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

Applications of AI (806) Consumer & Patient Education and Shared-Decision Making (1228) eHealth Literacy / Digital Literacy (847) Quality/Credibility of eHealth Information and Trust Issues (916) Generative Language Models Including ChatGPT (1371)

Published on in Vol 5 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/77149, first published .
Smartphone screen displays "What can I help with?" prompt for virtual assistant.

Leveraging Large Language Models to Improve the Readability of German Online Medical Texts: Evaluation Study

Leveraging Large Language Models to Improve the Readability of German Online Medical Texts: Evaluation Study

Authors of this article:

Amela Miftaroski1 Author Orcid Image ;   Richard Zowalla1, 2 Author Orcid Image ;   Martin Wiesner1, 3 Author Orcid Image ;   Monika Pobiruchin1, 3 Author Orcid Image
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Journals

  1. Widhani A, Maria S, Chairani A, Visco N, Nurhadi M, Harjoprawito L, Elvira D, Tedja I, Yuniza Y, Fetarayani D, Koesnoe S, Wicaksana B, Hasibuan A, Yunihastuti E. Comparing the Accuracy of ChatGPT-4o, DeepSeek-V3, and Gemini 2.5 Flash in Answering Frequently Asked Questions About Systemic Lupus Erythematosus: Quantitative Study. JMIR Formative Research 2026;10:e89156 View