Detection of Medical Misinformation in Hemangioma Patient Education: Comparative Study of ChatGPT-4o and DeepSeek-R1 Large Language Models.

ABSTRACT:

Background

This study examines the capability of large language models (LLMs) in detecting medical rumors, using hemangioma-related information as an example. It compares the performances of ChatGPT-4o and DeepSeek-R1.

Objective

This study aimed to evaluate and compare the accuracy, stability, and expert-rated reliability of 2 LLMs, ChatGPT-4o and DeepSeek-R1, in classifying medical information related to hemangiomas as either "rumors" or "accurate information."

Methods

We collected 82 publicly available texts from social media platforms, medical education websites, international guidelines, and journals. Of the 82 items, 47/82 (57%) were labeled as "rumors," and 35/82 (43%) were labeled as "accurate information." Three vascular anomaly specialists with extensive clin

SUBMITTER: Wang G 

PROVIDER: S-EPMC12627899 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature