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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:

Performance of ChatGPT and Bard on the official part 1 FRCOphth practice questions
Thomas Fowler, Simon Pullen, Liam Birkett
British Journal of Ophthalmology (2023) Vol. 108, Iss. 10, pp. 1379-1383
Closed Access | Times Cited: 28

Showing 1-25 of 28 citing articles:

Prompt engineering in consistency and reliability with the evidence-based guideline for LLMs
Wang Li, Xi Chen, Xiangwen Deng, et al.
npj Digital Medicine (2024) Vol. 7, Iss. 1
Open Access | Times Cited: 81
Utility of artificial intelligence‐based large language models in ophthalmic care
Sayantan Biswas, Leon N. Davies, Amy L. Sheppard, et al.
Ophthalmic and Physiological Optics (2024) Vol. 44, Iss. 3, pp. 641-671
Open Access | Times Cited: 30
Comparative accuracy of ChatGPT-4, Microsoft Copilot and Google Gemini in the Italian entrance test for healthcare sciences degrees: a cross-sectional study
Giacomo Rossettini, Lia Rodeghiero, Federica Corradi, et al.
BMC Medical Education (2024) Vol. 24, Iss. 1
Open Access | Times Cited: 22
Effectiveness of AI-powered Chatbots in responding to orthopaedic postgraduate exam questions—an observational study
Raju Vaishya, Karthikeyan P. Iyengar, Mohit Kumar Patralekh, et al.
International Orthopaedics (2024) Vol. 48, Iss. 8, pp. 1963-1969
Closed Access | Times Cited: 14
ChatGPT’s Performance on Portuguese Medical Examination Questions: Comparative Analysis of ChatGPT-3.5 Turbo and ChatGPT-4o Mini
Filipe Prazeres
JMIR Medical Education (2025) Vol. 11, pp. e65108-e65108
Open Access | Times Cited: 1
Towards regulatory generative AI in ophthalmology healthcare: a security and privacy perspective
Yueye Wang, Chi Liu, Keyao Zhou, et al.
British Journal of Ophthalmology (2024) Vol. 108, Iss. 10, pp. 1349-1353
Closed Access | Times Cited: 7
Understanding natural language: Potential application of large language models to ophthalmology
Zefeng Yang, Biao Wang, Fengqi Zhou, et al.
Asia-Pacific Journal of Ophthalmology (2024) Vol. 13, Iss. 4, pp. 100085-100085
Open Access | Times Cited: 7
Evaluating the competency of ChatGPT in MRCP Part 1 and a systematic literature review of its capabilities in postgraduate medical assessments
Oliver Vij, Henry Calver, Nikki Myall, et al.
PLoS ONE (2024) Vol. 19, Iss. 7, pp. e0307372-e0307372
Open Access | Times Cited: 6
ChatGPT Assisting Diagnosis of Neuro-Ophthalmology Diseases Based on Case Reports
Yeganeh Madadi, Mohammad Delsoz, Priscilla A. Lao, et al.
Journal of Neuro-Ophthalmology (2024)
Open Access | Times Cited: 6
The Transformative Power of Generative Artificial Intelligence for Achieving the Sustainable Development Goal of Quality Education
Prema Nedungadi, Kai–Yu Tang, Raghu Raman
Sustainability (2024) Vol. 16, Iss. 22, pp. 9779-9779
Open Access | Times Cited: 6
The Performance of Artificial Intelligence-based Large Language Models on Ophthalmology-related Questions in Swedish Proficiency Test for Medicine: ChatGPT-4 omni vs Gemini 1.5 Pro
Mehmet Cem Sabaner, Arzu Seyhan Karatepe, Kemal Mert Mutibayraktaroglu, et al.
Deleted Journal (2024), pp. 100070-100070
Open Access | Times Cited: 4
Artificial Intelligence Large Language Models Are Nearly Equivalent to Fourth-Year Orthopaedic Residents on the Orthopaedic In-Training Examination: A Cause for Concern or Excitement?
Ashraf Nawari, Jamal Zahir, Suneel Kumar, et al.
Journal of Orthopaedic Experience & Innovation (2025)
Closed Access
Evaluating the Accuracy of Gemini 2.0 Advanced and ChatGPT 4o in Cataract Knowledge: A Performance Analysis Using Brazilian Council of Ophthalmology Board Exam Questions
Diego Casagrande, Mauro Gobira
Cureus (2025)
Open Access
Performance of Large Language Models (ChatGPT and Gemini Advanced) in Gastrointestinal Pathology and Clinical Review of Applications in Gastroenterology
Swachi Jain, Baidarbhi Chakraborty, Ashish Agarwal, et al.
Cureus (2025)
Open Access
Artificial Intelligence vs. Human Cognition: A Comparative Analysis of ChatGPT and Candidates Sitting the European Board of Ophthalmology Diploma Examination
Anna Maino, Jakub Klikowski, Brendan Strong, et al.
Vision (2025) Vol. 9, Iss. 2, pp. 31-31
Open Access
Vision of the future: large language models in ophthalmology
Prashant D. Tailor, Haley S. D’Souza, Hanzhou Li, et al.
Current Opinion in Ophthalmology (2024) Vol. 35, Iss. 5, pp. 391-402
Closed Access | Times Cited: 3
Ethical considerations for large language models in ophthalmology
Fritz Gerald P. Kalaw, Sally L. Baxter
Current Opinion in Ophthalmology (2024)
Closed Access | Times Cited: 3
Assessment of Large Language Models in Cataract Care Information Provision: A Quantitative Comparison
Zichang Su, Kai Jin, Hongkang Wu, et al.
Ophthalmology and Therapy (2024)
Open Access | Times Cited: 3
Applications of ChatGPT in the diagnosis, management, education, and research of retinal diseases: a scoping review
Victor C. F. Bellanda, Manuel Filipe Santos, Daniel Ferraz, et al.
International Journal of Retina and Vitreous (2024) Vol. 10, Iss. 1
Open Access | Times Cited: 2
Opportunities and Challenges of Chatbots in Ophthalmology: A Narrative Review
Mehmet Cem Sabaner, Rodrigo Anguita, Fares Antaki, et al.
Journal of Personalized Medicine (2024) Vol. 14, Iss. 12, pp. 1165-1165
Open Access | Times Cited: 2
Role of artificial intelligence (Google bard) in morphological, histopathological, and radiological image identifications
Sultan Ayoub Meo, Abdulelah Adnan Abukhalaf, Muhammad Zain Sultan Meo, et al.
Saudi Medical Journal (2024) Vol. 45, Iss. 5, pp. 531-536
Open Access | Times Cited: 1
Utilizing Large Language Models in Ophthalmology: The Current Landscape and Challenges
Peranut Chotcomwongse, Paisan Ruamviboonsuk, Andrzej Grzybowski
Ophthalmology and Therapy (2024) Vol. 13, Iss. 10, pp. 2543-2558
Open Access | Times Cited: 1
Accuracy of Large Language Models in Answering Ophthalmology Board-Style Questions: A Meta-Analysis
Jo‐Hsuan Wu, Takashi Nishida, Tianming Liu
Asia-Pacific Journal of Ophthalmology (2024) Vol. 13, Iss. 5, pp. 100106-100106
Open Access | Times Cited: 1
ChatGPT and Other Large Language Models in Medical Education — Scoping Literature Review
Alexandra Aster, Matthias Carl Laupichler, Tamina Rockwell-Kollmann, et al.
Medical Science Educator (2024) Vol. 35, Iss. 1, pp. 555-567
Open Access | Times Cited: 1
Comparison of ChatGPT 3.5 Turbo and Human Performance in taking the European Board of Ophthalmology Diploma (EBOD) Exam
Anna Maino, Jakub Klikowski, Brendan Strong, et al.
Research Square (Research Square) (2024)
Open Access
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