医疗保健中的大数据——当前研究趋势的综合文献计量学分析

IF 0.9 Q4 COMPUTER SCIENCE, SOFTWARE ENGINEERING Scalable Computing-Practice and Experience Pub Date : 2023-09-10 DOI:10.12694/scpe.v24i3.2155
Aijaz Reshi, Arif Shah, Shabana Shafi, Majid Hussain Qadri
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引用次数: 0

摘要

本研究的主要目的是对医疗保健领域的大数据研究现状进行全面的文献计量分析。在过去十年中,大数据作为医疗保健领域的一项重要技术,导致了科学文献的指数级增长。本研究的重点是分析许多关键的文献计量指标,如总体研究产出、作者生产率、机构生产率、国家生产率、合作分析、研究趋势以及大数据和医疗保健研究产出的专题重点。对SCOPUS和Web of Science数据库中1018个出版来源中发表的2294篇研究论文进行了分析。从2012年开始进行的初步研究结果显示,第一年有6篇研究文章发表在给定领域。然后,该领域发表的文章每年都呈指数级增长,然而,就发表数量而言,2019年至2021年是最具生产力和增量的年份。本研究的分析结果从年度科研产出、全球被引次数最多的文章、作者时间产出、最高产的国家和最相关的隶属关系等方面对科研产出进行了绩效分析。此外,还对关键词共现、专题制图、最相关作者、年度来源分布、协作网络分析等指标进行了科学制图分析。本研究对该领域的研究热点和趋势、主题重点和未来研究方向提供了较为全面的分析结果,为本研究领域做出了有益的贡献。这些成果将有助于大数据和医疗保健领域的研究人员规划和设计需要探索的研究以及挑战和机遇。
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Big Data in Healthcare - A Comprehensive Bibliometric Analysis of Current Research Trends
The primary purpose of this study is to perform a comprehensive bibliometric analysis of research landscape of big data in healthcare. Big data as a significant technology used in healthcare during the past decade has led to the exponential growth in scientific literature. This study is focused on analysis of many crucial bibliometric indicators such as, overall research output, author productivity, institutional productivity, country wise productivity, collaboration analysis, research trends along with a thematic focus of research output in big data and healthcare. The analysis has been performed on 2294 research articles published in 1018 publication sources from SCOPUS and Web of Science databases. The initial results of the study performed from year 2012 reveals that in the first year 6 research articles were published in the given domain. Then every year the growth of published articles in the field was exponential, however years 2019 to 2021 were the most productive and incremental in terms of number of publications. The analysis results of the study present the performance analysis of research production in terms of annual scientific production, most globally cited articles, author’s production over the time, most productive countries, and most relevant affiliations. In addition, the science mapping analysis including the indicators such as, keyword Co-occurrence, Thematic Mapping, Most Relevant Authors, annual source distribution, and collaboration Network analysis has been presented. The study delivers expedient contribution to the field of study by noticeably offering comprehensive analysis results regarding research hotspots and trends, thematic emphasis, and future direction of research in the field. These outcomes will aid researchers in big data and healthcare in planning and designing the research and the challenges and opportunities needed to be explored.
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来源期刊
Scalable Computing-Practice and Experience
Scalable Computing-Practice and Experience COMPUTER SCIENCE, SOFTWARE ENGINEERING-
CiteScore
2.00
自引率
0.00%
发文量
10
期刊介绍: The area of scalable computing has matured and reached a point where new issues and trends require a professional forum. SCPE will provide this avenue by publishing original refereed papers that address the present as well as the future of parallel and distributed computing. The journal will focus on algorithm development, implementation and execution on real-world parallel architectures, and application of parallel and distributed computing to the solution of real-life problems.
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