A Bibliometric Analysis and Visualization of Medical Big Data Research

• Main Authors: Huchang Liao, Ming Tang, Li Luo, Chunyang Li, Francisco Chiclana, Xiao-Jun Zeng
• Format: Article
• Language: English
• Published: MDPI AG 2018-01-01
• Series: Sustainability
• Subjects: medical big data; bibliometric analysis; visualization; co-citation analysis; co-authorship analysis
• Online Access: http://www.mdpi.com/2071-1050/10/1/166

With the rapid development of “Internet plus”, medical care has entered the era of big data. However, there is little research on medical big data (MBD) from the perspectives of bibliometrics and visualization. The substantive research on the basic aspects of MBD itself is also rare. This study aims to explore the current status of medical big data through visualization analysis on the journal papers related to MBD. We analyze a total of 988 references which were downloaded from the Science Citation Index Expanded and the Social Science Citation Index databases from Web of Science and the time span was defined as “all years”. The GraphPad Prism 5, VOSviewer and CiteSpace softwares are used for analysis. Many results concerning the annual trends, the top players in terms of journal and institute levels, the citations and H-index in terms of country level, the keywords distribution, the highly cited papers, the co-authorship status and the most influential journals and authors are presented in this paper. This study points out the development status and trends on MBD. It can help people in the medical profession to get comprehensive understanding on the state of the art of MBD. It also has reference values for the research and application of the MBD visualization methods.