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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:

The Potential Role of Large Language Models in Uveitis Care: Perspectives After ChatGPT and Bard Launch
Collin Tan Yip Ming, William Rojas‐Carabali, Carlos Cifuentes‐González, et al.
Ocular Immunology and Inflammation (2023) Vol. 32, Iss. 7, pp. 1435-1439
Open Access | Times Cited: 10

Showing 10 citing articles:

Investigating the Accuracy and Completeness of an Artificial Intelligence Large Language Model About Uveitis: An Evaluation of ChatGPT
Rayna Marshall, Krishna Mallem, Hannah Xu, et al.
Ocular Immunology and Inflammation (2024) Vol. 32, Iss. 9, pp. 2052-2055
Closed Access | Times Cited: 11
Comparison of ChatGPT-4o, Google Gemini 1.5 Pro, Microsoft Copilot Pro, and Ophthalmologists in the management of uveitis and ocular inflammation: A comparative study of large language models
Senol Demir
Journal Français d Ophtalmologie (2025) Vol. 48, Iss. 4, pp. 104468-104468
Closed Access
Performance of Chatgpt in ophthalmology exam; human versus AI
Ali Safa Balcı, Zeliha Yazar, Banu Öztürk, et al.
International Ophthalmology (2024) Vol. 44, Iss. 1
Closed Access | Times Cited: 3
Managing a patient with uveitis in the era of artificial intelligence: Current approaches, emerging trends, and future perspectives
William Rojas‐Carabali, Carlos Cifuentes‐González, Laura Gutiérrez-Sinisterra, et al.
Asia-Pacific Journal of Ophthalmology (2024) Vol. 13, Iss. 4, pp. 100082-100082
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
Artificial intelligence derived large language model in decision-making process in uveitis
Inès Schumacher, Virginie Manuela Marie Bühler, Damian Jaggi, et al.
International Journal of Retina and Vitreous (2024) Vol. 10, Iss. 1
Open Access | Times Cited: 1
Evaluation of the reliability and readability of answers given by chatbots to frequently asked questions about endophthalmitis: A cross-sectional study on chatbots
Süleyman Demir
Health Informatics Journal (2024) Vol. 30, Iss. 4
Open Access | Times Cited: 1
Accuracy and Completeness of Large Language Models About Antibody–Drug Conjugates and Associated Ocular Adverse Effects
Rayna Marshall, Hannah Xu, Lauren A. Dalvin, et al.
Cornea (2024)
Closed Access
Investigating the comparative superiority of artificial intelligence programs in assessing knowledge levels regarding ocular inflammation, uvea diseases, and treatment modalities
Eyüpcan Şensoy, Mehmet Çıtırık
Taiwan Journal of Ophthalmology (2024) Vol. 14, Iss. 3, pp. 409-413
Open Access
Is Automated Machine Learning useful for ocular toxoplasmosis identification and classification of the inflammatory activity?
Carlos Cifuentes‐González, William Rojas‐Carabali, Germán Mejía‐Salgado, et al.
Deleted Journal (2024), pp. 100079-100079
Open Access
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