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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:

Advancing glaucoma detection with convolutional neural networks: a paradigm shift in ophthalmology
H Shafeeq Ahmed, Vidyadevi Mahadevappa
Romanian Journal of Ophthalmology (2023) Vol. 67, Iss. 3
Open Access | Times Cited: 10

Showing 10 citing articles:

A comparative study on the effectiveness of interactive versus non-interactive optic disc photograph training modules for glaucoma diagnosis among ophthalmology residents
Thanatcha Tanjirawatana, Kitiya Ratanawongphaibul, Anita Manassakorn, et al.
Cogent Education (2025) Vol. 12, Iss. 1
Open Access | Times Cited: 1
Evaluation of Convolutional Neural Networks (CNNs) in Identifying Retinal Conditions Through Classification of Optical Coherence Tomography (OCT) Images
Rohin R. Teegavarapu, Harshal A. Sanghvi, Triya Belani, et al.
Cureus (2025)
Open Access
Artificial Intelligence for Optical Coherence Tomography in Glaucoma
Mak B. Djulbegovic, Henry Bair, David J. Taylor Gonzalez, et al.
Translational Vision Science & Technology (2025) Vol. 14, Iss. 1, pp. 27-27
Open Access
Independent Evaluation of RetFound Foundation Model's Performance on Optic Nerve Analysis Using Fundus Photography
Maggie Chen, Rohith Ravindranath, Robert T. Chang, et al.
Ophthalmology Science (2025), pp. 100720-100720
Open Access
AN EFFICIET GLAUCOMA PREDICTION AND CLASSIFICATION INTEGRATING RETINAL FUNDUS IMAGES AND CLINICAL DATA USING DnCNN WITH MACHINE LEARNING ALGORITHMS
Bindu Priya Makala, D. Manoj Kumar
Results in Engineering (2025), pp. 104220-104220
Open Access
Evaluating the Incidence of Glaucoma, Age-Related Macular Degeneration, and Diabetic Retinopathy in Western New York and Assessing the Feasibility of Utilizing Optical Coherence Tomography and Artificial Intelligence for the Timely Identification of these Ocular Diseases

Journal of Community Medicine & Public Health (2024) Vol. 8, Iss. 3
Open Access | Times Cited: 1
Advanced Analysis of OCT/OCTA Images for Accurately Differentiating Between Glaucoma and Healthy Eyes Using Deep Learning Techniques
S POURJAVAN, François Gouverneur, Benoît Macq, et al.
Clinical ophthalmology (2024) Vol. Volume 18, pp. 3493-3502
Open Access | Times Cited: 1
A neural network model for predicting the effectiveness of treatment in patients with neovascular glaucoma associated with diabetes mellitus
Olga Volodymyrivna Guzun, O. Zadorozhnyy, Volodymyr Viktorovych Vychuzhanin, et al.
Romanian Journal of Ophthalmology (2024) Vol. 68, Iss. 3
Open Access
Vision Transformer-based Interpretable Metabolic Syndrome Classification Using Retinal Images
Kyung-Ah Sohn, Tae Kwan Lee, So Yeon Kim, et al.
Research Square (Research Square) (2024)
Open Access
Glaucoma detection based on fundus images using machine learning techniques
Sachin Jain, Dhas L. Panneer
i-manager s Journal on Information Technology (2024) Vol. 13, Iss. 4, pp. 1-1
Closed Access
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