Large Language Models in Patient Health Communication for Atherosclerotic Cardiovascular Disease: Pilot Cross-Sectional Comparative Analysis.

ABSTRACT:

Background

Large language models (LLMs) have emerged as promising tools for enhancing public access to medical information, particularly for chronic diseases such as atherosclerotic cardiovascular disease (ASCVD). However, their effectiveness in patient-centered health communication remains underexplored, especially in multilingual contexts.

Objective

Our study aimed to conduct a comparative evaluation of 3 advanced LLMs-DeepSeek R1, ChatGPT-4o, and Gemini-in generating responses to ASCVD-related patient queries in both English and Chinese, assessing their performance across the domains of accuracy, completeness, and comprehensibility.

Methods

We conducted a cross-sectional evaluation based on 25 clinically validated ASCVD questions spanning 5 domains-definitions, dia

SUBMITTER: Li P 

PROVIDER: S-EPMC12824577 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature