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

Responsible Health AI (87) mHealth in a Clinical Setting (776) Decision Support for Health Professionals (1644) Generative Language Models Including ChatGPT (825) Clinical Informatics (1450)

Published on in Vol 5 (2026)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/83640, first published .
Performance of Large Language Models Under Input Variability in Health Care Applications: Dataset Development and Experimental Evaluation

Performance of Large Language Models Under Input Variability in Health Care Applications: Dataset Development and Experimental Evaluation

Performance of Large Language Models Under Input Variability in Health Care Applications: Dataset Development and Experimental Evaluation

Authors of this article:

Saubhagya Joshi1 Author Orcid Image ;   Monjil Mehta2 Author Orcid Image ;   Sarjak Maniar2 Author Orcid Image ;   Mengqian Wang3 Author Orcid Image ;   Vivek Kumar Singh1 Author Orcid Image
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Journals

  1. Harada Y. Safety Audit of a Large Language Model for Lay Self-Triage Using Japanese Symptom Vignettes: Persistent Red-Flag Under-Triage Despite Improved Reproducibility Under Near-Deterministic Decoding. Cureus 2026 View