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SYSTEMATIC REVIEW article

Front. Med.
Sec. Ophthalmology
Volume 11 - 2024 | doi: 10.3389/fmed.2024.1481088
This article is part of the Research Topic Imaging in the Diagnosis and Treatment of Eye Diseases View all articles

Trends and Hotspots in the Field of Diabetic Retinopathy Imaging Research from 2000-2023

Provisionally accepted
Qing Zhang Qing Zhang 1Ping Zhang Ping Zhang 2Naimei Chen Naimei Chen 3Zhentao Zhu Zhentao Zhu 3*Wangting Li Wangting Li 2*Qiang Wang Qiang Wang 4*
  • 1 The Third Affiliated Hospital of Xinxiang Medical University, Xinxiang, China
  • 2 Shenzhen Eye Institute, Shenzhen Eye Hospital, Shenzhen, China
  • 3 Department of Ophthalmology, Huaian Hospital of Huaian City, Huaian, China
  • 4 Department of Ophthalmology, Third Affiliated Hospital,Wenzhou Medical University, Ruian, China

The final, formatted version of the article will be published soon.

    Background: Diabetic retinopathy (DR) poses a major threat to diabetic patients' vision and is a critical public health issue. Imaging applications for DR have grown since the 21st century, aiding diagnosis, grading, and screening. This study uses bibliometric analysis to assess the field's advancements and key areas of interest.This study performed a bibliometric analysis of DR imaging articles collected from the Web of Science Core Collection database between January 1st, 2000, and December 31st, 2023. The literature information was then analyzed through CiteSpace.The US and China led in the number of publications, with 719 and 609, respectively. The University of London topped the institution list with 139 papers. Tien Yin Wong was the most prolific researcher. Invest. Ophthalmol. Vis. Sci. published the most articles (105). Notable burst keywords were "deep learning," "artificial intelligence," et al.The US is at the forefront of DR research, with the University of London as the top institution and Invest. Ophthalmol. Vis. Sci. as the most published journal. Tien Yin Wong is the most influential researcher. Hotspots like "deep learning," and "artificial intelligence," have seen a significant rise, indicating artificial intelligence's growing role in DR imaging.

    Keywords: Diabetic Retinopathy, imaging, diagnosis, artificial intelligence, Bibliometric

    Received: 15 Aug 2024; Accepted: 27 Sep 2024.

    Copyright: © 2024 Zhang, Zhang, Chen, Zhu, Li and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence:
    Zhentao Zhu, Department of Ophthalmology, Huaian Hospital of Huaian City, Huaian, China
    Wangting Li, Shenzhen Eye Institute, Shenzhen Eye Hospital, Shenzhen, 518040, China
    Qiang Wang, Department of Ophthalmology, Third Affiliated Hospital,Wenzhou Medical University, Ruian, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.