Performance of Large Language Models for Structured Recognition and Refractive Prediction

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

RECRUITING

Total Enrollment

100 participants

Study Classification

OBSERVATIONAL

Study Start Date

2025-08-01

Study Completion Date

2035-12-31

Brief Summary

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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.

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Detailed Description

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This study compares three large language models accessed in their native configurations, without fine-tuning or external tools. For each examination, the original IOLMaster 700 report image was supplied without manual annotation or pre-processing. A standardized instruction required: (i) structured extraction of AL, ACD, LT, WTW, K1/K2 and axes, ΔK, TK1/TK2 and axes, and ΔTK; (ii) binary toric candidacy and T-code according to institutional ALCON mapping; and (iii) refractive recommendations (sphere, cylinder, implantation axis). Each model generated three independent outputs per case. De-identification and IRB oversight (waiver of consent) were implemented according to institutional policy. The unit of enrollment is participants (n=54), with outcomes analyzed per eye (162 eyes) and per model generation where applicable.

Conditions

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Cataract

Study Design

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Observational Model Type

CASE_ONLY

Study Time Perspective

RETROSPECTIVE

Eligibility Criteria

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Inclusion Criteria

-postoperative corrected distance visual acuity (CDVA) of 0.10 logMAR or better -an absolute IOL rotational stability of less than 10∘ at the 1-month follow-up examination

Exclusion Criteria

* incomplete biometric data on the examination report;
* a history of previous ocular surgery or ocular trauma
* the occurrence of intraoperative complications, such as an anterior capsular tear or posterior capsular rupture
* the development of significant postoperative complications, including but not limited to severe intraocular infection or inadequate pupillary dilation.

Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No