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医疗保健研究中信息论与复杂性科学方法的可视化分析

Visual Analysis on Information Theory and Science of Complexity Approaches in Healthcare Research.

作者信息

Wang Xiaoyu, Zhao Wang, Wang Yongzhong, Zhao Qin, Yang Xuejie, Su Kaixiang, Gu Dongxiao

机构信息

The Department of Pharmacy, Anhui University of Traditional Chinese Medicine, Hefei 230031, China.

The School of Management, Hefei University of Technology, Hefei 230009, China.

出版信息

Entropy (Basel). 2020 Jan 16;22(1):109. doi: 10.3390/e22010109.

Abstract

In order to explore the knowledge base, research hotspot, development status, and future research direction of healthcare research based on information theory and complex science, a total of 3031 literature data samples from the core collection of Web of Science from 2003 to 2019 were selected for bibliometric analysis. HistCite, CiteSpace, Excel, and other analytical tools were used to deeply analyze and visualize the temporal distribution, spatial distribution, knowledge evolution, literature co-citation, and research hotspots of this field. This paper reveals the current development of healthcare research field based on information theory and science of complexity, analyzes and discusses the research hotspots and future development that trends in this field, and provides important knowledge support for researchers in this field for further relevant research.

摘要

为了探究基于信息论和复杂科学的医疗保健研究的知识库、研究热点、发展现状及未来研究方向,选取了2003年至2019年Web of Science核心合集中的3031篇文献数据样本进行文献计量分析。使用HistCite、CiteSpace、Excel等分析工具对该领域的时间分布、空间分布、知识演化、文献共被引及研究热点进行深入分析和可视化呈现。本文揭示了基于信息论和复杂科学的医疗保健研究领域的当前发展情况,分析和讨论了该领域的研究热点及未来发展趋势,为该领域的研究人员进行进一步的相关研究提供了重要的知识支持。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ac6f/7516411/c6532b9d22f0/entropy-22-00109-g004.jpg

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