ArticleDigital journal of ophthalmology : DJO2025
Accuracy of an artificial intelligence chatbot in identifying congenital glaucoma from other ocular etiologies.
Article in Digital journal of ophthalmology : DJO, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Diagnostic Accuracy and Counseling Quality of GPT-4o for Strabismus and Pseudostrabismus in Patient-Generated Mobile Photographs: A Preliminary Evaluation.Clinical ophthalmology (Auckland, N.Z.) · 2025Article
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4 authors.
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Abstract
Purpose: To evaluate the accuracy and appropriateness of responses provided by ChatGPT in identifying congenital glaucoma from a series of written and image-based prompts. Methods: A series of questions regarding common signs and symptoms of congenital glaucoma were developed and queried to ChatGPT-3.5 and ChatGPT-4.0, and a set of publicly available images of patients with congenital glaucoma were queried to the image search function of ChatGPT-4.0. Outputs were graded by three pediatric ophthalmologists with expertise in congenital glaucoma. Completeness of response, accuracy, potential for harm, and concern for glaucoma were assessed by each reviewer. Results: A higher proportion of prompt responses from ChatGPT-4.0 were graded to be acceptable/appropriate than from ChatGPT-3.5 (22/33 vs 9/33 [ Conclusions: Despite superior performance from ChatGPT-4.0 compared with ChatGPT-3.5 in raising concern for congenital glaucoma and appropriateness of responses from text-based prompts, it performed poorly in recognizing clinical images of congenital glaucoma.
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