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NCT07183891

Performance of Large Language Models for Structured Recognition and Refractive Prediction

Recruiting now Last updated 19 September 2025
What this trial tests

trial in Cataract in 100 participants. Currently enrolling.

Timeline
1 August 2025
Primary endpoint
31 December 2030
31 December 2035

Quick facts

Lead sponsorJin Yang
StatusRecruiting now
Study typeOBSERVATIONAL
Enrollment100
Start date1 August 2025
Primary completion31 December 2030
Estimated completion31 December 2035
Sites1 location across China

Conditions studied

Sponsor

Jin Yang — full company profile →

Who can join

18 and older, any sex, with Cataract. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

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.

Publications & conference data

No peer-reviewed publications indexed yet for this trial.

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Other recruiting trials for Cataract

Currently open trials in the same condition.

Other Jin Yang trials

Trials by the same sponsor.

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Data sources for this page

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