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

Formative Evaluation of Digital Health Interventions (3347) Digital Mental Health Interventions, e-Mental Health and Cyberpsychology (2203) Generative Language Models Including ChatGPT (757) Human Factors and Usability Case Studies (1036) Quality/Credibility of eHealth Information and Trust Issues (664) eHealth Literacy / Digital Literacy (550)

Published on in Vol 9 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/73642, first published .
Using Artificial Intelligence ChatGPT to Access Medical Information About Chemical Eye Injuries: Comparative Study

Using Artificial Intelligence ChatGPT to Access Medical Information About Chemical Eye Injuries: Comparative Study

Using Artificial Intelligence ChatGPT to Access Medical Information About Chemical Eye Injuries: Comparative Study

Authors of this article:

Layan Yousef Alharbi1 Author Orcid Image ;   Rema Rashed Alrashoud1 Author Orcid Image ;   Bader Shabib Alotaibi1 Author Orcid Image ;   Abdulaziz Meshal Al Dera1 Author Orcid Image ;   Raghad Saleh Alajlan1 Author Orcid Image ;   Reem Rashed AlHuthail2 Author Orcid Image ;   Dalal Ibrahim Alessa2 Author Orcid Image
Article Authors Cited by (1) Tweetations Metrics

Journals

  1. Kermansaravi A, Tonekabonipour E, Abdelhalim M, Dar S, Amr B. Critical evaluation of large language models for human cross-sectional anatomy identification: implications for collaborative intelligence. BMC Research Notes 2026 View