Related Experiment Video
Updated: Apr 22, 2026
Comparison of Agreement and Accuracy using Binocular Wavefront Optometer with Autorefractor and Phoropter
Published on: September 16, 2025
Comparison of three large language models in recognizing ophthalmological examination and supporting preoperative
Xuanqiao Lin1, Yizhou Yang1, Songlian Wang2
1Department of Ophthalmology, Eye, Ear, Nose, and Throat Hospital of Fudan University, Shanghai, People's Republic of China.
Purpose:
To evaluate the performance of three large language models (LLMs) in automated recognition of IOLMaster 700 reports and preoperative toric intraocular lens (IOL) planning.
Methods:
The retrospective study analyzed preoperative examination reports of patients who underwent cataract surgery with toric IOL implantation. Three models (ChatGPT-5, ChatGPT-5 Thinking and DeepSeek Thinking) were instructed to extract key biometric parameters, evaluate a patient's suitability for toric IOL implantation, and generate a plan. Model performance was evaluated based on structured-data recognition, refractive prediction outcomes and thinking times.
Results:
Fifty-four eyes of 54 patients were analyzed. ChatGPT-5 Thinking model consistently achieved the highest agreement with clinical reference for all extracted parameters, and demonstrated more reliable extraction of axis information. ChatGPT-5 showed intermediate performance, while DeepSeek Thinking was the least consistent in axis-dependent fields but performed adequately for basic biometry. Refractive and axis prediction errors were smallest with ChatGPT-5 Thinking, yielding the largest proportion of cases within prespecified clinical thresholds and the highest concordance with the calculator-based reference plan. Analysis of thinking times showed that longer processing did not necessarily correlate with better accuracy.
Conclusions:
Advanced LLMs show promise for automated interpretation of ophthalmic biometry reports and calculator-based toric IOL planning workflows. These findings support the feasibility of LLM-assisted workflow automation, with ChatGPT-5 Thinking providing the most favorable balance of accuracy and efficiency in this setting.
