Accuracy of large language models in answering ophthalmology board-style questions: A meta-analysis

Wu, J.-H., Nishida, T., & Liu, T. Y. A. (2024). Accuracy of large language models in answering ophthalmology board-style questions: A meta-analysis. Asia-Pacific Journal of Ophthalmology, 13(5), 100106. https://doi.org/10.1016/j.apjo.2024.100106
Authors:
Jo-Hsuan Wu
Takashi Nishida
T. Y. Alvin Liu
Affiliated Authors:
Jo-Hsuan Wu
Columbia Affiliation:
Subjects:
Educational Measurement (MeSH)
Ophthalmology (MeSH)
Deep Learning (MeSH)
Author Keywords:
board-style questions
chatgpt
large language models
ophthalmology board exams
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Publication Type:
Article
Unique ID:
10.1016/j.apjo.2024.100106
PMID:
39374807
DOI:
10.1016/j.apjo.2024.100106
Journal:
Asia-Pacific Journal of Ophthalmology
Publication Date:
Data Source:
Web of Science
Source Link:
View Web of Science Record
View PubMed Record

Record Created: