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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:

Deep Learning for Diabetic Retinopathy Analysis: A Review, Research Challenges, and Future Directions
Muhammad Waqas Nadeem, Hock Guan Goh, Muzammil Hussain, et al.
Sensors (2022) Vol. 22, Iss. 18, pp. 6780-6780
Open Access | Times Cited: 50

Showing 26-50 of 50 citing articles:

Early Detection of Diabetic Foot Ulcers through Wearable Shoe Design
Vikneswaran Vijean, Syakirah Afiza Mohammed, Razi Ahmad, et al.
(2022), pp. 1-5
Closed Access | Times Cited: 3
Diabetic Retinopathy Detection using Deep Learning
Deepak Mane
Deleted Journal (2024) Vol. 19, Iss. 2, pp. 18-27
Open Access
Stationary wavelet transform and SpinalNet trained light spectrum Tasmanian devil optimization enabled DR detection using fundus images
Mubin Tamboli, Amol Dhumane, Rajesh S. Prasad, et al.
Multimedia Tools and Applications (2024)
Closed Access
Diabetic Retinopathy Detection Using Real-World Datasets of Fundus Images
Raksheet Jain, Drashti Magia, J. Joy
Lecture notes in networks and systems (2024), pp. 149-169
Closed Access
Detection of Diabetic Retinopathy (DR) Severity from Fundus Photographs using Conv-ViT
Dheeraj Chintamreddy, Usha Rani Seshasayee
(2024), pp. 1-6
Closed Access
Diabetic retinopathy classification using improved metaheuristics with deep residual network on fundus imaging
R. Ramesh, S. Sathiamoorthy
Multimedia Tools and Applications (2024)
Closed Access
A Novel Classification Approach for Retinal Disease Using Improved Gannet Optimization‐Based Capsule DenseNet
S. Venkatesan, M. Kempanna, J Nagaraja, et al.
International Journal of Imaging Systems and Technology (2024) Vol. 34, Iss. 5
Closed Access
Color Fundus Photography and Deep Learning Applications in Alzheimer’s Disease
Oana M. Dumitrascu, Xin Li, Wenhui Zhu, et al.
Mayo Clinic Proceedings Digital Health (2024) Vol. 2, Iss. 4, pp. 548-558
Open Access
Computationally efficient deep learning models for diabetic retinopathy detection: a systematic literature review
Nazeef Ul Haq, Talha Waheed, Kashif Ishaq, et al.
Artificial Intelligence Review (2024) Vol. 57, Iss. 11
Open Access
Multiresolution cascaded attention U-Net for localization and segmentation of optic disc and fovea in fundus images
Rajaram Shalini, Varun P. Gopi
Scientific Reports (2024) Vol. 14, Iss. 1
Open Access
Detection of diabetic retinopathy using deep learning methods
Bilal A. Ozturk, Heba Emad Namiq, Hussein Ali Rasool, et al.
Intelligent Decision Technologies (2024), pp. 1-18
Closed Access
Artificial intelligence in fracture detection on radiographs: a literature review
Antonio Lo Mastro, Enrico Grassi, Daniela Berritto, et al.
Japanese Journal of Radiology (2024)
Closed Access
Mathematical model for assessing the functional state of human eye parameters
Vladimir Vychuzhanin, Alexey Vychuzhanin, O. Guzun, et al.
Reporter of the Priazovskyi State Technical University Section Technical sciences (2024) Vol. 1, Iss. 49, pp. 6-16
Open Access
Applying a convolutional neural network as a statistical method to evaluate the correlation between diabetic retinopathy and diabetic nephropathy
Tao Li, Juan Tang, Jiayou Gao, et al.
Research Square (Research Square) (2023)
Open Access | Times Cited: 1
A combined fuzzy backtracking search optimization algorithm to localize retinal blood vessels for diabetic retinopathy
Anil Kumar Neelapala, Gnane Swarnadh Satapathi, Vamsi Borra, et al.
Biomedical Physics & Engineering Express (2023) Vol. 9, Iss. 5, pp. 055025-055025
Closed Access | Times Cited: 1
Optical system based data classification for diabetes retinopathy detection using machine language with artificial intelligence
Suraj Malik, Sudharsanan Srinivasan, Chandra Shekhar Rajora, et al.
Optical and Quantum Electronics (2023) Vol. 55, Iss. 10
Closed Access | Times Cited: 1
Deep Learning-Based Diabetic Retinopathy Detection Using ResNet34 Model
K. Anugirba, Lal Raja Singh R
(2023), pp. 225-228
Closed Access | Times Cited: 1
Empowering Rural Healthcare: MobileNet-Driven Deep Learning for Early Diabetic Retinopathy Detection in Nepal
Saurav Dev Bhatta
Journal of Electronics Electromedical Engineering and Medical Informatics (2023) Vol. 5, Iss. 4
Open Access | Times Cited: 1
EfficientNetV2 for Quality Estimation of Diabetic Retinopathy Images from DeepDRiD
Sudhakar Tummala
Research Square (Research Square) (2022)
Open Access | Times Cited: 1
Detecting Severity of Diabetic Retina by Functional Learning with Image Processing Techniques
A. Deepak Kumar, T. Sasipraba
Indian Journal of Computer Science and Engineering (2023) Vol. 14, Iss. 1, pp. 94-104
Open Access
Contextual Augmentation Based on Metric-Guided Features for Ocular Axial Length Prediction
Yeonwoo Jeong, Jae‐Ho Han, Jaeryung Oh
Mathematics (2023) Vol. 11, Iss. 13, pp. 3021-3021
Open Access
Validation of Automatic Diabetic Retinopathy Screening and Diagnosis via Deep Neural Networks on Multi-modal Retinal Fundus Image Datasets
Jixiang Guo, Xiang Li, Wei Zhang, et al.
(2023), pp. 834-840
Closed Access
Preserving sight: Managing and preventing diabetic retinopathy
Mohd Altaf Dar, Mudasir Maqbool, Irfat Ara, et al.
Open Health (2023) Vol. 4, Iss. 1
Open Access
Advancing Diabetic Retinopathy Diagnosis: Leveraging Optical Coherence Tomography Imaging with Convolutional Neural Networks
Kamil Yavuzer, Mehmet Çıtırık, Beyza Yavuzer
Romanian Journal of Ophthalmology (2023) Vol. 67, Iss. 4
Open Access
Comparing the Clinical Viability of Automated Fundus Image Segmentation Methods
Gorana Gojić, Veljko Petrović, Дину Драган, et al.
Sensors (2022) Vol. 22, Iss. 23, pp. 9101-9101
Open Access
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