Thirunavukarasu AJ, Ting DSJ, Elangovan K, Gutierrez L, Tan TF, Ting DSW. Large language models in medicine. Nat Med. 2023;29:1930–40. https://doi.org/10.1038/s41591-023-02448-8.

Article  PubMed  Google Scholar 

Cascella M, Semeraro F, Montomoli J, Bellini V, Piazza O, Bignami E. The breakthrough of large language models release for medical applications: 1-year timeline and perspectives. J Med Syst. 2024;48:22. https://doi.org/10.1007/s10916-024-02045-3.

Article  PubMed  PubMed Central  Google Scholar 

Eysenbach G. The role of ChatGPT, generative language models, and artificial intelligence in medical education: a conversation with ChatGPT and a call for papers. JMIR Med Educ. 2023;9:e46885. https://doi.org/10.2196/46885.

Article  PubMed  PubMed Central  Google Scholar 

Zandi R, Fahey JD, Drakopoulos M, Bryan JM, Dong S, Bryar PJ, et al. Exploring diagnostic precision and triage proficiency: a comparative study of GPT-4 and bard in addressing common ophthalmic complaints. Bioengineering. 2024;11:120. https://doi.org/10.3390/bioengineering11020120.

Article  PubMed  PubMed Central  Google Scholar 

Lyons RJ, Arepalli SR, Fromal O, Choi JD, Jain N. Artificial intelligence chatbot performance in triage of ophthalmic conditions. Can J Ophthalmol. 2024;59:e301–e308. https://doi.org/10.1016/j.jcjo.2023.07.016.

Article  PubMed  Google Scholar 

Singh S, Djalilian A, Ali MJ. ChatGPT and ophthalmology: exploring its potential with discharge summaries and operative notes. Semin Ophthalmol. 2023;38:503–7. https://doi.org/10.1080/08820538.2023.2209166.

Article  PubMed  Google Scholar 

Gopalakrishnan N, Joshi A, Chhablani J, Yadav NK, Reddy NG, Rani PK, et al. Recommendations for initial diabetic retinopathy screening of diabetic patients using large language model-based artificial intelligence in real-life case scenarios. Int J Retin Vitreous. 2024;10:11. https://doi.org/10.1186/s40942-024-00533-9.

Article  Google Scholar 

Choudhary A, Gopalakrishnan N, Joshi A, Balakrishnan D, Chhablani J, Yadav NK, et al. Recommendations for diabetic macular edema management by retina specialists and large language model-based artificial intelligence platforms. Int J Retin Vitreous. 2024;10:22. https://doi.org/10.1186/s40942-024-00544-6.

Article  Google Scholar 

Liu X, Wu J, Shao A, Shen W, Ye P, Wang Y, et al. Uncovering language disparity of ChatGPT on retinal vascular disease classification: cross-sectional study. J Med Internet Res. 2024;26:e51926. https://doi.org/10.2196/51926.

Article  PubMed  PubMed Central  Google Scholar 

Mohammadi SS, Nguyen QD. A user-friendly approach for the diagnosis of diabetic retinopathy using ChatGPT and automated machine learning. Ophthalmol Sci. 2024;4:100495. https://doi.org/10.1016/j.xops.2024.100495.

Article  PubMed  PubMed Central  Google Scholar 

Chen X, Zhang W, Xu P, Zhao Z, Zheng Y, Shi D, et al. FFA-GPT: an automated pipeline for fundus fluorescein angiography interpretation and question-answer. NPJ Digit Med. 2024;7:111. https://doi.org/10.1038/s41746-024-01101-z.

Article  PubMed  PubMed Central  Google Scholar 

Chen X, Zhang W, Zhao Z, Xu P, Zheng Y, Shi D, et al. ICGA-GPT: report generation and question answering for indocyanine green angiography images. Br J Ophthalmol. 2024;108:1450–6. https://doi.org/10.1136/bjo-2023-324446.

Article  PubMed  Google Scholar 

Lin Z, Zhang D, Shi D, Xu R, Tao Q, Wu L, et al. Contrastive pre-training and linear interaction attention-based transformer for universal medical reports generation. J Biomed Inf. 2023;138:104281. https://doi.org/10.1016/j.jbi.2023.104281.

Article  Google Scholar 

Chen X, Xu P, Li Y, Zhang W, Song F, He M, et al. ChatFFA: an ophthalmic chat system for unified vision-language understanding and question answering for fundus fluorescein angiography. iScience. 2024;27:110021. https://doi.org/10.1016/j.isci.2024.110021.

Article  PubMed  PubMed Central  Google Scholar 

Carlà MM, Gambini G, Baldascino A, Giannuzzi F, Boselli F, Crincoli E, et al. Exploring AI-chatbots’ capability to suggest surgical planning in ophthalmology: ChatGPT versus Google Gemini analysis of retinal detachment cases. Br J Ophthalmol. 2024;108:1457–69. https://doi.org/10.1136/bjo-2023-325143.

Article  PubMed  Google Scholar 

Huang X, Raja H, Madadi Y, Delsoz M, Poursoroush A, Kahook MY, et al. Predicting glaucoma before onset using a large language model chatbot. Am J Ophthalmol. 2024;266:289–99. https://doi.org/10.1016/j.ajo.2024.05.022.

Article  PubMed  Google Scholar 

Kass MA, Heuer DK, Higginbotham EJ, Johnson CA, Keltner JL, Miller JP, et al. The ocular hypertension treatment study: a randomized trial determines that topical ocular hypotensive medication delays or prevents the onset of primary open-angle glaucoma. Arch Ophthalmol. 2002;120:701–13. https://doi.org/10.1001/archopht.120.6.701.

Article  PubMed  Google Scholar 

Carlà MM, Gambini G, Baldascino A, Boselli F, Giannuzzi F, Margollicci F, et al. Large language models as assistance for glaucoma surgical cases: a ChatGPT vs. Google Gemini comparison. Graefes Arch Clin Exp Ophthalmol. 2024;262:2945–59. https://doi.org/10.1007/s00417-024-06470-5.

Article  PubMed  PubMed Central  Google Scholar 

Rojas-Carabali W, Sen A, Agarwal A, Tan G, Cheung CY, Rousselot A, et al. Chatbots Vs. human experts: evaluating diagnostic performance of chatbots in uveitis and the perspectives on AI adoption in ophthalmology. Ocul Immunol Inflamm. 2024;32:1591–8. https://doi.org/10.1080/09273948.2023.2266730.

Article  PubMed  Google Scholar 

Ćirković A, Katz T. Exploring the potential of ChatGPT-4 in predicting refractive surgery categorizations: comparative study. JMIR Form Res. 2023;7:e51798. https://doi.org/10.2196/51798.

Article  PubMed  PubMed Central  Google Scholar 

Ali MJ. ChatGPT and lacrimal drainage disorders: performance and scope of improvement. Ophthalmic Plast Reconstr Surg. 2023;39:221–5. https://doi.org/10.1097/IOP.0000000000002418.

Article  PubMed  PubMed Central  Google Scholar 

Tailor PD, Dalvin LA, Chen JJ, Iezzi R, Olsen TW, Scruggs BA, et al. A comparative study of responses to retina questions from either experts, expert-edited large language models, or expert-edited large language models alone. Ophthalmol Sci. 2024;4:100485. https://doi.org/10.1016/j.xops.2024.100485.

Article  PubMed  PubMed Central  Google Scholar 

Pushpanathan K, Lim ZW, Er Yew SM, Chen DZ, Hui’En Lin HA, Lin Goh JH, et al. Popular large language model chatbots’ accuracy, comprehensiveness, and self-awareness in answering ocular symptom queries. iScience. 2023;26:108163. https://doi.org/10.1016/j.isci.2023.108163.

Article  PubMed  PubMed Central  Google Scholar 

Tailor PD, Xu TT, Fortes BH, Iezzi R, Olsen TW, Starr MR, et al. Appropriateness of ophthalmology recommendations from an online chat-based artificial intelligence model. Mayo Clin Proc Digit Health. 2024;2:119–28. https://doi.org/10.1016/j.mcpdig.2024.01.003.

Article  PubMed  PubMed Central  Google Scholar 

Barclay KS, You JY, Coleman MJ, Mathews PM, Ray VL, Riaz KM, et al. Quality and agreement with scientific consensus of ChatGPT information regarding corneal transplantation and Fuchs dystrophy. Cornea. 2024;43:746–50. https://doi.org/10.1097/ICO.0000000000003439.

Article  PubMed  Google Scholar 

Kianian R, Sun D, Crowell EL, Tsui E. The use of large language models to generate education materials about uveitis. Ophthalmol Retin. 2024;8:195–201. https://doi.org/10.1016/j.oret.2023.09.008.

Article  Google Scholar 

Dihan Q, Chauhan MZ, Eleiwa TK, Hassan AK, Sallam AB, Khouri AS, et al. Using large language models to generate educational materials on childhood glaucoma. Am J Ophthalmol. 2024;265:28–38. https://doi.org/10.1016/j.ajo.2024.04.004.

Article  PubMed  Google Scholar 

Ferro Desideri L, Roth J, Zinkernagel M, Anguita R. Application and accuracy of artificial intelligence-derived large language models in patients with age related macular degeneration. Int J Retin Vitreous. 2023;9:71. https://doi.org/10.1186/s40942-023-00511-7.

Article  Google Scholar 

Wu G, Zhao W, Wong A, Lee DA. Patients with floaters: answers from virtual assistants and large language models. Digit Health. 2024;10:20552076241229933. https://doi.org/10.1177/20552076241229933.

Article  PubMed  PubMed Central  Google Scholar 

Milad D, Antaki F, Milad J, Farah A, Khairy T, Mikhail D, et al. Assessing the medical reasoning skills of GPT-4 in complex ophthalmology cases. Br J Ophthalmol. 2024;108:1398–405. https://doi.org/10.1136/bjo-2023-325053.