ArticleGraefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie2024
Large language models as assistance for glaucoma surgical cases: a ChatGPT vs. Google Gemini comparison.
Article in Graefe's archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 1 of them a synthesis that pooled it.
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Who cites it
34 citing papers in PubMed, 1 synthesis or guideline pooled it, 69 citations in OpenAlex.
- Evaluating Large Language Models in Ophthalmology: Systematic Review.Journal of medical Internet research · 2025Pooled it
- Large Language Models Approximate Inter-Expert Agreement in Glaucoma Suspect and Glaucoma Classification from Multimodal Data.Ophthalmology science · 2026Article
- The doctors of the future: the competition of ChatGPT-4, ChatGPT-4 omni, and Gemini 2.0 Flash in andrology.BMC urology · 2026Article
- Can artificial intelligence applications be utilised in the management of dental trauma? A comparison of ChatGPT, Gemini, and DeepSeek.BMC oral health · 2026Article
- Patient Cognitive Bias in Large Language Model-Supported Health Consultations: Simulation-Based Comparative Study.Journal of medical Internet research · 2026Article
- Large Language Models in Ophthalmology: A Bibliographic Analysis.Turkish journal of ophthalmology · 2026Article
- Applications of Large Language Models in Glaucoma: A Scoping Review.Vision (Basel, Switzerland) · 2026Review
- Can large language models provide quality, reliable and readable information about sudden infant death syndrome?BMC pediatrics · 2026Article
- Performance of artificial intelligence chatbots in the diagnosis and management of simulated dental trauma cases: an evaluation based on IADT guidelines.Clinical oral investigations · 2025Article
- Comparison of chatbots' accuracy in endodontics questions in dentistry specialization exam in Türkiye: ChatGPT-4o, Gemini Advanced, Copilot, and Claude.BMC oral health · 2025Article
- Performance of several large language models when answering common patient questions about type 1 diabetes in children: accuracy, comprehensibility and practicality.BMC pediatrics · 2025Article
- Comparative Assessment of Large Language Models in Optics and Refractive Surgery: Performance on Multiple-Choice Questions.Vision (Basel, Switzerland) · 2025Article
- Evaluation of large language models within GenAI in qualitative research.Scientific reports · 2025Article
- Large language models in ophthalmology: a scoping review on their utility for clinicians, researchers, patients, and educators.Eye (London, England) · 2025Article
- Assessing the role of large language models in adolescent idiopathic scoliosis care: a comparison between ChatGPT and Google Gemini.Acta orthopaedica et traumatologica turcica · 2025Article
- Evaluating large language models for renal colic imaging recommendations: a comparative analysis of Gemini, copilot, and ChatGPT-4.0.International journal of emergency medicine · 2025Article
- Article
- Comparative analysis of ChatGPT-4o mini, ChatGPT-4o and Gemini Advanced in the treatment of postmenopausal osteoporosis.BMC musculoskeletal disorders · 2025Article
- Accuracy of LLMs in medical education: evidence from a concordance test with medical teacher.BMC medical education · 2025Article
- Evaluation of Responses to Questions About Keratoconus Using ChatGPT-4.0, Google Gemini and Microsoft Copilot: A Comparative Study of Large Language Models on Keratoconus.Eye & contact lens · 2025Article
Corrections and comments
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeThe aim of this study was to define the capability of ChatGPT-4 and Google Gemini in analyzing detailed glaucoma case descriptions and suggesting an accurate surgical plan.
methodsRetrospective analysis of 60 medical records of surgical glaucoma was divided into "ordinary" (n = 40) and "challenging" (n = 20) scenarios. Case descriptions were entered into ChatGPT and Bard's interfaces with the question "What kind of surgery would you perform?" and repeated three times to analyze the answers' consistency. After collecting the answers, we assessed the level of agreement with the unified opinion of three glaucoma surgeons. Moreover, we graded the quality of the responses with scores from 1 (poor quality) to 5 (excellent quality), according to the Global Quality Score (GQS) and compared the results.
resultsChatGPT surgical choice was consistent with those of glaucoma specialists in 35/60 cases (58%), compared to 19/60 (32%) of Gemini (p = 0.0001). Gemini was not able to complete the task in 16 cases (27%). Trabeculectomy was the most frequent choice for both chatbots (53% and 50% for ChatGPT and Gemini, respectively). In "challenging" cases, ChatGPT agreed with specialists in 9/20 choices (45%), outperforming Google Gemini performances (4/20, 20%). Overall, GQS scores were 3.5 ± 1.2 and 2.1 ± 1.5 for ChatGPT and Gemini (p = 0.002). This difference was even more marked if focusing only on "challenging" cases (1.5 ± 1.4 vs. 3.0 ± 1.5, p = 0.001).
conclusionChatGPT-4 showed a good analysis performance for glaucoma surgical cases, either ordinary or challenging. On the other side, Google Gemini showed strong limitations in this setting, presenting high rates of unprecise or missed answers.
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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.