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Review
. 2023 Mar 15;11(5):219.
doi: 10.21037/atm-22-3773. Epub 2023 Mar 9.

International publication trends in the application of artificial intelligence in ophthalmology research: an updated bibliometric analysis

Xue Jiang  1 , Minyue Xie  1 , Lan Ma  1 , Li Dong  1 , Dongmei Li  1
Affiliations
Review

International publication trends in the application of artificial intelligence in ophthalmology research: an updated bibliometric analysis

Xue Jiang et al. Ann Transl Med. .

Abstract

Background: The literature on artificial intelligence (AI)-related topics has been expanding rapidly over the last two decades, showing that AI is a crucial force in advancing ophthalmology. This analysis aims to provide a dynamic and longitudinal bibliometric analysis of AI-related ophthalmic papers.

Methods: The Web of Science was searched to retrieve papers regarding the application of AI in ophthalmology published in the English language up to May 2022. The variables were analyzed using Microsoft Excel 2019 and GraphPad Prism 9. Data visualization was performed using VOSviewer and CiteSpace.

Results: In this study, a total of 1,686 publications were analyzed. Recently, AI-related ophthalmology research has increased exponentially. China was the most productive country in this research field, with 483 articles, but the United States of America (446 publications) contributed most to the sum of citations and the H-index. The League of European Research Universities, Ting DSW, and Daniel SW were the most prolific institution and researchers. This field is primarily concerned with diabetic retinopathy (DR), glaucoma, optical coherence tomography, and the classification and diagnosis of fundus pictures. Current hotspots in AI research include deep learning, diagnosing and predicting systemic disorders by fundus images, incidence and progression of ocular diseases, and outcome prediction.

Conclusions: This analysis thoroughly reviews AI-related research in ophthalmology to help academics better comprehend the growth and possible practice consequences of AI. The association between eye and systemic biomarkers, telemedicine, real-world studies, and the development and application of new AI algorithms, such as visual converters, will continue to be research hotspots over the next few years.

Keywords: Artificial intelligence (AI); VOSviewer; bibliometrics; data visualization; ophthalmology.

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Conflict of interest statement

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://atm.amegroups.com/article/view/10.21037/atm-22-3773/coif). The authors have no conflicts of interest to declare.

Figures

Figure 1
Figure 1
Flowchart detailing the paper retrieval and screening process.
Figure 2
Figure 2
Contributions to the AI research in ophthalmology of different countries or regions. (A) The number of publications, citations (×0.05) and H-index value (×5) of the top 20 countries or regions. (B) A histogram showing the sum of publications worldwide and the top 3 countries, with the line indicating the time course of RRI. RRI, relative research interest. AI, artificial intelligence.
Figure 3
Figure 3
Fitting curves of the publication growth trends with years. (A) Global. (B) China. (C) The United States of America. (D) India.
Figure 4
Figure 4
Distribution of journals and institutions focusing on AI research in ophthalmology. (A) The top 20 journals with the most publications in this field. (B) The top 20 institutions with the most publications in this field. AI, artificial intelligence.
Figure 5
Figure 5
Institutional cooperation for AI research in ophthalmology. AI, artificial intelligence.
Figure 6
Figure 6
The analysis of keywords of AI research in ophthalmology. (A) Mapping of the keywords in the research. All keywords were divided into 4 clusters and given different colors: fundus imaging-related research (right in green), glaucoma research (left in red), OCT-related research (up in blue), and DR-related research (center in purple). Larger circles represent a higher frequency of the keywords. (B) The distribution of keywords based on the average time of appearance. Yellow indicates a recent appearance, and blue indicates an early appearance. Lines represent 2 keywords appearing in the same publication. Thicker lines indicate closer relationships. OCT, optical coherence tomography; DR, diabetic retinopathy; AI, artificial intelligence.
See this image and copyright information in PMC

Comment in

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