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

IF 4.1 Q1 HEALTH CARE SCIENCES & SERVICES BMJ Health & Care Informatics Pub Date : 2024-02-28 DOI:10.1136/bmjhci-2023-100780
Hayley Monson, Jeffrey Demaine, Adrianna Perryman, Tina Felfeli
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Abstract

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.

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眼科学和视觉科学领域人工智能文献的 3 年趋势(2018-2021 年)文献计量分析。
目标:本分析报告旨在从专题和地理角度介绍眼科和视觉研究以及人工智能(AI)领域的现状。这将明确该领域未来的发展方向,并帮助临床医生适应新的技术发展:方法:对四个不同的数据库进行了全面检索。方法:对四个不同的数据库进行了全面搜索,并进行了统计和文献计量分析,以确定文献的特点。使用的软件包括 R Studio bibliometrix 软件包和 VOSviewer:最终的文献计量分析共纳入了 3939 篇文章。糖尿病视网膜病变(391篇,占前100个关键词的6%)是出现频率最高的索引关键词。人口最少的国家和开展国际合作的国家发表的文献影响最大。通过假设检验证实了这一点,即发表文章总数与平均引用次数之间没有相关性(P 值=0.866,r=0.038),而国际合作比率与平均引用次数之间的曲线图则产生了正相关性(r=0.283)。大部分论文集中在视觉和计算机科学专业期刊上,这类期刊的论文数量最多(18.00 篇/期刊),但在期刊总数中所占比例较小(结论:这类期刊的论文数量最多,但在期刊总数中所占比例较小):本研究对人工智能与眼科学交叉领域的文献进行了独特的描述,除了总结热门研究课题外,还介绍了文章影响力与地域之间的相关性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
6.10
自引率
4.90%
发文量
40
审稿时长
18 weeks
期刊最新文献
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