Bibliometric analysis of the 3-year trends (2018-2021) in literature on artificial intelligence in ophthalmology and vision sciences.

OBJECTIVES: The objective of this analysis is to present a current view of the field of ophthalmology and vision research and artificial intelligence (AI) from topical and geographical perspectives. This will clarify the direction of the field in the future and aid clinicians in adapting to new technological developments. METHODS: A comprehensive search of four different databases was conducted. Statistical and bibliometric analysis were done to characterise the literature. Softwares used included the R Studio bibliometrix package, and VOSviewer. RESULTS: A total of 3939 articles were included in the final bibliometric analysis. Diabetic retinopathy (391, 6% of the top 100 keywords) was the most frequently occurring indexed keyword by a large margin. The highest impact literature was produced by the least populated countries and in those countries who collaborate internationally. This was confirmed via a hypothesis test where no correlation was found between gross number of published articles and average number of citations (p value=0.866, r=0.038), while graphing ratio of international collaboration against average citations produced a positive correlation (r=0.283). Majority of publications were found to be concentrated in journals specialising in vision and computer science, with this category of journals having the highest number of publications per journal (18.00 publications/journal), though they represented a small proportion of the total journals (<1%). CONCLUSION: This study provides a unique characterisation of the literature at the intersection of AI and ophthalmology and presents correlations between article impact and geography, in addition to summarising popular research topics.

Clinical characteristics of non-infectious uveitis treated with and without systemic immunomodulatory therapy.

OBJECTIVE: To compare the patient characteristics and long-term outcomes for those treated with and without systemic immunomodulatory therapy (IMT) for non-infectious uveitis (NIU). DESIGN: Retrospective cohort study. PARTICIPANTS: All consecutive adults with NIU receiving care at 5 uveitis subspecialty tertiary care clinics between 2010 and 2021. METHODS: Clinical outcomes were evaluated on initial presentation and at the last available follow-up. The main outcome measures were baseline characteristics and final visual acuity. RESULTS: A total of 914 NIU patients (418 IMT, 496 non-IMT) with a median age of 51.0 years and 57.4% female were identified. Over half the patients had bilateral disease, with a significantly higher proportion of bilateral cases in the IMT group compared with the non-IMT group (p < 0.001). The IMT group was more likely to have chronic uveitis (p < 0.001), with a higher proportion of patients experiencing cataracts and cystoid macular edema (p < 0.001 for both). A significantly higher proportion of non-IMT patients had anterior uveitis and an idiopathic etiology (p < 0.001). Overall, visual acuity improved significantly from baseline to last follow-up in the entire cohort (p < 0.001), with a slightly better improvement in the IMT group. Multivariable linear regression analysis suggested that baseline visual acuity and panuveitis were significant predictors of final visual acuity (p < 0.001 for both). CONCLUSIONS: NIU patients on IMT are often younger, suffer from bilateral and chronic uveitis, and are more likely to have ocular complications. Those in the non-IMT group are more likely to have anterior idiopathic NIU. Baseline visual acuity and panuveitis are the main predictors of final vision outcomes among patients with NIU.

Bibliometric analysis of the uveitis literature and research trends over the past two decades.

OBJECTIVE: This study aimed to examine the publication patterns and present a current view of the field of uveitis using a bibliometric analysis. DESIGN: Bibliometric analysis. METHODS AND ANALYSIS: A comprehensive search of three databases including MEDLINE, EMBASE and Cochrane was conducted from 1 January 2000 to 31 December 2022. Search results from all three databases were subjected to analysis by Bibliometrix, an R programme that analyses large literature dataset with statistical and mathematical models. Visualisation of collaboration networks and relevance between countries was presented with VOSviewer. RESULTS: A total of 26 296 articles were included in the analysis. The field of uveitis has undergone a significant exponential growth since 2000, with an average growth rate of 4.14%. The most substantial annual growth was between the years 2021 and 2022 (36%). According to the corresponding author's countries, the three most productive countries were Turkey (3288, 12.6%), the USA (3136, 12%) and Japan (1981, 7.6%). The USA (243, 31.4%), England (117, 15%) and Germany (62, 8%) are the top three countries that contributed to clinical trials. The average international collaboration of all countries was 2.5%. CONCLUSIONS: Uveitis literature has undergone significant growth in the past two decades. The demographic factors of publishing countries lead to their various productivity and types of these uveitis studies, which is closely associated with the countries' scientific research resources and patient populations.

Three-year trends in literature on artificial intelligence in ophthalmology and vision sciences: a protocol for bibliometric analysis.

INTRODUCTION: The aim of this study is to provide an insight into the literature at the intersection of artificial intelligence and ophthalmology. METHODS AND ANALYSIS: The project will be performed in four key stages: formulation of search terms, literature collection, literature screening and literature analysis. A comprehensive search of databases including Scopus, Web of Science, Dimensions and Cochrane will be conducted. The Distiller SR software will be used for manual screening all relevant articles. The selected articles will be analysed via R Bibliometrix, a program for mathematical analysis of large sets of literature, and VOSviewer, which creates visual representations of connections between articles. ETHICS AND DISSEMINATION: This study did not require research ethics approval given the use of publicly available data and lack of human subjects. The results will be presented at scientific meetings and published in peer-reviewed journals.