Visualising Digital Pathology Research : A Bibliometric Analysis from 1991-2021

Abstract

Introduction: Digital pathology encompasses the acquisition, management, sharing and interpretation of pathology information in a digital environment. Bibliometric analysis is a quantitative method to examine scholarly publications including the number of publications, citations, co-authorships, and collaboration network. Aim of this study is to provide a bibliometric analysis of academic documents on digital pathology (DP) from 1991-2021. Methods: The literature on digital pathology were obtained from the Scopus database. Frequency, percentage, data visualisation and citation metric were analysed using Microsoft Excel 365 and VOSviewer. Results: A total of 1848 documents from the Scopus database were analysed. There is a continuous growth of publications on DP with a total of 28330 citations. The United States was the most productive contributor to the publications followed by the United Kingdom and European countries, whilst University of Pittsburgh Medical Center, US produced the most publications. Progress in Biomedical Optics and Imaging Proceedings of SPIE was the largest source title while the Medical Image Analysis was the most prestigious journal. The keyword analysis suggests that DP research is mainly a medical imaging and engineering research domain with application in the histopathology subject. Conclusion: Digital Pathology research and publications continue to grow and concentrated in the Western countries. The publications focused on the image analysis, machine learning and engineering research domain in histopathology subject. Potential research areas include the implementation, validation of use and impact of DP to the pathology services and health care with exploration in other pathology subjects such as haematology.