This paper is in the following e-collection/theme issue:

Clinical Information and Decision Making (1915) AI Language Models in Health Care (202) Generative Language Models Including ChatGPT (708) Natural Language Processing (917) Decision Support for Health Professionals (1539) Theme Issue: AI and ChatGPT in Dermatology (24)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/67489, first published .
Clinical Management of Wasp Stings Using Large Language Models: Cross-Sectional Evaluation Study

Clinical Management of Wasp Stings Using Large Language Models: Cross-Sectional Evaluation Study

Clinical Management of Wasp Stings Using Large Language Models: Cross-Sectional Evaluation Study

Authors of this article:

Wei Pan1 Author Orcid Image ;   Shuman Zhang1 Author Orcid Image ;   Yonghong Wang1 Author Orcid Image ;   Zhenglin Quan2 Author Orcid Image ;   Yanxia Zhu3 Author Orcid Image ;   Zhicheng Fang1 Author Orcid Image ;   Xianyi Yang1 Author Orcid Image
Article Authors Cited by (2) Tweetations Metrics

Journals

  1. Han F, Liu Y, Li H, Chen X, Liang L, Xu D, Ye L, Ouyang Y, He P, Liao W. Machine learning enables early risk stratification of hymenopteran stings: evidence from a tropical multicenter cohort. Frontiers in Public Health 2025;13 View
  2. Vicens-Novell G, Puig Fuentes A, Serrano Delgado P, Ruiz-Leon B. Understanding Hymenoptera Venom Allergy: Key Concepts and Clinical Approaches. Current Treatment Options in Allergy 2025;12(1) View