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SYSTEMATIC REVIEW article

Front. Med.
Sec. Ophthalmology
Volume 11 - 2024 | doi: 10.3389/fmed.2024.1489139
This article is part of the Research Topic New Concepts, Advances, and Future Trends in Clinical Research on Eye Diseases View all 6 articles

In-Depth Analysis of Research Hotspots and Emerging Trends in AI for Retinal Diseases Over the Past Decade

Provisionally accepted
Mingkai Guo Mingkai Guo 1Di Gong Di Gong 2Weihua Yang Weihua Yang 2*
  • 1 The Third School of Clinical Medicine, Guangzhou Medical University, Guangzhou, China
  • 2 Shenzhen Eye Hospital，Jinan University，Shenzhen Eye Institute, Shenzhen, China

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

    The application of Artificial Intelligence (AI) in diagnosing retinal diseases represents a significant advancement in ophthalmological research, with the potential to reshape future practices in the field. This study explores the extensive applications and emerging research frontiers of AI in retinal diseases.Objective: This study aims to uncover the developments and predict future directions of AI research in retinal disease over the past decade. Methods: This study analyzes AI utilization in retinal disease research through articles, using citation data sourced from the Web of Science (WOS) Core Collection database, covering the period from January 1, 2014, to December 31, 2023. A combination of WOS analyzer, CiteSpace 6.2 R4, and VOSviewer 1.6.19 was used for a bibliometric analysis focusing on citation frequency, collaborations, and keyword trends from an expert perspective. Results: A total of 2,861 articles across 93 countries or regions were cataloged, with notable growth in article numbers since 2017. China leads with 926 articles, constituting 32% of the total. The United States has the highest h-index at 66, while England has the most significant network centrality at 0.24. Notably, the University of London is the leading institution with 99 articles and shares the highest h-index ( 25) with University College London. The National University of Singapore stands out for its central role with a score of 0.16. Research primarily spans ophthalmology and computer science, with "network," "transfer learning," and "convolutional neural networks" being prominent burst keywords from 2021 to 2023. Conclusions: China leads globally in article counts, while the United States has a significant research impact. The University of London and University College London have made significant contributions to the literature. Diabetic retinopathy is the retinal disease with the highest volume of research. AI applications have focused on developing algorithms for diagnosing retinal diseases and investigating abnormal physiological features of the eye. Future research should pivot towards more advanced diagnostic systems for ophthalmic diseases.

    Keywords: artificial intelligence, Retinal disease, deep learning, machine learning, hotspot, trend

    Received: 05 Sep 2024; Accepted: 06 Nov 2024.

    Copyright: © 2024 Guo, Gong and Yang. 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: Weihua Yang, Shenzhen Eye Hospital，Jinan University，Shenzhen Eye Institute, Shenzhen, 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.