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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:

Detection of Diabetic Retinopathy Using Bichannel Convolutional Neural Network
Shu‐I Pao, Hong-Zin Lin, Ke‐Hung Chien, et al.
Journal of Ophthalmology (2020) Vol. 2020, pp. 1-7
Open Access | Times Cited: 98

Showing 1-25 of 98 citing articles:

Deep learning for diabetic retinopathy detection and classification based on fundus images: A review
Nikos Tsiknakis, Dimitris Theodoropoulos, Georgios C. Manikis, et al.
Computers in Biology and Medicine (2021) Vol. 135, pp. 104599-104599
Open Access | Times Cited: 211
Deep Learning Techniques for Diabetic Retinopathy Classification: A Survey
Mohammad Atwany, Abdulwahab Sahyoun, Mohammad Yaqub
IEEE Access (2022) Vol. 10, pp. 28642-28655
Open Access | Times Cited: 153
NIMEQ-SACNet: A novel self-attention precision medicine model for vision-threatening diabetic retinopathy using image data
Anas Bilal, Xiaowen Liu, Muhammad Shafiq, et al.
Computers in Biology and Medicine (2024) Vol. 171, pp. 108099-108099
Closed Access | Times Cited: 47
Automated Detection and Diagnosis of Diabetic Retinopathy: A Comprehensive Survey
Vasudevan Lakshminarayanan, Hoda Kheradfallah, Arya Sarkar, et al.
Journal of Imaging (2021) Vol. 7, Iss. 9, pp. 165-165
Open Access | Times Cited: 87
Diabetic retinopathy classification based on multipath CNN and machine learning classifiers
S. Gayathri, Varun P. Gopi, P. Palanisamy
Physical and Engineering Sciences in Medicine (2021) Vol. 44, Iss. 3, pp. 639-653
Closed Access | Times Cited: 77
Hybrid Retinal Image Enhancement Algorithm for Diabetic Retinopathy Diagnostic Using Deep Learning Model
Saif Hameed Abbood, Haza Nuzly Abdull Hamed, Mohd Shafry Mohd Rahim, et al.
IEEE Access (2022) Vol. 10, pp. 73079-73086
Open Access | Times Cited: 67
Classification of diabetic retinopathy with feature selection over deep features using nature-inspired wrapper methods
Murat Canayaz
Applied Soft Computing (2022) Vol. 128, pp. 109462-109462
Closed Access | Times Cited: 59
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
Artificial Humming Bird Optimization–Based Hybrid CNN-RNN for Accurate Exudate Classification from Fundus Images
E. Dhiravidachelvi, Senthil Pandi S, R. Prabavathi, et al.
Journal of Digital Imaging (2022) Vol. 36, Iss. 1, pp. 59-72
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
Deep Learning and Medical Image Processing Techniques for Diabetic Retinopathy: A Survey of Applications, Challenges, and Future Trends
Posham Uppamma, Sweta Bhattacharya
Journal of Healthcare Engineering (2023) Vol. 2023, Iss. 1
Open Access | Times Cited: 26
Automated diabetic retinopathy severity grading using novel DR-ResNet + deep learning model
Samiya Majid Baba, Indu Bala, Gaurav Dhiman, et al.
Multimedia Tools and Applications (2024) Vol. 83, Iss. 28, pp. 71789-71831
Closed Access | Times Cited: 12
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: 10
Ensemble of multi-stage deep convolutional neural networks for automated grading of diabetic retinopathy using image patches
V. Deepa, C. Sathish Kumar, Thomas Cherian
Journal of King Saud University - Computer and Information Sciences (2021) Vol. 34, Iss. 8, pp. 6255-6265
Open Access | Times Cited: 44
Optimizing Deep Learning Model Parameters Using Socially Implemented IoMT Systems for Diabetic Retinopathy Classification Problem
Ashima Kukkar, Dinesh Gupta, Shehab Mohamed Beram, et al.
IEEE Transactions on Computational Social Systems (2022) Vol. 10, Iss. 4, pp. 1654-1665
Closed Access | Times Cited: 28
A systematic literature review of machine learning based risk prediction models for diabetic retinopathy progression
Tiwalade Modupe Usman, Yakub Kayode Saheed, Augustine Shey Nsang, et al.
Artificial Intelligence in Medicine (2023) Vol. 143, pp. 102617-102617
Closed Access | Times Cited: 16
Diabetic retinopathy detection using ensembled transfer learning based thrice CNN with SVM classifier
Neetha Merin Thomas, S. Albert Jerome
Multimedia Tools and Applications (2024) Vol. 83, Iss. 27, pp. 70089-70115
Closed Access | Times Cited: 7
Optical coherence tomography image based eye disease detection using deep convolutional neural network
Puneet, Rakesh Kumar, Meenu Gupta
Health Information Science and Systems (2022) Vol. 10, Iss. 1
Open Access | Times Cited: 27
Deep learning innovations in diagnosing diabetic retinopathy: The potential of transfer learning and the DiaCNN model
Mohamed R. Shoaib, Heba M. Emara, Jun Zhao, et al.
Computers in Biology and Medicine (2023) Vol. 169, pp. 107834-107834
Open Access | Times Cited: 13
Features extraction using encoded local binary pattern for detection and grading diabetic retinopathy
Mohamed A. Berbar
Health Information Science and Systems (2022) Vol. 10, Iss. 1
Open Access | Times Cited: 22
Diabetic Retinopathy: Detection and Classification Using AlexNet, GoogleNet and ResNet50 Convolutional Neural Networks
Jhonny Caicho, Cristina Chuya-Sumba, Nicole Jara, et al.
Communications in computer and information science (2022), pp. 259-271
Closed Access | Times Cited: 20
Classification of Diabetic Retinopathy Disease Levels by Extracting Topological Features Using Graph Neural Networks
Sumod Sundar, S. Sumathy
IEEE Access (2023) Vol. 11, pp. 51435-51444
Open Access | Times Cited: 12
Wavelet scattering transform application in classification of retinal abnormalities using OCT images
Zahra Baharlouei, Hossein Rabbani, Gerlind Plonka
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 11
Convolution Neural Networks for Disease Prediction: Applications and Challenges
Snowber Mushtaq, Omkar Singh
Scalable Computing Practice and Experience (2024) Vol. 25, Iss. 1, pp. 615-636
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
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