Evaluating ChatGPT on Orbital and Oculofacial Disorders: Accuracy and Readability Insights.

Michael BalasAna JanicPatrick DaigleNavdeep NijhawanAhsen HussainHarmeet GillGabriela L LahaieMichel J BelliveauSean A CrawfordParnian ArjmandEdsel B Ing

Published in: Ophthalmic plastic and reconstructive surgery (2023)

This study demonstrates the potential of ChatGPT 4.0 to provide accurate information in the field of ophthalmology, specifically orbital and oculofacial disease. However, challenges remain in ensuring accurate and comprehensive responses across all disease domains. Future improvements should focus on refining the model's correctness and eventually expanding the scope to visual data interpretation. Our results highlight the vast potential for artificial intelligence in educational and clinical ophthalmology contexts.

Keyphrases

artificial intelligence
big data
machine learning
deep learning
health information
high resolution
electronic health record
healthcare
mass spectrometry