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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Artificial intelligence to distinguish retinal vein occlusion patients using color fundus photographs
Xiang Ren, Wei Feng, Ruijin Ran, et al.
Eye (2022) Vol. 37, Iss. 10, pp. 2026-2032
Open Access | Times Cited: 15

Showing 15 citing articles:

Research progress on diagnosing retinal vascular diseases based on artificial intelligence and fundus images
Yuke Ji, Yun Ji, Yunfang Liu, et al.
Frontiers in Cell and Developmental Biology (2023) Vol. 11
Open Access | Times Cited: 16
Retinal Vein Occlusion–Background Knowledge and Foreground Knowledge Prospects—A Review
Maja Lendzioszek, Anna Bryl, Ewa Poppe, et al.
Journal of Clinical Medicine (2024) Vol. 13, Iss. 13, pp. 3950-3950
Open Access | Times Cited: 6
A Future Picture: A Review of Current Generative Adversarial Neural Networks in Vitreoretinal Pathologies and Their Future Potentials
Raheem Remtulla, Adam Samet, Merve Kulbay, et al.
Biomedicines (2025) Vol. 13, Iss. 2, pp. 284-284
Open Access
Screening cognitive impairment in patients with atrial fibrillation: a deep learning model based on retinal fundus photographs
Zhen Wang, Mingxiao Li, Peng Xia, et al.
Heart Rhythm O2 (2025)
Open Access
Retinal vein occlusion risk prediction without fundus examination using a no-code machine learning tool for tabular data: a nationwide cross-sectional study from South Korea
Na Hyeon Yu, Daeun Chloe Shin, Ik Hee Ryu, et al.
BMC Medical Informatics and Decision Making (2025) Vol. 25, Iss. 1
Open Access
Artificial intelligence in retinal imaging: current status and future prospects
Katharina A. Heger, Sebastian M. Waldstein
Expert Review of Medical Devices (2023) Vol. 21, Iss. 1-2, pp. 73-89
Closed Access | Times Cited: 9
Interpretable Detection of Diabetic Retinopathy, Retinal Vein Occlusion, Age-Related Macular Degeneration, and Other Fundus Conditions
Wenlong Li, Linbo Bian, Baikai Ma, et al.
Diagnostics (2024) Vol. 14, Iss. 2, pp. 121-121
Open Access | Times Cited: 3
Advances in artificial intelligence models and algorithms in the field of optometry
Suyu Wang, Yuke Ji, Bai Wen, et al.
Frontiers in Cell and Developmental Biology (2023) Vol. 11
Open Access | Times Cited: 4
Deep learning segmentation of non-perfusion area from color fundus images and AI-generated fluorescein angiography
Kanato Masayoshi, Yusaku Katada, Nobuhiro Ozawa, et al.
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 1
Prediction of treatment outcome for branch retinal vein occlusion using convolutional neural network-based retinal fluorescein angiography
Yu-peng Zhang, Zhen Xing, Aijun Deng
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access | Times Cited: 1
Automated detection of central retinal artery occlusion using OCT imaging via explainable deep learning
Ansgar Beuse, D. Wénzel, Martin S. Spitzer, et al.
Ophthalmology Science (2024) Vol. 5, Iss. 2, pp. 100630-100630
Open Access | Times Cited: 1
Artificial Intelligence for the Diagnosis and Screening of Retinal Diseases
Alessandro Arrigo, Emanuela Aragona, Francesco Bandello
touchREVIEWS in Ophthalmology (2023) Vol. 17, Iss. 2, pp. 1-1
Open Access | Times Cited: 2
Machine learning and its current and future applications in the management of vitreoretinal disorders
Nitin Kumar, S.G. Diwan, Amit Mehndiratta, et al.
Expert Review of Ophthalmology (2024) Vol. 19, Iss. 3, pp. 227-242
Closed Access
Deep Learning Segmentation of Non-perfusion Area from Color Fundus Images and AI-generated Fluorescein Angiography
Kanato Masayoshi, Yusaku Katada, Nobuhiro Ozawa, et al.
Research Square (Research Square) (2024)
Open Access
Application and progress of artificial intelligence technology in the segmentation of hyperreflective foci in OCT images for ophthalmic disease research
Jia-Ning Ying, Yanyan Zhang, Wen-Die Li, et al.
International Journal of Ophthalmology (2024) Vol. 17, Iss. 6, pp. 1138-1143
Open Access
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