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

Generative Language Models Including ChatGPT (708) Clinical Informatics (1325) Natural Language Processing (917) Evaluation and Research Methodology for mHealth (242) Machine Learning (2074) Artificial Intelligence (2127) AI Language Models in Health Care (202) Data Science (357) Advanced Data Analytics in eHealth (209)

Published on in Vol 27 (2025)

This is a member publication of University of Duisburg-Essen

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/73540, first published .
Using a Diverse Test Suite to Assess Large Language Models on Fast Health Care Interoperability Resources Knowledge: Comparative Analysis

Using a Diverse Test Suite to Assess Large Language Models on Fast Health Care Interoperability Resources Knowledge: Comparative Analysis

Using a Diverse Test Suite to Assess Large Language Models on Fast Health Care Interoperability Resources Knowledge: Comparative Analysis

Authors of this article:

Ahmad Idrissi-Yaghir1, 2 Author Orcid Image ;   Kamyar Arzideh2, 3 Author Orcid Image ;   Henning Schäfer2, 4 Author Orcid Image ;   Bahadir Eryilmaz2 Author Orcid Image ;   Mikel Bahn2 Author Orcid Image ;   Yutong Wen2 Author Orcid Image ;   Katarzyna Borys1, 2 Author Orcid Image ;   Eva Hartmann5 Author Orcid Image ;   Cynthia Schmidt2, 4 Author Orcid Image ;   Obioma Pelka1, 2 Author Orcid Image ;   Johannes Haubold1, 2 Author Orcid Image ;   Christoph M Friedrich6, 7 Author Orcid Image ;   Felix Nensa1, 2 Author Orcid Image ;   René Hosch1, 2 Author Orcid Image
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