Mapping the intellectual structure of research on surgery with mixed reality: Bibliometric network analysis (2000-2019)

Abstract

Objective: The purpose of this study is to view research trends on surgery with mixed reality, and present the intellectual structure using bibliometric network analysis for the period 2000-2019.

Methods: Analyses are implemented in the following four steps: (1) literature dataset acquisition from article database (Web of Science, Scopus, PubMed, and IEEE digital library), (2) dataset pre-processing and refinement, (3) network construction and visualization, and (4) analysis and interpretation. Descriptive analysis, bibliometric network analysis, and in-depth qualitative analysis were conducted.

Results: The 14,591 keywords of 5897 abstracts data were ultimately used to ascertain the intellectual structure of research on surgery with mixed reality. The dynamics of the evolution of keywords in the structure throughout the four periods is summarized with four aspects: (a) maintaining a predominant utilization tool for training, (b) widening clinical application area, (c) reallocating the continuum of mixed reality, and (d) steering advanced imaging and simulation technology.

Conclusions: The results of this study can provide valuable insights into technology adoption and research trends of mixed reality in surgery. These findings can help clinicians to overview prospective medical research on surgery using mixed reality. Hospitals can also understand the periodical maturity of technology of mixed reality in surgery, and, therefore, these findings can suggest an academic landscape to make a decision in adopting new technologies in surgery.