清晨好,您是今天最早来到科研通的研友!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您科研之路漫漫前行!

Global research of artificial intelligence in eyelid diseases: A bibliometric analysis

文献计量学 眼睑 数据科学 计算机科学 医学 图书馆学 眼科
作者
X. Zhang,Ziying Zhou,Yilu Cai,Andrzej Grzybowski,Juan Ye,Lixia Lou
出处
期刊:Heliyon [Elsevier BV]
卷期号:10 (14): e34979-e34979
标识
DOI:10.1016/j.heliyon.2024.e34979
摘要

PurposeTo generate an overview of global research on artificial intelligence (AI) in eyelid diseases using a bibliometric approach.MethodsAll publications related to AI in eyelid diseases from 1900 to 2023 were retrieved from the Web of Science (WoS) Core Collection database. After manual screening, 98 publications published between 2000 and 2023 were finally included. We analyzed the annual trend of publication and citation count, productivity and co-authorship of countries/territories and institutions, research domain, source journal, co-occurrence and evolution of the keywords and co-citation and clustering of the references, using the analytic tool of the WoS, VOSviewer, Wordcloud Python package and CiteSpace.ResultsBy analyzing a total of 98 relevant publications, we detected that this field had continuously developed over the past two decades and had entered a phase of rapid development in the last three years. Among these countries/territories and institutions contributing to this field, China was the most productive country and had the most institutions with high productivity, while USA was the most active in collaborating with others. The most popular research domains was Ophthalmology and the most productive journals were Ocular Surface. The co-occurrence network of keywords could be classified into 3 clusters respectively concerned about blepharoptosis, meibomian gland dysfunction and blepharospasm. The evolution of research hotspots is from clinical features to clinical scenarios and from image processing to deep learning. In the clustering analysis of co-cited reference network, cluster "0# deep learning" was the largest and latest, and cluster "#5 meibomian glands visibility assessment" existed for the longest time.ConclusionsAlthough the research of AI in eyelid diseases has rapidly developed in the last three years, there are still gaps in this area. Our findings provide researchers with a better understanding of the development of the field and a reference for future research directions.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
yan259完成签到 ,获得积分10
2秒前
钱念波完成签到 ,获得积分10
7秒前
猫小免完成签到 ,获得积分10
9秒前
12秒前
小企鹅发布了新的文献求助10
14秒前
王小凡完成签到 ,获得积分10
17秒前
victory_liu完成签到,获得积分0
18秒前
燕儿完成签到 ,获得积分10
19秒前
zhangruiii完成签到 ,获得积分10
25秒前
kaige88完成签到,获得积分10
37秒前
阿木完成签到 ,获得积分10
41秒前
易瑾完成签到 ,获得积分10
43秒前
stiger完成签到,获得积分0
46秒前
小企鹅完成签到,获得积分20
51秒前
yiiy完成签到,获得积分10
56秒前
PHI完成签到 ,获得积分10
57秒前
LEE123完成签到,获得积分10
1分钟前
张甜完成签到 ,获得积分10
1分钟前
义气柜子完成签到 ,获得积分10
1分钟前
粗暴的镜子完成签到,获得积分10
1分钟前
shepherd完成签到,获得积分10
1分钟前
包容的雨泽完成签到 ,获得积分10
1分钟前
呆萌冰彤完成签到 ,获得积分10
1分钟前
小张完成签到 ,获得积分10
2分钟前
111完成签到 ,获得积分10
2分钟前
2分钟前
miaorunquan完成签到,获得积分10
2分钟前
sonicker完成签到 ,获得积分10
2分钟前
叁月二完成签到 ,获得积分10
2分钟前
xdc完成签到,获得积分20
2分钟前
xdc发布了新的文献求助10
2分钟前
Ava应助xdc采纳,获得10
2分钟前
HiDasiy完成签到 ,获得积分10
2分钟前
JLB完成签到 ,获得积分10
2分钟前
吃的饱饱呀完成签到 ,获得积分10
2分钟前
我不是哪吒完成签到 ,获得积分10
2分钟前
3分钟前
xiaojinyu完成签到,获得积分10
3分钟前
xdc发布了新的文献求助10
3分钟前
xiaojinyu完成签到,获得积分10
3分钟前
高分求助中
Principles of Economics, 11th Edition 10000
University Physics with Modern Physics, 16th edition 10000
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
48V Low-voltage Power Distribution Network (PDN) Architecture Industry Report, 2024 800
ズームレンズの光学設計に関する研究 800
Fundamentals of Pharmaceutical and Biologics Regulations: A Global Perspective, Second Edition 700
Matrix Methods in Data Mining and Pattern Recognition Second Edition 610
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7298107
求助须知:如何正确求助?哪些是违规求助? 8916567
关于积分的说明 18879421
捐赠科研通 6963240
什么是DOI,文献DOI怎么找? 3210641
关于科研通互助平台的介绍 2379958
邀请新用户注册赠送积分活动 2187125