BACKGROUND
Artificial intelligence (AI) has been applied in research to assist in diagnosing retinal diseases, and it may influence how ophthalmologists work in the future. This study investigated the broad applications and research frontiers of AI in retinal diseases.
OBJECTIVE
This study aimed to gain insights into the progress and future trends of AI technology to the research of retinal diseases within the last 10 years.
METHODS
To assess the scope of AI application in retinal diseases in publications, citation data were obtained from the Web of Science (WOS) Core Collection database between January 1, 2013, and December 1, 2022, and analyzed from an expert viewpoint using WOS analyzer, CiteSpace 6.2 R1, and VOSviewer 1.6.19.The bibliometric method was used to analyze the citation frequency, cooperation and keyword popularity.
RESULTS
In total, 4,384 publications from 98 countries or regions were identified, with a significant increase in the number of papers published in this field since 2017. China published the highest number of articles (1,194), accounting for 27% of the total. The US had the highest h-index (76). Germany had the highest centrality (0.29). The University of London published the highest number of articles (144), the National University of Singapore had the highest h-index (33), and Harvard University had the highest centrality (0.49). The articles published mainly focused on ophthalmology or computer science and technology. The burst keywords in the period from 2020 to 2022 were “progression” and “risk factors.”
CONCLUSIONS
China published the most literature worldwide, the US was the most influential country in this research field. The University of London and the National University of Singapore maintained the highest literature influence.Diabetic retinopathy is the retinal disease with the most related research literature. The development of AI algorithms and examination of aberrant physiological features of the eye are the main areas of AI research in retinal disease diagnosis. Future studies should focus on more advanced ophthalmic disease diagnostic systems.
CLINICALTRIAL