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高度近视人工智能的全球趋势与热点:文献计量分析

Global trends and hotspots in artificial intelligence for high myopia: a bibliometric analysis.

作者信息

Wang Xuze, Wumaier Ailixiati, Wang Jun, Song Dejuan, Cai Yiting, Han Jin, Han Wei, Fang Zhi

机构信息

Zhejiang Provincial Key Laboratory of Ophthalmology, Zhejiang Provincial Clinical Research Center for Eye Diseases, School of Medicine, Eye Center of Second Affiliated Hospital, Zhejiang Provincial Engineering Institute on Eye Diseases, Zhejiang University, Hangzhou, China.

出版信息

Front Med (Lausanne). 2025 May 9;12:1567440. doi: 10.3389/fmed.2025.1567440. eCollection 2025.


DOI:10.3389/fmed.2025.1567440
PMID:40417679
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12098612/
Abstract

PURPOSE: This study aims to conduct a bibliometric analysis of global publications on the application of artificial intelligence (AI) in high myopia (HM). METHODS: We retrieved publications on AI in HM from the Web of Science Core Collection (WoSCC) database, MEDLINE and Chinese Science Citation Database (CSCD) with data up to 2024. The analysis focused on publication and citation trends, identifying key articles, influential countries, institutions, authors, and journals. Additionally, we explored research domains and emerging keywords. RESULTS: A total of 167 relevant publications were included. The first AI-related paper on HM was published in 2017, with a significant surge in 2021, followed by a consistent increase in publication and citation counts over the next 3 years. China emerged as the most productive country, with the most extensive international collaboration. East Asian authors dominated the top 10 most influential authors. Yang, Weihua and Investigative Ophthalmology & Visual Science (IOVS) contributed the most publications among authors and institutions, respectively. Keyword analysis revealed that retinal imaging-related terms remained a consistent research focus, while newly emerging keywords included "automated detection" and "childhood." CONCLUSION: Recent advancements in AI applications for HM have been significant and are expected to continue. Future research will likely focus on multimodal imaging and improving algorithm accessibility. Our findings offered the first comprehensive overview of global research on AI in HM, thus providing valuable insights for researchers to understand the current status and future trends in this field.

摘要

目的:本研究旨在对全球关于人工智能(AI)在高度近视(HM)中应用的出版物进行文献计量分析。 方法:我们从科学网核心合集(WoSCC)数据库、MEDLINE和中国科学引文数据库(CSCD)中检索截至2024年的关于AI在HM中的出版物。分析重点在于发表和被引趋势、确定关键文章、有影响力的国家、机构、作者和期刊。此外,我们还探索了研究领域和新兴关键词。 结果:共纳入167篇相关出版物。第一篇关于HM的AI相关论文发表于2017年,2021年有显著激增,随后在接下来的3年里发表量和被引次数持续增加。中国成为产出最多的国家,拥有最广泛的国际合作。东亚作者在最具影响力的前10位作者中占主导地位。在作者和机构中,杨卫华和《Investigative Ophthalmology & Visual Science》(IOVS)分别贡献了最多的出版物。关键词分析显示,视网膜成像相关术语一直是研究重点,而新兴关键词包括“自动检测”和“儿童期”。 结论:AI在HM应用方面的近期进展显著,预计将持续下去。未来研究可能会集中在多模态成像和提高算法可及性上。我们的研究结果首次全面概述了全球关于AI在HM中的研究,从而为研究人员了解该领域的现状和未来趋势提供了有价值的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5456/12098612/87b16b639531/fmed-12-1567440-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5456/12098612/1cd868e8115e/fmed-12-1567440-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5456/12098612/bd8738643074/fmed-12-1567440-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5456/12098612/cbd5f559a4db/fmed-12-1567440-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5456/12098612/93f8ffc1d9bc/fmed-12-1567440-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5456/12098612/070ce1203fae/fmed-12-1567440-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5456/12098612/99a7391df021/fmed-12-1567440-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5456/12098612/1a35ab153ddc/fmed-12-1567440-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5456/12098612/87b16b639531/fmed-12-1567440-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5456/12098612/1cd868e8115e/fmed-12-1567440-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5456/12098612/bd8738643074/fmed-12-1567440-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5456/12098612/cbd5f559a4db/fmed-12-1567440-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5456/12098612/93f8ffc1d9bc/fmed-12-1567440-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5456/12098612/070ce1203fae/fmed-12-1567440-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5456/12098612/99a7391df021/fmed-12-1567440-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5456/12098612/1a35ab153ddc/fmed-12-1567440-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5456/12098612/87b16b639531/fmed-12-1567440-g008.jpg

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本文引用的文献

[1]
Integrating electrocardiogram and fundus images for early detection of cardiovascular diseases.

Sci Rep. 2025-2-5

[2]
The Promise of Remote Patient Monitoring.

Telemed J E Health. 2024-12

[3]
A deep learning-based image analysis for assessing the extent of abduction in abducens nerve palsy patients before and after strabismus surgery.

Adv Ophthalmol Pract Res. 2024-6-25

[4]
AI-based fully automatic analysis of retinal vascular morphology in pediatric high myopia.

BMC Ophthalmol. 2024-9-27

[5]
Diagnosing Cataracts in the Digital Age: A Survey on AI, Metaverse, and Digital Twin Applications.

Semin Ophthalmol. 2024-11

[6]
IOL power calculation in long eyes: Selection of the best axial length adjustement factor using the most common formulas.

Heliyon. 2024-8-23

[7]
Artificial intelligence in myopia in children: current trends and future directions.

Curr Opin Ophthalmol. 2024-11-1

[8]
Choroidal Vascularity and Axial Length Elongation in Highly Myopic Children: A 2-Year Longitudinal Investigation.

Invest Ophthalmol Vis Sci. 2024-8-1

[9]
High myopia: Reviews of myopia control strategies and myopia complications.

Ophthalmic Physiol Opt. 2024-9

[10]
Multimodal imaging in diabetic retinopathy and macular edema: An update about biomarkers.

Surv Ophthalmol. 2024

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