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Author Spotlight: Challenges in Developing Dry Eye Animal Models and Future Research Directions
Published on: February 9, 2024
Dry Eye Analysis: A Citation Network Study
Miguel Angel M A Sanchez-Tena1, Cristina C Alvarez-Peregrina1, Cesar C Villa-Collar1
1School of Biomedical and Health Sciences, Universidad Europea de Madrid, Madrid 20822, Spain.
Introduction:
Dry eye is one of the most frequent eye problems with prevalence and incidence from 5% to 50%. Citation network analysis allows us to simplify information in a visual way and provides a better understanding of the research done in a specific field. The objective of this paper is to quantify and analyse the relationships among the scientific literature in this field using citation network analysis.
Materials And Methods:
The program used to analyse the citations was CitNetExplorer®. Previously, papers published in the research field during a predefined period were found using the keywords defined in Web of ScienceTM (WOS).
Results:
Using the keyword "dry eye," during the period 2007 to 2018, the most cited paper is by Lemp, MA (2007), with a citation index score of 913 in our citation network containing 6,500 most relevant papers. Analysing clustering, we found 5 relevant groups that match the main areas of research in this field: definition and classification, treatment, retina, refractive surgery, and quality of vision. Core Publication is composed of 64% of the papers in the network, which is a high percentage. It indicates a clear focus on the research carried out in this field.
Conclusions:
This citation network analysis shows definition and classification of dry eye to be the most researched area in this field, followed by treatment.
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