Large Language Models for Therapy Recommendations Across 3 Clinical Specialties: Comparative Study.

ABSTRACT:

Background

As advancements in artificial intelligence (AI) continue, large language models (LLMs) have emerged as promising tools for generating medical information. Their rapid adaptation and potential benefits in health care require rigorous assessment in terms of the quality, accuracy, and safety of the generated information across diverse medical specialties.

Objective

This study aimed to evaluate the performance of 4 prominent LLMs, namely, Claude-instant-v1.0, GPT-3.5-Turbo, Command-xlarge-nightly, and Bloomz, in generating medical content spanning the clinical specialties of ophthalmology, orthopedics, and dermatology.

Methods

Three domain-specific physicians evaluated the AI-generated therapeutic recommendations for a diverse set of 60 diseases. The evaluation

SUBMITTER: Wilhelm TI 

PROVIDER: S-EPMC10644179 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature