a comprehensive study on knowledge graph modeling in healthcare was conducted in this study. The research methodologies in this study were: (1) article retrieval and general bibliometric analysis; (2) visualization of research distribution; and (3) research recommendations. In the last three years, 867 articles were retrieved from three databases. The citation metrics analysis was also conducted to determine the quality level of articles retrieval. An analysis was conducted using network and density visualization related to the relationship between research topics and trends. The final results in this paper are recommendations for research topics and research titles related to knowledge graph modeling in healthcare.
医疗保健中的知识图建模:文献计量分析
医疗保健问题是目前全球研究最多的问题。许多医疗研究人员与非医疗研究人员合作,以提高医疗质量。知识图是一种广泛使用的计算机科学和数学方法,用于解决医疗保健问题。它可以对事件之间的关系进行建模,以构建新的知识。因此,本研究对医疗保健中的知识图建模进行了全面的研究。本研究的研究方法为:(1)文献检索和一般文献计量分析;(2) 研究分布的可视化;(3)研究建议。在过去三年中,从三个数据库中检索到867篇文章。还进行了引文度量分析,以确定文章检索的质量水平。使用网络和密度可视化对研究主题和趋势之间的关系进行了分析。本文的最终结果是对医疗保健中知识图建模相关的研究主题和研究标题的建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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6 weeks
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