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

Theme Issue (2023): AI and ChatGPT in Dermatology (13) Natural Language Processing (692) New Methods and Approaches in Medical Education (232) Testing and Assessment in Medical Education (52) Generative Language Models Including ChatGPT (311) Chatbots and Conversational Agents (531) Dermatology (45)

Published on in Vol 7 (2024)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/55898, first published .
Assessing the Application of Large Language Models in Generating Dermatologic Patient Education Materials According to Reading Level: Qualitative Study

Assessing the Application of Large Language Models in Generating Dermatologic Patient Education Materials According to Reading Level: Qualitative Study

Assessing the Application of Large Language Models in Generating Dermatologic Patient Education Materials According to Reading Level: Qualitative Study

Authors of this article:

Raphaella Lambert1 Author Orcid Image ;   Zi-Yi Choo1 Author Orcid Image ;   Kelsey Gradwohl2 Author Orcid Image ;   Liesl Schroedl2 Author Orcid Image ;   Arlene Ruiz De Luzuriaga2 Author Orcid Image
Article Authors Cited by (4) Tweetations (3) Metrics

Journals

  1. Behers B, Vargas I, Behers B, Rosario M, Wojtas C, Deevers A, Hamad K. Assessing the Readability of Patient Education Materials on Cardiac Catheterization From Artificial Intelligence Chatbots: An Observational Cross-Sectional Study. Cureus 2024 View
  2. Oliva A, Pasick L, Hoffer M, Rosow D. Improving readability and comprehension levels of otolaryngology patient education materials using ChatGPT. American Journal of Otolaryngology 2024;45(6):104502 View
  3. Aydin S, Karabacak M, Vlachos V, Margetis K. Large language models in patient education: a scoping review of applications in medicine. Frontiers in Medicine 2024;11 View
  4. Joshi S, Ha E, Amaya A, Mendoza M, Rivera Y, Singh V. Ensuring Accuracy and Equity in Vaccination Information From ChatGPT and CDC: Mixed-Methods Cross-Language Evaluation. JMIR Formative Research 2024;8:e60939 View