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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:

Economic Evaluations of Artificial Intelligence in Ophthalmology
Paisan Ruamviboonsuk, Somporn Chantra, Kasem Seresirikachorn, et al.
Asia-Pacific Journal of Ophthalmology (2021) Vol. 10, Iss. 3, pp. 307-316
Open Access | Times Cited: 34

Showing 1-25 of 34 citing articles:

Artificial intelligence and digital health in global eye health: opportunities and challenges
Ting Fang Tan, Arun James Thirunavukarasu, Liyuan Jin, et al.
The Lancet Global Health (2023) Vol. 11, Iss. 9, pp. e1432-e1443
Closed Access | Times Cited: 46
A systematic review and meta-analysis of artificial neural network, machine learning, deep learning, and ensemble learning approaches in field of geotechnical engineering
Elaheh Yaghoubi, Elnaz Yaghoubi, Ahmed A. Khamees, et al.
Neural Computing and Applications (2024) Vol. 36, Iss. 21, pp. 12655-12699
Open Access | Times Cited: 21
Characterizing the Clinical Adoption of Medical AI Devices through U.S. Insurance Claims
Kevin Wu, Eric Q. Wu, Brandon Theodorou, et al.
NEJM AI (2023) Vol. 1, Iss. 1
Open Access | Times Cited: 35
A systematic review and meta-analysis of artificial intelligence diagnostic accuracy in prostate cancer histology identification and grading
Andrey Morozov, Mark Taratkin, Andrey Bazarkin, et al.
Prostate Cancer and Prostatic Diseases (2023) Vol. 26, Iss. 4, pp. 681-692
Closed Access | Times Cited: 22
“Spaceflight-to-Eye Clinic”: Terrestrial advances in ophthalmic healthcare delivery from space-based innovations
Joshua Ong, Ethan Waisberg, Mouayad Masalkhi, et al.
Life Sciences in Space Research (2024) Vol. 41, pp. 100-109
Closed Access | Times Cited: 7
Artificial intelligence in retinal imaging for cardiovascular disease prediction: current trends and future directions
Dragon Y.L. Wong, Mary C. Lam, An Ran Ran, et al.
Current Opinion in Ophthalmology (2022) Vol. 33, Iss. 5, pp. 440-446
Closed Access | Times Cited: 23
AI-integrated ocular imaging for predicting cardiovascular disease: advancements and future outlook
Yu Huang, Carol Y. Cheung, Da‐Wei Li, et al.
Eye (2023) Vol. 38, Iss. 3, pp. 464-472
Closed Access | Times Cited: 14
Comparing code-free and bespoke deep learning approaches in ophthalmology
Carolyn Yu Tung Wong, Ciara O’Byrne, Priyal Taribagil, et al.
Graefe s Archive for Clinical and Experimental Ophthalmology (2024) Vol. 262, Iss. 9, pp. 2785-2798
Open Access | Times Cited: 5
Latest developments of generative artificial intelligence and applications in ophthalmology
Xiaoru Feng, Kezheng Xu, Mingjie Luo, et al.
Asia-Pacific Journal of Ophthalmology (2024) Vol. 13, Iss. 4, pp. 100090-100090
Open Access | Times Cited: 5
Cost-Utility Analysis of Deep Learning and Trained Human Graders for Diabetic Retinopathy Screening in a Nationwide Program
Attasit Srisubat, Kankamon Kittrongsiri, Sermsiri Sangroongruangsri, et al.
Ophthalmology and Therapy (2023) Vol. 12, Iss. 2, pp. 1339-1357
Open Access | Times Cited: 13
Current status and practical considerations of artificial intelligence use in screening and diagnosing retinal diseases: Vision Academy retinal expert consensus
Yu-Bai Chou, Aditya U. Kale, Paolo Lanzetta, et al.
Current Opinion in Ophthalmology (2023) Vol. 34, Iss. 5, pp. 403-413
Open Access | Times Cited: 11
Stakeholder Attitudes on AI Integration in Ophthalmology
Amr Saad, Ferhat Turgut, Matthias Becker, et al.
Klinische Monatsblätter für Augenheilkunde (2025) Vol. 242, Iss. 04, pp. 515-520
Open Access
A Review of Literature on the Economic Implications of Implementing Artificial Intelligence in Healthcare
Badr Alnasser
E-Health Telecommunication Systems and Networks (2023) Vol. 12, Iss. 03, pp. 35-48
Open Access | Times Cited: 9
Accuracy of artificial intelligence model for infectious keratitis classification: a systematic review and meta-analysis
Randy Sarayar, Yeni Dwi Lestari, Arnaud Arindra Adiyoso Setio, et al.
Frontiers in Public Health (2023) Vol. 11
Open Access | Times Cited: 9
Artificial intelligence in retinal imaging: current status and future prospects
Katharina A. Heger, Sebastian M. Waldstein
Expert Review of Medical Devices (2023) Vol. 21, Iss. 1-2, pp. 73-89
Closed Access | Times Cited: 9
The application of artificial intelligence in diabetic retinopathy: progress and prospects
Xin Xu, Mingchen Zhang, Sihong Huang, et al.
Frontiers in Cell and Developmental Biology (2024) Vol. 12
Open Access | Times Cited: 3
Technical/Algorithm, Stakeholder, and Society (TASS) barriers to the application of artificial intelligence in medicine: A systematic review
Linda T. Li, Lauren C. Haley, Alexandra K. Boyd, et al.
Journal of Biomedical Informatics (2023) Vol. 147, pp. 104531-104531
Open Access | Times Cited: 8
Ethical and Regulatory Challenges of Generative Artificial Intelligence in Healthcare: A Chinese Perspective
Lanyi Yu, Xiaomei Zhai
Journal of Clinical Nursing (2024)
Closed Access | Times Cited: 2
Prevalence and predictors for being unscreened for diabetic retinopathy: a population-based study over a decade
Tina Felfeli, Glen Katsnelson, Alex Kiss, et al.
Canadian Journal of Ophthalmology (2022) Vol. 58, Iss. 4, pp. 278-286
Closed Access | Times Cited: 10
Developments in Artificial Intelligence for Ophthalmology: Federated Learning
Zhen Ling Teo, Aaron Lee, Peter J. Campbell, et al.
Asia-Pacific Journal of Ophthalmology (2022) Vol. 11, Iss. 6, pp. 500-502
Open Access | Times Cited: 8
Assessment of angle closure disease in the age of artificial intelligence: A review
Zhi Da Soh, Mingrui Tan, Monisha E. Nongpiur, et al.
Progress in Retinal and Eye Research (2023) Vol. 98, pp. 101227-101227
Closed Access | Times Cited: 4
Automated Retinal Vessel Analysis Based on Fundus Photographs as a Predictor for Non-Ophthalmic Diseases—Evolution and Perspectives
Ciprian Danielescu, Marius Gabriel Dabija, Alin Horațiu Nedelcu, et al.
Journal of Personalized Medicine (2023) Vol. 14, Iss. 1, pp. 45-45
Open Access | Times Cited: 4
An Economic Analysis for the Use of Artificial Intelligence in Screening for Diabetic Retinopathy in Trinidad and Tobago
Ryan Ramoutar
Cureus (2024)
Open Access | Times Cited: 1
Update on Optical Coherence Tomography and Optical Coherence Tomography Angiography Imaging in Proliferative Diabetic Retinopathy
Sara Vaz-Pereira, Tiago Morais-Sarmento, Michael Engelbert
Diagnostics (2021) Vol. 11, Iss. 10, pp. 1869-1869
Open Access | Times Cited: 9
Prospective studies on artificial intelligence (AI)-based diabetic retinopathy screening
Onnisa Nanegrungsunk, Paisan Ruamviboonsuk, Andrzej Grzybowski
Annals of Translational Medicine (2022) Vol. 10, Iss. 24, pp. 1297-1297
Open Access | Times Cited: 6
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