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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:

Identification of glaucoma from fundus images using deep learning techniques
JohnD Akkara, S. Ajitha, M. V. Judy
Indian Journal of Ophthalmology (2021) Vol. 69, Iss. 10, pp. 2702-2709
Open Access | Times Cited: 51

Showing 1-25 of 51 citing articles:

Deep learning-based classification network for glaucoma in retinal images
Mamta Juneja, Sarthak Thakur, Archit Uniyal, et al.
Computers & Electrical Engineering (2022) Vol. 101, pp. 108009-108009
Closed Access | Times Cited: 43
En‐ConvNet: A novel approach for glaucoma detection from color fundus images using ensemble of deep convolutional neural networks
Poonguzhali Elangovan, Malaya Kumar Nath
International Journal of Imaging Systems and Technology (2022) Vol. 32, Iss. 6, pp. 2034-2048
Closed Access | Times Cited: 42
Artificial intelligence and machine learning in ophthalmology: A review
Ojas Srivastava, Matthew Tennant, Parampal S. Grewal, et al.
Indian Journal of Ophthalmology (2022) Vol. 71, Iss. 1, pp. 11-17
Open Access | Times Cited: 39
Multi-stage glaucoma classification using pre-trained convolutional neural networks and voting-based classifier fusion
Vijaya Kumar Velpula, Lakhan Dev Sharma
Frontiers in Physiology (2023) Vol. 14
Open Access | Times Cited: 36
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 | Times Cited: 1
Artificial intelligence in glaucoma: opportunities, challenges, and future directions
Xiaoqin Huang, Md Rafiqul Islam, Shanjita Akter, et al.
BioMedical Engineering OnLine (2023) Vol. 22, Iss. 1
Open Access | Times Cited: 16
The AI Revolution in Glaucoma: Bridging Challenges with Opportunities
Fei Li, Biao Wang, Zefeng Yang, et al.
Progress in Retinal and Eye Research (2024) Vol. 103, pp. 101291-101291
Closed Access | Times Cited: 6
AlterNet-K: a small and compact model for the detection of glaucoma
G. I. D'souza, P. C. Siddalingaswamy, Mayur Pandya
Biomedical Engineering Letters (2023) Vol. 14, Iss. 1, pp. 23-33
Open Access | Times Cited: 13
AI-Driven Predictive Analytics
Olivia Jana, Shivnath Ghosh
Advances in medical technologies and clinical practice book series (2025), pp. 181-214
Closed Access
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: 11
Recognition of Glaucomatous Fundus Images Using Machine Learning Methods Based on Optic Nerve Head Topographic Features
Chaowei Wu, Tzu-Yu Huang, Yeong‐Cheng Liou, et al.
Journal of Glaucoma (2024) Vol. 33, Iss. 8, pp. 601-606
Closed Access | Times Cited: 4
DeB5-XNet: An explainable ensemble model for ocular disease classification using feature extraction and Grad-CAM
Geethanjali Kher, Suyash Mehra Mehra, Rajni Bala, et al.
Informatics in Medicine Unlocked (2025), pp. 101632-101632
Open Access
Automatic Detection of Glaucoma from Retinal Fundus Images Using Convolutional Neural Network Model, Xception
Smita Das, Madhusudhan Mishra, Swanirbhar Majumder
(2025), pp. 195-204
Closed Access
Cloud-Based Optimized Deep Learning Framework for Automated Glaucoma Detection Using Stationary Wavelet Transform and Improved Grey-Wolf-Optimization with ELM Approach
Debendra Muduli, Syed Irfan Yaqoob, Santosh Kumar Sharma, et al.
Results in Engineering (2025), pp. 104682-104682
Open Access
Review of Visualization Approaches in Deep Learning Models of Glaucoma
Byoungyoung Gu, Sophia Sidhu, Robert N. Weinreb, et al.
Asia-Pacific Journal of Ophthalmology (2023) Vol. 12, Iss. 4, pp. 392-401
Open Access | Times Cited: 9
Glaucoma Detection Using Explainable AI and Deep Learning
Najeeba Afreen, Rajanikanth Aluvalu
EAI Endorsed Transactions on Pervasive Health and Technology (2024) Vol. 10
Open Access | Times Cited: 2
Precision Diagnosis of Glaucoma with VLLM Ensemble Deep Learning
Soohyun Wang, Byoungkug Kim, Jiheon Kang, et al.
Applied Sciences (2024) Vol. 14, Iss. 11, pp. 4588-4588
Open Access | Times Cited: 2
Improved swarm optimization of deep features for glaucoma classification using SEGSO and VGGNet
Kishore Balasubramanian, K. C. Ramya, K. Gayathri Devi
Biomedical Signal Processing and Control (2022) Vol. 77, pp. 103845-103845
Closed Access | Times Cited: 10
Comparison between Deep-Learning-Based Ultra-Wide-Field Fundus Imaging and True-Colour Confocal Scanning for Diagnosing Glaucoma
Younji Shin, Hyunsoo Cho, Yong Un Shin, et al.
Journal of Clinical Medicine (2022) Vol. 11, Iss. 11, pp. 3168-3168
Open Access | Times Cited: 8
Visual Field Prediction for Fundus Image with Generative AI
Honggu Kang, Seonghyeon Ko, J.-H. Kim, et al.
2023 17th International Conference on Ubiquitous Information Management and Communication (IMCOM) (2024), pp. 1-3
Closed Access | Times Cited: 1
Topo-Net: Retinal Image Analysis with Topological Deep Learning
Faisal Ahmed, Baris Coskunuzer
medRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 1
A Vision Transformer Approach to Fundus Image Classification
Danilo Rangel Arruda Leite, José Camara, João M. F. Rodrigues, et al.
Wireless Mobile Communication and Healthcare (2024), pp. 151-162
Closed Access | Times Cited: 1
DeB5-XNet: An Explainable Ensemble Model for Ocular Disease Classification using Transfer Learning and Grad-CAM
Geethanjali Kher, Suyash Mehra Mehra, Rajni Bala, et al.
Authorea (Authorea) (2024)
Open Access | Times Cited: 1
Beyond human perception: Revolutionizing ophthalmology with artificial intelligence and deep learning
Asma Jabeen
Journal of Clinical Ophthalmology and Research (2024) Vol. 12, Iss. 3, pp. 287-292
Open Access | Times Cited: 1
Advancements in Deep Learning for Automated Diagnosis of Ophthalmic Diseases: A Comprehensive Review
Soubhagya Kumar Dash, Prabira Kumar Sethy, Ashis Das, et al.
IEEE Access (2024) Vol. 12, pp. 171221-171240
Open Access | Times Cited: 1
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