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Performance of Large Language Models for Structured Recognition and Refractive Prediction

StatusRecruiting
PhaseNot specified
SponsorJin Yang
Started
View on ClinicalTrials.gov ↗

Record History

  1. Study First Submitted
Jin Yang
7 trials monitored
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We conducted a single-center, retrospective observational study to evaluate large language models (ChatGPT 4o, GPT-5, DeepSeek) for automated interpretation of de-identified IOLMaster 700 reports provided as raster images. Models produced structured biometric extraction, toric IOL recommendation, and refractive predictions (sphere, cylinder, axis). Primary outcomes included parameter-level agreement and refractive error metrics; secondary outcomes included decision-support performance for toric IOL selection and agreement on ordered T-codes. No clinical intervention was performed.
Trial Details
NCT Number NCT07183891
Lead Sponsor Jin Yang
Conditions
(from sponsor)		 Cataract
Related terms Astigmatism, Cataract
Enrollment 100 participants
Start Date
Primary Completion (estimated)
Study Completion (estimated)
Updated on ClinicalTrials.gov