Faculty, Staff and Student Publications
Publication Date
1-1-2025
Journal
Nature Medicine
DOI
10.1038/s41591-024-03425-5
PMID
39779929
PMCID
PMC12104976
PubMedCentral® Posted Date
5-26-2025
PubMedCentral® Full Text Version
Author MSS
Abstract
Large language models (LLMs) are rapidly being adopted in healthcare, necessitating standardized reporting guidelines. We present transparent reporting of a multivariable model for individual prognosis or diagnosis (TRIPOD)-LLM, an extension of the TRIPOD + artificial intelligence statement, addressing the unique challenges of LLMs in biomedical applications. TRIPOD-LLM provides a comprehensive checklist of 19 main items and 50 subitems, covering key aspects from title to discussion. The guidelines introduce a modular format accommodating various LLM research designs and tasks, with 14 main items and 32 subitems applicable across all categories. Developed through an expedited Delphi process and expert consensus, TRIPOD-LLM emphasizes transparency, human oversight and task-specific performance reporting. We also introduce an interactive website ( https://tripod-llm.vercel.app/ ) facilitating easy guideline completion and PDF generation for submission. As a living document, TRIPOD-LLM will evolve with the field, aiming to enhance the quality, reproducibility and clinical applicability of LLM research in healthcare through comprehensive reporting.
Keywords
Humans, Artificial Intelligence, Guidelines as Topic, Research Design, Prognosis, Delphi Technique, Large Language Models
Published Open-Access
yes
Recommended Citation
Gallifant, Jack; Afshar, Majid; Ameen, Saleem; et al., "The TRIPOD-LLM Reporting Guideline for Studies Using Large Language Models" (2025). Faculty, Staff and Student Publications. 4841.
https://digitalcommons.library.tmc.edu/uthgsbs_docs/4841
Included in
Bioinformatics Commons, Biomedical Informatics Commons, Genetic Phenomena Commons, Medical Genetics Commons, Oncology Commons