基于UMLS的肺癌治疗研究热点分析  

UMLS-based analysis of hotspots in studies on lung cancer therapy

作　　者：宫小翠 安新颖[1] 赵迎光[1] GONG Xiao-cui AN Xin-ying ZHAO Ying-guang(Institute of Medical Information, Chinese Academy of Medical Sciences, Beijing 100020, China)

机构地区：[1]中国医学科学院医学信息研究所,北京100020

出　　处：《中华医学图书情报杂志》2017年第1期46-50,共5页Chinese Journal of Medical Library and Information Science

基　　金：国家自然科学基金项目"基于语义的医学领域前沿知识发现及演化机制研究"(71303259);中国医学科学院中央公益性基本科研业务费课题"面向医学科技评价的多源异构数据处理机制研究"(2016ZX330027)

摘　　要：目的:利用文本挖掘的方法识别肺癌治疗的研究前沿热点。方法:在Pub Med数据库中检索2013-2014年发表的肺癌治疗相关文献,利用Meta Map进行UMLS概念映射,通过语义类型的限定去除较为宽泛意义的词,利用文档主题生成模型LDA进行主题识别。结果:利用LDA可以识别出肺癌治疗方面近两年的研究主题。结论:分析主题结果并阅读相关文献,可得出近年肺癌治疗的研究热点主题,为相关医学科研人员和管理人员提供参考。Objective To identify the frontiers and hotspots in studies on lung cancer therapy by text mining. Methods Pub Med-covered papers on lung cancer therapy were retrieved from 2013 to 2014. The terms with a broader meaning were excluded by mapping the UMLS concept with Meta Map and by limiting their semantic types. A LDA model was established to identify the topics. Results The LDA model could identify the frontiers and hotspots in studies on lung cancer therapy from 2013 to 2014. Conclusion Frontiers and hotspots in studies on lung cancer therapy can be identified by analyzing the topics and reading the related literature,which can thus provide reference for related medical researchers and managers.

关 键 词：肺癌 治疗 研究热点 UMLS LDA 文本挖掘 主题识别 

分 类 号：R734.2[医药卫生—肿瘤]