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This paper is in the following e-collection/theme issue:

Foundation Models and Their Applications in AI (112) Chatbots and Conversational Agents (1173) Presbyopia and other Age-related Eye Diseases and Vision Impairments (30) Generative Language Models Including ChatGPT (1508) Foundations of AI (91)

Published on in Vol 5 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/72101, first published .
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Performance of a Small Language Model Versus a Large Language Model in Answering Glaucoma Frequently Asked Patient Questions: Development and Usability Study

Performance of a Small Language Model Versus a Large Language Model in Answering Glaucoma Frequently Asked Patient Questions: Development and Usability Study

Authors of this article:

Adriano Cypriano Faneli1, 2 Author Orcid Image ;   Rafael Scherer1 Author Orcid Image ;   Rohit Muralidhar1 Author Orcid Image ;   Marcus Guerreiro-Filho1 Author Orcid Image ;   Luiz Beniz1 Author Orcid Image ;   Verônica Vilasboas-Campos1 Author Orcid Image ;   Douglas Costa1 Author Orcid Image ;   Alessandro A Jammal1 Author Orcid Image ;   Felipe A Medeiros1 Author Orcid Image
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Journals

  1. Njessi P, Maurice-Szamburski A, Amro C, Boyd C, Laloze J, Lupon E. Assessing ChatGPT and Gemini Responses to Common Patient Questions Regarding Augmentation Mammaplasty. Aesthetic Plastic Surgery 2026;50(11):4055 View
  2. Yin H, Miao Q, Zhou W, Hu C, Guo Y, Shen L, Cai H, Grzybowski A, Jin K. Evaluating large language model clinical reasoning in glaucoma using retrieval-augmented generation. Advances in Ophthalmology Practice and Research 2026;6(3):291 View
  3. Yin H, Yu T, Wu W, Shen L, Shi D, Chen Y, Zhao K, Grzybowski A, Jin K. Evaluating multimodal large language models for differential diagnosis of high myopia versus high myopia with Glaucoma. Frontiers in Medicine 2026;13 View