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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:

Applying supervised contrastive learning for the detection of diabetic retinopathy and its severity levels from fundus images
Md. Robiul Islam, Lway Faisal Abdulrazak, Md. Nahiduzzaman, et al.
Computers in Biology and Medicine (2022) Vol. 146, pp. 105602-105602
Open Access | Times Cited: 88

Showing 1-25 of 88 citing articles:

Medical image data augmentation: techniques, comparisons and interpretations
Evgin Göçeri
Artificial Intelligence Review (2023) Vol. 56, Iss. 11, pp. 12561-12605
Open Access | Times Cited: 158
On the Analyses of Medical Images Using Traditional Machine Learning Techniques and Convolutional Neural Networks
Saeed Iqbal, Adnan N. Qureshi, Jianqiang Li, et al.
Archives of Computational Methods in Engineering (2023) Vol. 30, Iss. 5, pp. 3173-3233
Open Access | Times Cited: 78
Development of revised ResNet-50 for diabetic retinopathy detection
Chun‐Ling Lin, Kun-Chi Wu
BMC Bioinformatics (2023) Vol. 24, Iss. 1
Open Access | Times Cited: 42
Artificial Intelligence (AI) for Early Diagnosis of Retinal Diseases
Uday Pratap Singh Parmar, Pier Luigi Surico, Rohan Bir Singh, et al.
Medicina (2024) Vol. 60, Iss. 4, pp. 527-527
Open Access | Times Cited: 19
Uncertainty-aware diabetic retinopathy detection using deep learning enhanced by Bayesian approaches
Muhammad Usman Akram, Muhammad Adnan, Syed Farooq Ali, et al.
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access | Times Cited: 1
Analysis of Diabetic Retinopathy (DR) Based on the Deep Learning
Abdul Muiz Fayyaz, Muhammad Imran Sharif, Sami Azam, et al.
Information (2023) Vol. 14, Iss. 1, pp. 30-30
Open Access | Times Cited: 38
A novel deep transfer learning based computerized diagnostic Systems for Multi-class imbalanced diabetic retinopathy severity classification
Richa Vij, Sakshi Arora
Multimedia Tools and Applications (2023) Vol. 82, Iss. 22, pp. 34847-34884
Closed Access | Times Cited: 27
Multi-Level severity classification for diabetic retinopathy based on hybrid optimization enabled deep learning
S. Zulaikha Beevi
Biomedical Signal Processing and Control (2023) Vol. 84, pp. 104736-104736
Closed Access | Times Cited: 21
A novel framework for lung cancer classification using lightweight convolutional neural networks and ridge extreme learning machine model with SHapley Additive exPlanations (SHAP)
Md. Nahiduzzaman, Lway Faisal Abdulrazak, Mohamed Arselene Ayari, et al.
Expert Systems with Applications (2024) Vol. 248, pp. 123392-123392
Closed Access | Times Cited: 12
A deep integrative approach for diabetic retinopathy classification with synergistic channel-spatial and self-attention mechanism
Sandeep Madarapu, Samit Ari, Kamalakanta Mahapatra
Expert Systems with Applications (2024) Vol. 249, pp. 123523-123523
Closed Access | Times Cited: 12
Diabetic Retinopathy Classification With Deep Learning via Fundus Images: A Short Survey
Shanshan Zhu, Changchun Xiong, Qingshan Zhong, et al.
IEEE Access (2024) Vol. 12, pp. 20540-20558
Open Access | Times Cited: 11
Dual branch deep learning network for detection and stage grading of diabetic retinopathy
Hossein Shakibania, Sina Raoufi, Behnam Pourafkham, et al.
Biomedical Signal Processing and Control (2024) Vol. 93, pp. 106168-106168
Open Access | Times Cited: 8
Diabetic retinopathy prediction based on vision transformer and modified capsule network
Mohammed Oulhadj, Jamal Riffi, Chaimae Khodriss, et al.
Computers in Biology and Medicine (2024) Vol. 175, pp. 108523-108523
Closed Access | Times Cited: 8
Attention-Driven Cascaded Network for Diabetic Retinopathy Grading from Fundus Images
Guanghui Yue, Yuan Li, Tianwei Zhou, et al.
Biomedical Signal Processing and Control (2022) Vol. 80, pp. 104370-104370
Closed Access | Times Cited: 29
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
A multi-resolution convolutional attention network for efficient diabetic retinopathy classification
Sandeep Madarapu, Samit Ari, Kamalakanta Mahapatra
Computers & Electrical Engineering (2024) Vol. 117, pp. 109243-109243
Closed Access | Times Cited: 5
Bayesian Deep Learning Applied to Diabetic Retinopathy with Uncertainty Quantification
Masoud Muhammed Hassan, Halbast Rashid Ismail
Heliyon (2025) Vol. 11, Iss. 2, pp. e41802-e41802
Open Access
Retinopathy Disease Detection and Classification Using a Coordinate Attention Module-Based Convolutional Neural Network with Leaky Rectified Linear Unit
Pravin Balaso Chopade, Prabhakar N. Kota, B. D. Jadhav, et al.
IIUM Engineering Journal (2025) Vol. 26, Iss. 1, pp. 129-147
Open Access
DR-ConvNeXt: DR classification method for reconstructing ConvNeXt model structure
Pengfei Song, Yun Wu
Journal of X-Ray Science and Technology (2025)
Closed Access
Artificial Intelligence for Glaucoma and Diabetic Retinopathy: A Review
Karanbir Singh Grover, Nitika Kapoor
Lecture notes in networks and systems (2025), pp. 217-227
Closed Access
Dual-stage dynamic hierarchical attention framework for saliency-aware explainable diabetic retinopathy grading
Shilpa Elsa Abraham, Binsu C. Kovoor
Engineering Applications of Artificial Intelligence (2025) Vol. 148, pp. 110364-110364
Closed Access
Diabetic Retinopathy Prediction Based on Wavelet Decomposition and Modified Capsule Network
Mohammed Oulhadj, Jamal Riffi, Chaimae Khodriss, et al.
Journal of Digital Imaging (2023) Vol. 36, Iss. 4, pp. 1739-1751
Closed Access | Times Cited: 13
Reliable and Energy-Efficient Diabetic Retinopathy Screening Using Memristor-Based Neural Networks
Sumit Diware, Koteswararao Chilakala, Rajiv Joshi, et al.
IEEE Access (2024) Vol. 12, pp. 47469-47482
Open Access | Times Cited: 4
Deep hybrid architecture with stacked ensemble learning for binary classification of retinal disease
C. Priyadharsini, Asnath Victy Phamila Y
Results in Engineering (2024), pp. 103219-103219
Open Access | Times Cited: 4
Fine-grained attention & knowledge-based collaborative network for diabetic retinopathy grading
Miao Tian, Hongqiu Wang, Yingxue Sun, et al.
Heliyon (2023) Vol. 9, Iss. 7, pp. e17217-e17217
Open Access | Times Cited: 10
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