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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:

Hierarchical severity grade classification of non-proliferative diabetic retinopathy
Charu Bhardwaj, Shruti Jain, Meenakshi Sood
Journal of Ambient Intelligence and Humanized Computing (2020) Vol. 12, Iss. 2, pp. 2649-2670
Closed Access | Times Cited: 66

Showing 1-25 of 66 citing articles:

Improved Support Vector Machine based on CNN-SVD for vision-threatening diabetic retinopathy detection and classification
Anas Bilal, Azhar Imran, Talha Imtiaz Baig, et al.
PLoS ONE (2024) Vol. 19, Iss. 1, pp. e0295951-e0295951
Open Access | Times Cited: 49
Developments in the detection of diabetic retinopathy: a state-of-the-art review of computer-aided diagnosis and machine learning methods
Ganeshsree Selvachandran, Shio Gai Quek, Raveendran Paramesran, et al.
Artificial Intelligence Review (2022) Vol. 56, Iss. 2, pp. 915-964
Open Access | Times Cited: 53
An enhanced swarm optimization-based deep neural network for diabetic retinopathy classification in fundus images
A. Mary Dayana, W. R. Sam Emmanuel
Multimedia Tools and Applications (2022) Vol. 81, Iss. 15, pp. 20611-20642
Closed Access | Times Cited: 38
EdgeSVDNet: 5G-Enabled Detection and Classification of Vision-Threatening Diabetic Retinopathy in Retinal Fundus Images
Anas Bilal, Xiaowen Liu, Talha Imtiaz Baig, et al.
Electronics (2023) Vol. 12, Iss. 19, pp. 4094-4094
Open Access | Times Cited: 38
Automatic Classification of Colour Fundus Images for Prediction Eye Disease Types Based on Hybrid Features
Ahlam Shamsan, Ebrahim Mohammed Senan, Hamzeh Salameh Ahmad Shatnawi
Diagnostics (2023) Vol. 13, Iss. 10, pp. 1706-1706
Open Access | Times Cited: 29
Automatic detection of non-proliferative diabetic retinopathy in retinal fundus images using convolution neural network
P. Saranya, S. Prabakaran
Journal of Ambient Intelligence and Humanized Computing (2020)
Closed Access | Times Cited: 63
Transfer learning based robust automatic detection system for diabetic retinopathy grading
Charu Bhardwaj, Shruti Jain, Meenakshi Sood
Neural Computing and Applications (2021) Vol. 33, Iss. 20, pp. 13999-14019
Closed Access | Times Cited: 53
Machine Learning Methods for Diagnosis of Eye-Related Diseases: A Systematic Review Study Based on Ophthalmic Imaging Modalities
Qaisar Abbas, Imran Qureshi, Junhua Yan, et al.
Archives of Computational Methods in Engineering (2022) Vol. 29, Iss. 6, pp. 3861-3918
Closed Access | Times Cited: 28
A Hybrid Technique for Diabetic Retinopathy Detection Based on Ensemble-Optimized CNN and Texture Features
Uzair Ishtiaq, Erma Rahayu Mohd Faizal Abdullah, Zubair Ishtiaque
Diagnostics (2023) Vol. 13, Iss. 10, pp. 1816-1816
Open Access | Times Cited: 17
Deep learning model using classification for diabetic retinopathy detection: an overview
Dharmalingam Muthusamy, Parimala Palani
Artificial Intelligence Review (2024) Vol. 57, Iss. 7
Open Access | Times Cited: 7
DeepSVDNet: A Deep Learning-Based Approach for Detecting and Classifying Vision-Threatening Diabetic Retinopathy in Retinal Fundus Images
Anas Bilal, Azhar Imran, Talha Imtiaz Baig, et al.
Computer Systems Science and Engineering (2024) Vol. 48, Iss. 2, pp. 511-528
Open Access | Times Cited: 6
A novel four-step feature selection technique for diabetic retinopathy grading
N Jagan Mohan, R. Murugan, Tripti Goel, et al.
Physical and Engineering Sciences in Medicine (2021) Vol. 44, Iss. 4, pp. 1351-1366
Closed Access | Times Cited: 34
Deep learning enabled optimized feature selection and classification for grading diabetic retinopathy severity in the fundus image
A. Mary Dayana, W. R. Sam Emmanuel
Neural Computing and Applications (2022) Vol. 34, Iss. 21, pp. 18663-18683
Closed Access | Times Cited: 25
Comparative study of different machine learning models for automatic diabetic retinopathy detection using fundus image
Shubhi Gupta, Sanjeev Thakur, Ashutosh Gupta
Multimedia Tools and Applications (2023) Vol. 83, Iss. 12, pp. 34291-34322
Closed Access | Times Cited: 14
A Lightweight Diabetic Retinopathy Detection Model Using a Deep-Learning Technique
Abdul Rahaman Wahab Sait
Diagnostics (2023) Vol. 13, Iss. 19, pp. 3120-3120
Open Access | Times Cited: 14
Localization and grading of NPDR lesions using ResNet-18-YOLOv8 model and informative features selection for DR classification based on transfer learning
Javeria Amin, Irum Shazadi, Muhammad Sharif, et al.
Heliyon (2024) Vol. 10, Iss. 10, pp. e30954-e30954
Open Access | Times Cited: 4
Classification of diabetic retinopathy grades using CNN feature extraction to segment the lesion
M. Swathi, S. Venkata Lakshmi
International Journal of Computational and Experimental Science and Engineering (2024) Vol. 10, Iss. 4
Open Access | Times Cited: 4
A hybrid model for diabetic retinopathy and diabetic macular edema severity grade classification
A. S. Sabeena, M. K. Jeyakumar
International Journal of Diabetes in Developing Countries (2025)
Closed Access
D-GET: Group-Enhanced Transformer for Diabetic Retinopathy Severity Classification in Fundus Fluorescein Angiography
Xina Liu, Jun Xie, Junjun Hou, et al.
Journal of Medical Systems (2025) Vol. 49, Iss. 1
Closed Access
Fused information of DeepLabv3+ and transfer learning model for semantic segmentation and rich features selection using equilibrium optimizer (EO) for classification of NPDR lesions
Javeria Amin, Muhammad Almas Anjum, M. A. Malik
Knowledge-Based Systems (2022) Vol. 249, pp. 108881-108881
Closed Access | Times Cited: 18
Image Processing and Machine Learning-Based Classification and Detection of Liver Tumor
V. Durga Prasad Jasti, Prasad Enagandula, Manish Sawale, et al.
BioMed Research International (2022) Vol. 2022, pp. 1-7
Open Access | Times Cited: 16
GO-DBN: Gannet Optimized Deep Belief Network Based wavelet kernel ELM for Detection of Diabetic Retinopathy
S.G. Krishnamoorthy, YU Wei-feng, Jin Luo, et al.
Expert Systems with Applications (2023) Vol. 229, pp. 120408-120408
Closed Access | Times Cited: 9
Deep long and short term memory based Red Fox optimization algorithm for diabetic retinopathy detection and classification
R. Pugal Priya, Thankamony Saradadevi Sivarani, A. Gnana Saravanan
International Journal for Numerical Methods in Biomedical Engineering (2021) Vol. 38, Iss. 3
Closed Access | Times Cited: 22
CT Image Segmentation Method of Liver Tumor Based on Artificial Intelligence Enabled Medical Imaging
Liping Liu, Lin Wang, Dan Xu, et al.
Mathematical Problems in Engineering (2021) Vol. 2021, pp. 1-8
Open Access | Times Cited: 21
Feature fusion and optimization integrated refined deep residual network for diabetic retinopathy severity classification using fundus image
A. Mary Dayana, W. R. Sam Emmanuel, C. Harriet Linda
Multimedia Systems (2023) Vol. 29, Iss. 3, pp. 1629-1650
Closed Access | Times Cited: 8
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