Large language models as assistance for glaucoma surgical cases: a ChatGPT vs. Google Gemini comparison

The 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. Retrospective 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. ChatGPT surgical choice was consistent with those of glaucoma specialists in 35/60 cases (58