全球大数据与健康管理的研究热点聚类分析

Clustering Analysis of Research Hotspots of the Big Data and Health Management

揭示全球大数据与健康管理的研究热点。采用文献计量学和双向聚类分析法。发现全球大数据与健康管理现已达到年均发文量1 000篇以上;全球有89个国家和地区都进行了该方面的研究,其中欧洲地区的国家合作交流频繁;该领域中重要出版物有Stud Health Technol Inform、Plo S one等;目前研究热点主要聚焦为蛋白质等生物大分子网络作用的信息挖掘、数据挖掘在药物数据库及电子健康档案的应用、基因组序列数据挖掘在疾病预测中的应用、药物生物信息学的数据挖掘、生物医学大型数据库的数据挖掘、系统生物学的数据挖掘和医疗卫生服务中的数据挖掘等7个方面。

To analyze the key points of articles about big data and health management from database of PubMed, bibliometrics and bicluster methods were used. The average annual output of papers published has reached more than 1 000 in this field; and 89 countries or regions have carried out the research, among which European countries have developed cooperation and exchange frequently; the important journals include Stud Health Technol Inform, and PIoS one, etc; research hotspots focus mainly on 7 aspects： information mining of protein interaction networks, applica- tion of data mining in drug database and electronic health records, application of genome sequence data mining in disease prediction, data mining of drug bioinformatics, data mining of biomedical large database, data mining of sys- tems biology, and data mining of medical and health services.