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Sustainability 2018, 10(1), 166;

A Bibliometric Analysis and Visualization of Medical Big Data Research

Business School, Sichuan University, Chengdu 610064, China
Medical Insurance Office,West China School of Medicine, Sichuan University, Chengdu 610041, China
Centre for Computational Intelligence, Faculty of Technology, De Montfort University, Leicester LE1 9BH, UK
School of Computer Science, University of Manchester, Manchester M13 9PL, UK
Author to whom correspondence should be addressed.
Received: 13 December 2017 / Revised: 1 January 2018 / Accepted: 9 January 2018 / Published: 11 January 2018
(This article belongs to the Special Issue Big Data and Predictive Analytics for Sustainability)
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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. View Full-Text
Keywords: medical big data; bibliometric analysis; visualization; co-citation analysis; co-authorship analysis medical big data; bibliometric analysis; visualization; co-citation analysis; co-authorship analysis

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Liao, H.; Tang, M.; Luo, L.; Li, C.; Chiclana, F.; Zeng, X.-J. A Bibliometric Analysis and Visualization of Medical Big Data Research. Sustainability 2018, 10, 166.

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