Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

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 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

Showing 1-25 of 211 citing articles:

A survey on deep learning tools dealing with data scarcity: definitions, challenges, solutions, tips, and applications
Laith Alzubaidi, Jinshuai Bai, Aiman Al-Sabaawi, et al.
Journal Of Big Data (2023) Vol. 10, Iss. 1
Open Access | Times Cited: 337
Application of generative adversarial networks (GAN) for ophthalmology image domains: a survey
Aram You, Jin Kuk Kim, Ik Hee Ryu, et al.
Eye and Vision (2022) Vol. 9, Iss. 1
Open Access | Times Cited: 139
Automatic Diagnosis of Glaucoma from Retinal Images Using Deep Learning Approach
Ayesha Shoukat, Shahzad Akbar, Syed Ale Hassan, et al.
Diagnostics (2023) Vol. 13, Iss. 10, pp. 1738-1738
Open Access | Times Cited: 43
A Lesion-Based Diabetic Retinopathy Detection Through Hybrid Deep Learning Model
Ayesha Jabbar, Hannan Bin Liaqat, Aftab Akram, et al.
IEEE Access (2024) Vol. 12, pp. 40019-40036
Open Access | Times Cited: 24
Artificial intelligence for diabetic retinopathy detection: A systematic review
Archana Senapati, Hrudaya Kumar Tripathy, Vandana Sharma, et al.
Informatics in Medicine Unlocked (2024) Vol. 45, pp. 101445-101445
Open Access | Times Cited: 16
The development of “automated visual evaluation” for cervical cancer screening: The promise and challenges in adapting deep‐learning for clinical testing
Kanan Desai, Brian Befano, Zhiyun Xue, et al.
International Journal of Cancer (2021) Vol. 150, Iss. 5, pp. 741-752
Open Access | Times Cited: 59
Diagnosis of Retinal Diseases Based on Bayesian Optimization Deep Learning Network Using Optical Coherence Tomography Images
Malliga Subramanian, Sandeep Kumar Mathivanan, Sathishkumar Veerappampalayam Easwaramoorthy, et al.
Computational Intelligence and Neuroscience (2022) Vol. 2022, pp. 1-15
Open Access | Times Cited: 52
Hinge attention network: A joint model for diabetic retinopathy severity grading
Nagur Shareef Shaik, Teja Krishna Cherukuri
Applied Intelligence (2022) Vol. 52, Iss. 13, pp. 15105-15121
Closed Access | Times Cited: 43
Triple-DRNet: A triple-cascade convolution neural network for diabetic retinopathy grading using fundus images
Muwei Jian, Hongyu Chen, Tao Chen, et al.
Computers in Biology and Medicine (2023) Vol. 155, pp. 106631-106631
Closed Access | Times Cited: 40
Artificial Intelligence for Diabetic Retinopathy Screening Using Color Retinal Photographs: From Development to Deployment
Andrzej Grzybowski, Panisa Singhanetr, Onnisa Nanegrungsunk, et al.
Ophthalmology and Therapy (2023) Vol. 12, Iss. 3, pp. 1419-1437
Open Access | Times Cited: 28
Vision Transformer Model for Predicting the Severity of Diabetic Retinopathy in Fundus Photography-Based Retina Images
Waleed Nazih, Ahmad O. Aseeri, Osama Youssef Atallah, et al.
IEEE Access (2023) Vol. 11, pp. 117546-117561
Open Access | Times Cited: 24
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: 23
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
CRA-Net: Transformer guided category-relation attention network for diabetic retinopathy grading
Feng Zang, Hui Ma
Computers in Biology and Medicine (2024) Vol. 170, pp. 107993-107993
Closed Access | Times Cited: 9
Benchmarking Deep Learning Frameworks for Automated Diagnosis of Ocular Toxoplasmosis: A Comprehensive Approach to Classification and Segmentation
Syed Samiul Alam, Samiul Based Shuvo, Shams Nafisa Ali, et al.
IEEE Access (2024) Vol. 12, pp. 22759-22777
Open Access | Times Cited: 8
Diagnosis of Diabetic Retinopathy through Retinal Fundus Images and 3D Convolutional Neural Networks with Limited Number of Samples
Ahsan Bin Tufail, Inam Ullah, Wali Ullah Khan, et al.
Wireless Communications and Mobile Computing (2021) Vol. 2021, Iss. 1
Open Access | Times Cited: 50
A New Approach for Detecting Fundus Lesions Using Image Processing and Deep Neural Network Architecture Based on YOLO Model
Carlos Santos, Marílton Sanchotene de Aguiar, Daniel Welfer, et al.
Sensors (2022) Vol. 22, Iss. 17, pp. 6441-6441
Open Access | Times Cited: 36
Nailfold capillaroscopy and deep learning in diabetes
Reema Shah, Jeremy Petch, Walter Nelson, et al.
Journal of Diabetes (2023) Vol. 15, Iss. 2, pp. 145-151
Open Access | Times Cited: 18
Geometric Correspondence-Based Multimodal Learning for Ophthalmic Image Analysis
Yan Wang, Liangli Zhen, Tien‐En Tan, et al.
IEEE Transactions on Medical Imaging (2024) Vol. 43, Iss. 5, pp. 1945-1957
Closed Access | Times Cited: 7
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
Implementing and evaluating a fully functional AI-enabled model for chronic eye disease screening in a real clinical environment
Christos Skevas, Nicolás Pérez de Olaguer, Albert Lleó, et al.
BMC Ophthalmology (2024) Vol. 24, Iss. 1
Open Access | Times Cited: 7
A systematic review of economic evaluation of artificial intelligence-based screening for eye diseases: From possibility to reality
Hongkang Wu, Kai Jin, Chee Chew Yip, et al.
Survey of Ophthalmology (2024) Vol. 69, Iss. 4, pp. 499-507
Open Access | Times Cited: 7
VisionDeep-AI: Deep learning-based retinal blood vessels segmentation and multi-class classification framework for eye diagnosis
Rakesh Chandra Joshi, Anuj Kumar Sharma, Malay Kishore Dutta
Biomedical Signal Processing and Control (2024) Vol. 94, pp. 106273-106273
Closed Access | Times Cited: 7
Deep learning for personalized health monitoring and prediction: A review
Robertas Damaševičius, Senthil Kumar Jagatheesaperumal, Kandala N. V. P. S. Rajesh, et al.
Computational Intelligence (2024) Vol. 40, Iss. 3
Open Access | Times Cited: 7
Using Deep Learning to Segment Retinal Vascular Leakage and Occlusion in Retinal Vasculitis
Dhanach Dhirachaikulpanich, Jianyang Xie, Xiuju Chen, et al.
Ocular Immunology and Inflammation (2024), pp. 1-8
Open Access | Times Cited: 6
Page 1 - Next Page

Scroll to top