| 基于CiteSpace国内传染病预测模型热点趋势可视化分析 |
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| 引用本文： | 王晓璇,朱高培,冯佳宁,肖宇飞,孙娜,许小珊,王素珍.基于CiteSpace国内传染病预测模型热点趋势可视化分析[J].现代预防医学,2020,0(16):2886-2890. |
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| 作者姓名： | 王晓璇 朱高培 冯佳宁 肖宇飞 孙娜 许小珊 王素珍 |
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| 作者单位： | 潍坊医学院公共卫生学院，山东 潍坊 261053 |
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| 摘 要： | 目的 通过分析近20年来国内传染病预测模型相关研究的发文量、学者、研究机构等相关信息，辅助国内学者更全面了解该领域研究现状、研究热点及趋势。方法 以2000 - 2019年间CNKI中文数据库相关的论文作为数据来源，运用CiteSpace5.6.R 2和SPSS 20.0分别进行文献计量分析和多维尺度分析。结果 共获取符合要求的文献207篇，其中发文量最多的机构为《现代预防医学》杂志（17篇）；发文量最多的学者为李晓松（6篇）；发文量最多的机构为华中科技大学（10篇）。ARIMA模型和灰色模型在传染病预测模型中的应用是目前研究的热点。结论 国内传染病预测模型研究存在一定的局限性，需要进一步探讨联合模型和模型的优化；此外发文量和影响力有待进一步提升，机构部门之间的合作联系需进一步加强，需建立多部门多学科的合作。
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| 关 键 词： | CiteSpace 传染病 预测 模型 |
Visualization analysis of hot trends based on CiteSpace domestic infectious disease prediction model |
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| WANG Xiao-xuan,ZHU Gao-pei,FENG Jia-ning,XIAO Yu-fei,SUN Na,XU Xiao-shan,WANG Su-zhen.Visualization analysis of hot trends based on CiteSpace domestic infectious disease prediction model[J].Modern Preventive Medicine,2020,0(16):2886-2890. |
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| Authors: | WANG Xiao-xuan ZHU Gao-pei FENG Jia-ning XIAO Yu-fei SUN Na XU Xiao-shan WANG Su-zhen |
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| Affiliation: | *Department of Public Health and Management, Weifang Medical University, Weifang, Shandong 261053, China |
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| Abstract: | The aim of this study was to analyze the publication volume, relevant scholars and research institutions ofdomestic researches on infectious disease prediction models in the past 20 years, in order to assist domestic scholars to have amore comprehensive understanding of the research status, research hotspots and trends in this field. Methods Data sources werepapers related to CNKI Chinese database from 2000 to 2019. CiteSpace 5.6.R2 was used for bibliometrics and SPSS 20.0 was usedfor multidimensional scaling analysis. Results A total of 207 literatures that met the requirements were obtained, among whichthe journal of Modern Preventive Medicine published the most. The scholar with the most publications was Li Xiaosong.Huazhong University of Science and Technology published the most papers. The applications of ARIMA model and grey model inthe prediction of infectious diseases were the focus of current research. Conclusion There were some limitations in the researchon the prediction model of infectious diseases in China. Joint models and optimization of models need to be further explored. Inaddition, the absolute number and influence of publications need to be further enhanced. We need to further strengthen thecooperation between institutions and departments, and establish multi-sectoral and multi-disciplinary cooperative relations. |
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| Keywords: | CiteSpace Infectious disease Prediction Model |
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