A clinician-based comparative study of large language models in answering medical questions: the case of asthma

A clinician-based comparative study of large language models in answering medical questions: the case of asthma

ObjectiveThis study aims to evaluate and compare the performance of four major large language models (GPT-3.5, GPT-4.0, YouChat, and Perplexity) in answering 32 common asthma-related questions.Materials and methodsSeventy-five clinicians from various tertiary hospitals participated in this study. Ea...

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Main Authors: Yong Yin, Mei Zeng, Hansong Wang, Haibo Yang, Caijing Zhou, Feng Jiang, Shufan Wu, Tingyue Huang, Shuahua Yuan, Jilei Lin, Mingyu Tang, Jiande Chen, Bin Dong, Jiajun Yuan, Dan Xie
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-04-01
Series:Frontiers in Pediatrics
Subjects:
large language models (LLMs)
pediatric asthma
medical question answering
clinical decision support
AI in healthcare
Online Access:https://www.frontiersin.org/articles/10.3389/fped.2025.1461026/full
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https://www.frontiersin.org/articles/10.3389/fped.2025.1461026/full

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