Jiang Xue, Xie Minyue, Ma Lan, Dong Li, Li Dongmei
Beijing Tongren Eye Center, Beijing Ophthalmology & Visual Sciences Key Lab, Capital Medical University, Beijing Tongren Hospital, Beijing, China.
Ann Transl Med. 2023 Mar 15;11(5):219. doi: 10.21037/atm-22-3773. Epub 2023 Mar 9.
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.
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.
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.
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.
在过去二十年中，关于人工智能（AI）相关主题的文献迅速增加，表明人工智能是推动眼科发展的关键力量。本分析旨在对人工智能相关眼科论文进行动态和纵向的文献计量分析。
检索科学网以获取截至2022年5月以英文发表的关于人工智能在眼科应用的论文。使用Microsoft Excel 2019和GraphPad Prism 9对变量进行分析。使用VOSviewer和CiteSpace进行数据可视化。
在本研究中，共分析了1686篇出版物。最近，人工智能相关的眼科研究呈指数级增长。中国是该研究领域产出最多的国家，有483篇文章，但美国（446篇出版物）在总被引次数和H指数方面贡献最大。欧洲研究型大学联盟、丁DSW和丹尼尔SW是产出最多的机构和研究人员。该领域主要关注糖尿病视网膜病变（DR）、青光眼、光学相干断层扫描以及眼底图片的分类和诊断。当前人工智能研究的热点包括深度学习、通过眼底图像诊断和预测全身性疾病、眼部疾病的发病率和进展以及结局预测。
本分析全面回顾了眼科领域与人工智能相关的研究，以帮助学者更好地理解人工智能的发展及其可能的实践影响。眼睛与全身生物标志物之间的关联、远程医疗、真实世界研究以及新人工智能算法（如视觉转换器）的开发和应用，在未来几年仍将是研究热点。
