中医药防治肺纤维化相关文献的数据挖掘

发布时间：2019-01-13 20:29

【摘要】：目的:应用数据挖掘技术研究有关中医药防治肺纤维化数据挖掘的文献,了解数据挖掘中医药防治肺纤维化的现状,并进一步应用数据挖掘技术为研究中医药防治肺纤维化提供参考。方法:检索中文期刊全文数据库(CNKI)、万方、维普、中国生物医学文献数据库(CBM)数据库,根据纳入标准及排除标准纳入文献,从文献类别、发表年份、数据挖掘方法及软件、资料来源、研究领域等方面进行数据分析。结果:共纳入中医药防治肺纤维化相关数据挖掘文献19篇,最近5年发表16篇;文献类别以期刊为主,占73.68%;建立数据库软件以Microsoft Office Excel为主,占57.89%,而数据分析软件以SPSS为主,占54.17%;数据挖掘方法涉及频数分析、聚类分析、关联分析、因子分析和对应分析五种;资料来源以现代期刊硕博文献和临床病案记录为主,占73.69%;研究领域则集中于中药复方用药规律,占84.21%。结论:应用数据挖掘技术研究中医药防治肺纤维化成果显著,但研究深度及广度不足,只有进一步加大研究力度并充分利用数据挖掘的优势,才能有效推动中医药防治肺纤维化的研究。
[Abstract]:Objective: to study the literature on data mining of prevention and treatment of pulmonary fibrosis by using data mining technology, and to understand the present situation of data mining in the prevention and treatment of pulmonary fibrosis with traditional Chinese medicine. And further application of data mining technology for the study of Chinese medicine prevention and treatment of pulmonary fibrosis to provide a reference. Methods: the Chinese journal full-text database (CNKI), Wanfang, Weipu, and Chinese biomedical literature database (CBM) database were searched. According to the inclusion criteria and exclusion criteria, the literature was included in the literature category, and published in the year of publication. Data mining methods and software, data sources, research areas and other aspects of data analysis. Results: there were 19 articles on data mining related to the prevention and treatment of pulmonary fibrosis by TCM, 16 of which were published in the last 5 years, and the main types of literatures were periodicals, accounting for 73.68%. The database software is mainly Microsoft Office Excel, accounting for 57.89, while the data analysis software is SPSS, accounting for 54.17.The methods of data mining include frequency analysis, cluster analysis, association analysis, factor analysis and correspondence analysis. The data were mainly collected from modern journals and medical records, accounting for 73.69, while the research fields focused on the law of drug use of traditional Chinese medicine compound, accounting for 84.21. Conclusion: the application of data mining technology in the prevention and treatment of pulmonary fibrosis by traditional Chinese medicine has achieved remarkable results, but the depth and breadth of the research are insufficient. Only by further strengthening the research and making full use of the advantages of data mining, In order to effectively promote the prevention and treatment of Chinese medicine pulmonary fibrosis research.
【作者单位】：辽宁中医药大学;辽宁中医药大学附属医院;
【基金】：国家自然科学基金面上项目(81373579);国家自然科学基金青年科学基金项目(81403290) 辽宁省科技厅计划项目(2012225018-202) 辽宁省中医临床重点学(专)科服务能力建设项目(2013-LNZYXZK-2) 辽宁省高等学校科学研究一般基础研究项目(L2014369) 沈阳市科技局计划项目(F14-231-1-13)
【分类号】：R259;TP311.13

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