Evaluating large language models in pediatric fever management: a two-layer study.

ABSTRACT:

Background

Pediatric fever is a prevalent concern, often causing parental anxiety and frequent medical consultations. While large language models (LLMs) such as ChatGPT, Perplexity, and YouChat show promise in enhancing medical communication and education, their efficacy in addressing complex pediatric fever-related questions remains underexplored, particularly from the perspectives of medical professionals and patients' relatives.

Objective

This study aimed to explore the differences and similarities among four common large language models (ChatGPT3.5, ChatGPT4.0, YouChat, and Perplexity) in answering thirty pediatric fever-related questions and to examine how doctors and pediatric patients' relatives evaluate the LLM-generated answers based on predefined criteria.

Metho

SUBMITTER: Yang G 

PROVIDER: S-EPMC12441047 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature