Comparison of ChatGPT-4 and ChatGPT-4 Plus Responses to Retinopathy of Prematurity–Related Questions and Performance Evaluation in Different Languages

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Authors: Fatma Hilal Yılmaz, Melek Büyükeren, Beyza Özcan, Ramazan Keçeci, Muslu Kazım Körez
Cited by: 0
References: 19

Abstract

Purpose: To compare the accuracy and performance of the ChatGPT-4 and ChatGPT-4 Plus (OpenAI) models in different languages in terms of questions about retinopathy of prematurity (ROP). Methods: Within the scope of the study, 15 questions about ROP were asked of both models. The questions were asked in Turkish and English, and the answers were evaluated by clinicians at five levels: “incorrect,” “inadequate,” “adequate,” “correct,” and “very correct.” The reliability of the responses was analyzed using the intraclass correlation coefficient (ICC), and quality scores were compared using the t -test. Results: According to the ICC analysis, the experts scoring the responses showed high agreement (95%). The difference between the response accuracy scores of both models (ChatGPT-4: P = .704 and ChatGPT-4 Plus: P = .999) and languages (ChatGPT-4: P = .704 and Chat-GPT-4 Plus: P = .999) was not statistically significant. The performance of the models in Turkish and English was found to have similar accuracy levels. Conclusions: In this study, ChatGPT-4 and Chat-GPT-4 Plus models accurately responded to ROP-related questions, and language differences did not affect performance. It was concluded that artificial intelligence–based models have the potential to overcome multilingualism and language barriers in health care settings.

Fields of Study & Subjects

Artificial Intelligence in Healthcare and Education Ophthalmology and Visual Health Research Retinopathy of Prematurity Studies

Publication details

Journal / source
Journal of Pediatric Ophthalmology & Strabismus
Volume
63
Issue
4
Pages
298–303
Publication date
11 February 2026
Language
EN