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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:

Artificial intelligence for diabetic retinopathy screening, prediction and management
Dinesh Visva Gunasekeran, Daniel Shu Wei Ting, Gavin Siew Wei Tan, et al.
Current Opinion in Ophthalmology (2020) Vol. 31, Iss. 5, pp. 357-365
Closed Access | Times Cited: 106

Showing 1-25 of 106 citing articles:

Metaverse and Virtual Health Care in Ophthalmology: Opportunities and Challenges
Ting Fang Tan, Yong Li, Jane Lim, et al.
Asia-Pacific Journal of Ophthalmology (2022) Vol. 11, Iss. 3, pp. 237-246
Open Access | Times Cited: 144
Digital health during COVID-19: lessons from operationalising new models of care in ophthalmology
Dinesh Visva Gunasekeran, Yih‐Chung Tham, Daniel Shu Wei Ting, et al.
The Lancet Digital Health (2021) Vol. 3, Iss. 2, pp. e124-e134
Open Access | Times Cited: 134
A deep learning system for predicting time to progression of diabetic retinopathy
Ling Dai, Bin Sheng, Ting‐Li Chen, et al.
Nature Medicine (2024)
Open Access | Times Cited: 94
Automatic interpretation and clinical evaluation for fundus fluorescein angiography images of diabetic retinopathy patients by deep learning
Zhiyuan Gao, Xiangji Pan, Ji Shao, et al.
British Journal of Ophthalmology (2022) Vol. 107, Iss. 12, pp. 1852-1858
Closed Access | Times Cited: 72
Integrated image-based deep learning and language models for primary diabetes care
Jiajia Li, Zhouyu Guan, Jing Wang, et al.
Nature Medicine (2024) Vol. 30, Iss. 10, pp. 2886-2896
Open Access | Times Cited: 38
Bone marrow mesenchymal stem cells-induced exosomal microRNA-486-3p protects against diabetic retinopathy through TLR4/NF-κB axis repression
W. Li, Longyu Jin, Yue Cui, et al.
Journal of Endocrinological Investigation (2020) Vol. 44, Iss. 6, pp. 1193-1207
Closed Access | Times Cited: 76
Diabetic Retinopathy in the Aging Population: A Perspective of Pathogenesis and Treatment
Sameer P. Leley, Thomas A. Ciulla, Ashay D. Bhatwadekar
Clinical Interventions in Aging (2021) Vol. Volume 16, pp. 1367-1378
Open Access | Times Cited: 69
Artificial intelligence: the unstoppable revolution in ophthalmology
David Benet, Óscar J. Pellicer-Valero
Survey of Ophthalmology (2021) Vol. 67, Iss. 1, pp. 252-270
Open Access | Times Cited: 67
Diabetic Retinopathy Detection Using Deep Learning Methods
S. Suganyadevi, K. Renuka Devi, K. Balasamy, et al.
2022 First International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT) (2022), pp. 1-6
Closed Access | Times Cited: 40
Grand Challenges in global eye health: a global prioritisation process using Delphi method
Jacqueline Ramke, Jennifer Evans, Esmael Habtamu, et al.
The Lancet Healthy Longevity (2022) Vol. 3, Iss. 1, pp. e31-e41
Open Access | Times Cited: 38
Artificial intelligence in diabetic retinopathy: Bibliometric analysis
Tahmina Nasrin Poly, Md. Mohaimenul Islam, Bruno Walther, et al.
Computer Methods and Programs in Biomedicine (2023) Vol. 231, pp. 107358-107358
Closed Access | Times Cited: 37
Artificial intelligence performance in detecting lymphoma from medical imaging: a systematic review and meta-analysis
Anying Bai, Mingyu Si, Peng Xue, et al.
BMC Medical Informatics and Decision Making (2024) Vol. 24, Iss. 1
Open Access | Times Cited: 14
Digital Health Solutions for Mental Health Disorders During COVID-19
Alton Chew, Ryan Ong, Hsien-Hsien Lei, et al.
Frontiers in Psychiatry (2020) Vol. 11
Open Access | Times Cited: 56
Automated microaneurysms detection for early diagnosis of diabetic retinopathy: A Comprehensive review
Veena Mayya, S. Sowmya Kamath, Uma Kulkarni
Computer Methods and Programs in Biomedicine Update (2021) Vol. 1, pp. 100013-100013
Open Access | Times Cited: 48
Artificial intelligence in screening, diagnosis, and classification of diabetic macular edema: A systematic review
Mohammad Hasan Shahriari, Hamideh Sabbaghi, Farkhondeh Asadi, et al.
Survey of Ophthalmology (2022) Vol. 68, Iss. 1, pp. 42-53
Closed Access | Times Cited: 34
Acceptance and Perception of Artificial Intelligence Usability in Eye Care (APPRAISE) for Ophthalmologists: A Multinational Perspective
Dinesh Visva Gunasekeran, Feihui Zheng, Gilbert Yong San Lim, et al.
Frontiers in Medicine (2022) Vol. 9
Open Access | Times Cited: 29
Robotics and cybersurgery in ophthalmology: a current perspective
Munirah Alafaleq
Journal of Robotic Surgery (2023) Vol. 17, Iss. 4, pp. 1159-1170
Open Access | Times Cited: 16
Head to head comparison of diagnostic performance of three non-mydriatic cameras for diabetic retinopathy screening with artificial intelligence
Mehmet Erkan Doğan, Ahmet Burak Bilgin, Ramazan Sarı, et al.
Eye (2024) Vol. 38, Iss. 9, pp. 1694-1701
Open Access | Times Cited: 6
How Does Smart Healthcare Service Affect Resident Health in the Digital Age? Empirical Evidence From 105 Cities of China
Yan Chen, Liyezi Zhang, Mengyang Wei
Frontiers in Public Health (2022) Vol. 9
Open Access | Times Cited: 25
MIDO GDM: an innovative artificial intelligence-based prediction model for the development of gestational diabetes in Mexican women
Héctor Gallardo‐Rincón, María Jesús Ríos-Blancas, Janinne Ortega-Montiel, et al.
Scientific Reports (2023) Vol. 13, Iss. 1
Open Access | Times Cited: 15
Updates in deep learning research in ophthalmology
Wei Yan Ng, Shihao Zhang, Zhaoran Wang, et al.
Clinical Science (2021) Vol. 135, Iss. 20, pp. 2357-2376
Closed Access | Times Cited: 32
Predicting Hypoxia Using Machine Learning: Systematic Review
Lena Pigat, Benjamin P. Geisler, Seyedmostafa Sheikhalishahi, et al.
JMIR Medical Informatics (2024) Vol. 12, pp. e50642-e50642
Open Access | Times Cited: 4
Deep Learning for Multi-Label Disease Classification of Retinal Images: Insights from Brazilian Data for AI Development in Lower-Middle Income Countries
Dewi S. W. Gould, Jenny Yang, David A. Clifton
medRxiv (Cold Spring Harbor Laboratory) (2024)
Open Access | Times Cited: 4
Chitosan as a promising materials for the construction of nanocarriers for diabetic retinopathy: an updated review
Yan Lv, Chenglei Zhai, Gang Sun, et al.
Journal of Biological Engineering (2024) Vol. 18, Iss. 1
Open Access | Times Cited: 4
Current Research and Future Strategies for the Management of Vision-Threatening Diabetic Retinopathy
Huating Li, Weiping Jia, Stela Vujosevic, et al.
Asia-Pacific Journal of Ophthalmology (2024) Vol. 13, Iss. 5, pp. 100109-100109
Open Access | Times Cited: 4
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