Comparison of Large Language Models in Diagnosis and Management of Challenging Clinical Cases

Subscription LLMs were more prevalent among highly ranked LLMs suggesting that these perform better as ophthalmic assistants. While readability was poor for the average person, the content was understood by a board-certified ophthalmologist. The accuracy of LLMs is not high enough to recommend patient care in standalone mode, but aiding clinicians in patient care and prevent oversights is promising.

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Publication Details

Journal
Clinical ophthalmology
Published
2024-11-01
DOI
https://doi.org/10.2147/opth.s488232
Citations
5
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.60
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article

Comparison of Large Language Models in Diagnosis and Management of Challenging Clinical Cases

David J. Browning, S Shanmugam
5 citations
Clinical ophthalmology
Artificial Intelligence in Healthcare and Education
0.60
article

Comparison of Large Language Models in Diagnosis and Management of Challenging Clinical Cases

David J. Browning, S Shanmugam
article en
5 citations

Abstract

Subscription LLMs were more prevalent among highly ranked LLMs suggesting that these perform better as ophthalmic assistants. While readability was poor for the average person, the content was understood by a board-certified ophthalmologist. The accuracy of LLMs is not high enough to recommend patient care in standalone mode, but aiding clinicians in patient care and prevent oversights is promising.

Clinical ophthalmologyVol. Volume 18
Wake Forest University (US)
Quality Education
Openalex Percentile: Top 28%
Artificial Intelligence in Healthcare and Education
0.60
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