ArticleTurkish journal of ophthalmology2024
The Ability of Large Language Models to Generate Patient Information Materials for Retinopathy of Prematurity: Evaluation of Readability, Accuracy, and Comprehensiveness.
Article in Turkish journal of ophthalmology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
3 citing papers in PubMed.
- Large Language Model Simplification of Open Access Pediatric Strabismus Literature: Cross-Sectional Validation of Readability and Clinical Fidelity.JMIR formative research · 2026Article
- Large Language Model-Generated Patient Education Materials in Pediatric Ophthalmology: A Scoping Review.Clinical ophthalmology (Auckland, N.Z.) · 2026Review
- Performance of ChatGPT-4 Omni and Gemini 1.5 Pro on Ophthalmology-Related Questions in the Turkish Medical Specialty Exam.Turkish journal of ophthalmology · 2025Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objectives: This study compared the readability of patient education materials from the Turkish Ophthalmological Association (TOA) retinopathy of prematurity (ROP) guidelines with those generated by large language models (LLMs). The ability of GPT-4.0, GPT-4o mini, and Gemini to produce patient education materials was evaluated in terms of accuracy and comprehensiveness. Materials and Methods: Thirty questions from the TOA ROP guidelines were posed to GPT-4.0, GPT-4o mini, and Gemini. Their responses were then reformulated using the prompts "Can you revise this text to be understandable at a 6 Results: The TOA brochure was found to have a reading level above the 6 Conclusion: GPT-4.0 appeared to have greater potential for generating more readable, accurate, and comprehensive patient education materials. However, when integrating LLMs into the healthcare field, regional medical differences and the accuracy of the provided information must be carefully assessed.
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Registered trials
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