ArticleRomanian journal of ophthalmology
A comparative analysis of GPT-3.5 and GPT-4.0 on a multiple-choice ophthalmology question bank: A study on artificial intelligence developments.
Article in Romanian journal of ophthalmology. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Evaluating the Performance of ChatGPT on Board-Style Examination Questions in Ophthalmology: A Meta-Analysis.Journal of medical systems · 2025Pooled it
- Evaluating large language model`s performance in answering principles of health course questions.Scientific reports · 2026Article
- Artificial Intelligence in Cardiology Examination: A Comparative Study of Physicians, ChatGPT-4, and ChatGPT-5.Cureus · 2026Article
- How Far Have Large Language Models Advanced in Ophthalmology? A Systematic Review of Their Development, Evaluation, and Readiness for Clinical Use.Research square · 2026Article
- Comparative performance of GPT-4, GPT-o3, GPT-5, Gemini-3-Flash, and DeepSeek-R1 in ophthalmology question answering.Frontiers in cell and developmental biology · 2026Article
- Comparative evaluation of artificial intelligence models GPT-4 and GPT-3.5 in clinical decision-making in sports surgery and physiotherapy: a cross-sectional study.BMC medical informatics and decision making · 2025Article
- Tests of large language models' medical competence and application for clinical decision support of musculoskeletal rehabilitation.Frontiers in digital health · 2025Article
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1 author.
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Abstract
Introduction: To evaluate the performance of ChatGPT-4.0 and ChatGPT-3.5 in answering multiple-choice questions in OphthoQuestions (www.ophthoquestions.com), a popular question preparation bank, and to compare the performance of GPT-4.0 and GPT-3.5. Methods: In January 2024, using a personal account on OphthoQuestions (www.ophthoquestions.com), 520 questions were selected from 4,551 OphthoQuestions. These 520 questions were created by randomly selecting 40 questions from each of 13 ophthalmology subspecialties. GPT-3.5 and GPT-4.0 were asked to answer these same 520 questions. Results: ChatGPT-4.0 and ChatGPT-3.5 answered 408 questions (78.46%) 95% CI [70,88%] and 333 questions (64.15%) 95% CI [53,74%] of 520 questions correctly, respectively. GPT-4.0 answered significantly more questions correctly than GPT-3.5 (p= 0.0195). ChatGPT-4.0 showed a statistically significant difference compared to ChatGPT-3.5 in giving correct answers in all subgroup analyses (p<0.05). Discussions: This study gives an encouraging new proof of ChatGPT's ability to manage complex clinical and medical data, focusing on the development and consistency of artificial intelligence algorithms. The statistically significant success of GPT-4.0 over GPT-3.5 in this study should be examined in light of future algorithm advances, particularly in online tests, which will increase progressively as the use of artificial intelligence poses an increasing danger to test integrity. Protocols such as required proctoring should be considered. In the following years, ChatGPT's clinical management and decision-making expertise should be supplemented by more research indicating that it may be a beneficial resource for ophthalmologists and other medical professionals seeking information and guidance on challenging cases. Conclusions: GPT-4.0 was found to give more and more consistent answers than GPT 3.5 on a multiple-choice ophthalmology question bank. ChatGPT has shown significant differences between algorithms in accuracy and repeatability when handling questions related to eye diseases. This study shows that new artificial intelligence algorithms are promising. More data is needed to use artificial intelligence language models in medical applications.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.