Appropriateness of Ophthalmology Recommendations From an Online Chat-Based Artificial Intelligence Model.

ABSTRACT:

Objective

To determine the appropriateness of ophthalmology recommendations from an online chat-based artificial intelligence model to ophthalmology questions.

Patients and methods

Cross-sectional qualitative study from April 1, 2023, to April 30, 2023. A total of 192 questions were generated spanning all ophthalmic subspecialties. Each question was posed to a large language model (LLM) 3 times. The responses were graded by appropriate subspecialists as appropriate, inappropriate, or unreliable in 2 grading contexts. The first grading context was if the information was presented on a patient information site. The second was an LLM-generated draft response to patient queries sent by the electronic medical record (EMR). Appropriate was defined as accurate and specific enough t

SUBMITTER: Tailor PD 

PROVIDER: S-EPMC10994056 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature