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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:

Application of Comprehensive Artificial intelligence Retinal Expert (CARE) system: a national real-world evidence study
Duoru Lin, Jianhao Xiong, Congxin Liu, et al.
The Lancet Digital Health (2021) Vol. 3, Iss. 8, pp. e486-e495
Open Access | Times Cited: 102

Showing 1-25 of 102 citing articles:

Research progress on double-network hydrogels
Xinxin Huang, Jingchao Li, Jing Luo, et al.
Materials Today Communications (2021) Vol. 29, pp. 102757-102757
Closed Access | Times Cited: 124
Artificial Intelligence for Screening of Multiple Retinal and Optic Nerve Diseases
Li Dong, Wanji He, Ruiheng Zhang, et al.
JAMA Network Open (2022) Vol. 5, Iss. 5, pp. e229960-e229960
Open Access | Times Cited: 85
Artificial intelligence in ophthalmology: The path to the real-world clinic
Zhongwen Li, Lei Wang, Xuefang Wu, et al.
Cell Reports Medicine (2023) Vol. 4, Iss. 7, pp. 101095-101095
Open Access | Times Cited: 61
Economic evaluation of combined population-based screening for multiple blindness-causing eye diseases in China: a cost-effectiveness analysis
Hanruo Liu, Ruyue Li, Yue Zhang, et al.
The Lancet Global Health (2023) Vol. 11, Iss. 3, pp. e456-e465
Closed Access | Times Cited: 48
Bias in medical AI: Implications for clinical decision-making
James M. Cross, Michael A. Choma, John A. Onofrey
PLOS Digital Health (2024) Vol. 3, Iss. 11, pp. e0000651-e0000651
Open Access | Times Cited: 19
From Machine Learning to Patient Outcomes: A Comprehensive Review of AI in Pancreatic Cancer
Satvik Tripathi, Azadeh Tabari, Arian Mansur, et al.
Diagnostics (2024) Vol. 14, Iss. 2, pp. 174-174
Open Access | Times Cited: 17
Modeling adoption of intelligent agents in medical imaging
Francisco Maria Calisto, Nuno Nunes, Jacinto C. Nascimento
International Journal of Human-Computer Studies (2022) Vol. 168, pp. 102922-102922
Closed Access | Times Cited: 68
Artificial intelligence for diabetic retinopathy in low-income and middle-income countries: a scoping review
Charles R Cleland, Justus Rwiza, Jennifer Evans, et al.
BMJ Open Diabetes Research & Care (2023) Vol. 11, Iss. 4, pp. e003424-e003424
Open Access | Times Cited: 28
Artificial Intelligence in Community-Based Diabetic Retinopathy Telemedicine Screening in Urban China: Cost-effectiveness and Cost-Utility Analyses With Real-world Data
Senlin Lin, Yingyan Ma, Yi Xu, et al.
JMIR Public Health and Surveillance (2023) Vol. 9, pp. e41624-e41624
Open Access | Times Cited: 23
Economic evaluation for medical artificial intelligence: accuracy vs. cost-effectiveness in a diabetic retinopathy screening case
Yueye Wang, Chi Liu, Wenyi Hu, et al.
npj Digital Medicine (2024) Vol. 7, Iss. 1
Open Access | Times Cited: 14
Artificial Intelligence, Digital Imaging, and Robotics Technologies for Surgical Vitreoretinal Diseases
Stanley Poh, Josh Tjunrong Sia, Michelle Yip, et al.
Ophthalmology Retina (2024) Vol. 8, Iss. 7, pp. 633-645
Closed Access | Times Cited: 8
Oculomics: Current Concepts and Evidence
Zhuoting Zhu, Yueye Wang, Ziyi Qi, et al.
Progress in Retinal and Eye Research (2025), pp. 101350-101350
Closed Access | Times Cited: 1
Cost-effectiveness and cost-utility of a digital technology-driven hierarchical healthcare screening pattern in China
Xiaohang Wu, Yuxuan Wu, Zhenjun Tu, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 7
The AI Revolution in Glaucoma: Bridging Challenges with Opportunities
Fei Li, Biao Wang, Zefeng Yang, et al.
Progress in Retinal and Eye Research (2024) Vol. 103, pp. 101291-101291
Closed Access | Times Cited: 7
The performance of a deep learning system in assisting junior ophthalmologists in diagnosing 13 major fundus diseases: a prospective multi-center clinical trial
Bing Li, Huan Chen, Weihong Yu, et al.
npj Digital Medicine (2024) Vol. 7, Iss. 1
Open Access | Times Cited: 6
DeepFundus: A flow-cytometry-like image quality classifier for boosting the whole life cycle of medical artificial intelligence
Lixue Liu, Xiaohang Wu, Duoru Lin, et al.
Cell Reports Medicine (2023) Vol. 4, Iss. 2, pp. 100912-100912
Open Access | Times Cited: 14
Real-world post-deployment performance of a novel machine learning-based digital health technology for skin lesion assessment and suggestions for post-market surveillance
Lucy Thomas, Chris Hyde, Daniel Mullarkey, et al.
Frontiers in Medicine (2023) Vol. 10
Open Access | Times Cited: 14
Evaluating the accuracy of the Ophthalmologist Robot for multiple blindness-causing eye diseases: a multicentre, prospective study protocol
Qixin Li, Jie Tan, He Xie, et al.
BMJ Open (2024) Vol. 14, Iss. 3, pp. e077859-e077859
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
Development and Validation of a Multimodal Multitask Vision Foundation Model for Generalist Ophthalmic Artificial Intelligence
Jianing Qiu, Jian Wu, Hao Wei, et al.
NEJM AI (2024) Vol. 1, Iss. 12
Closed Access | Times Cited: 5
Overcoming Pilotitis in Digital Medicine at the Intersection of Data, Clinical Evidence, and Adoption
Mathias Egermark, Agata Blasiak, Alexandria Remus, et al.
Advanced Intelligent Systems (2022) Vol. 4, Iss. 9
Closed Access | Times Cited: 20
Multi-label classification of fundus images with graph convolutional network and LightGBM
Kai Sun, Mengjia He, Xu Yao, et al.
Computers in Biology and Medicine (2022) Vol. 149, pp. 105909-105909
Closed Access | Times Cited: 20
Application of artificial intelligence system for screening multiple fundus diseases in Chinese primary healthcare settings: a real-world, multicentre and cross-sectional study of 4795 cases
Chufeng Gu, Yujie Wang, Yan Jiang, et al.
British Journal of Ophthalmology (2023) Vol. 108, Iss. 3, pp. 424-431
Open Access | Times Cited: 11
Prediction of preeclampsia from retinal fundus images via deep learning in singleton pregnancies: a prospective cohort study
Tianfan Zhou, Shengyi Gu, Feixue Shao, et al.
Journal of Hypertension (2024) Vol. 42, Iss. 4, pp. 701-710
Open Access | Times Cited: 4
Automated detection of nine infantile fundus diseases and conditions in retinal images using a deep learning system
Yaling Liu, Hai Xie, Xinyu Zhao, et al.
The EPMA Journal (2024) Vol. 15, Iss. 1, pp. 39-51
Open Access | Times Cited: 4
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