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.

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The intuitionistic fuzzy set has shown definite advantages in handling vagueness and uncertainty over a fuzzy set. Taking the powerfulness of the analytic hierarchy process (AHP) and the fuzzy AHP (FAHP) into account when tackling comprehensive multi-criteria decision-making problems, in this paper, we extend the classic AHP and the FAHP into the intuitionistic fuzzy AHP (IFAHP) in which the preferences are represented by intuitionistic fuzzy values. The IFAHP can be used to handle more complex problems, where the decision maker has some uncertainty in assigning preference values to the objects considered. The paper proposes a new way to check the consistency of an intuitionistic preference relation and then introduces an automatic procedure to repair the inconsistent one. It is worth pointing out that our proposed method can improve the inconsistent intuitionistic preference relation without the participation of the decision maker, and thus, it can save much time and show some advantages over the AHP and the FAHP. This paper also develops a novel normalizing rank summation method to derive the priority vector of an intuitionistic preference relation, on which the priorities of the hierarchy in the IFAHP are derived. The procedure of the IFAHP is given in detail, and an example concerning global supplier development is used to demonstrate our results. Index Terms-Decision making, intuitionistic hierarchy analysis process, intuitionistic fuzzy set, intuitionistic preference relation.1063-6706

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