Accessibility settings

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

Generative Language Models Including ChatGPT (1676) Clinical Informatics (2431) Natural Language Processing (1356) Advanced Data Analytics in eHealth (390) Evaluation and Research Methodology for mHealth (412) Machine Learning (3378) Artificial Intelligence (5101) Data Science (732) AI Language Models in Health Care (863)

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 .
Robot doing bench press with flames, symbolizing fitness and AI

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
Article Authors Cited by (5) Tweetations Metrics

Journals

  1. Sugihara Y, Milosavljevic A, Jankovskaja S, Falk M. A review for navigating the trade-offs: evaluating open-source and proprietary large language models for clinical and biomedical information extraction. Frontiers in Digital Health 2026;8 View
  2. Platt S, Hier D, Yadamsuren B, Nguyen A, Hartzell V. Transforming FHIR into an OWL Knowledge Graph for Schema-Grounded Natural-Language Querying and Exploratory Data Analysis. Applied Sciences 2026;16(8):3936 View
  3. Ferreira J, Maia L, Correia R, Vilas A, Matos J, Vila-Chã N, Pereira M. Clinical summarization from FHIR bundles using model context protocol–orchestrated large language models: A scenario-based physician validation study. Next Research 2026;14:102565 View
  4. Gavai A, Heringa J. From Prediction to Interaction: A Behavioral Informatics Framework for AI in Preventive Health. Journal of Medical Internet Research 2026;28:e98961 View

Conference Proceedings

  1. Gao Y, Yu S, Huang Y. 2025 5th International Conference on Mechanical Automation and Electronic Information Engineering (MAEIE). Large-Model-Based Knowledge Transfer for Industrial Data Fusion and Interoperability Research View