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Synapse
March 1, 2026Diagnostic and Interventional Radiology0 citationsOpen Access

Reporting checklist for foundation and large language models in medical research (REFINE): an international consensus guideline

IMIsmail MeseTDTugba Akinci D’AntonoliCBChristian Bluethgen

Key Points

  • The aim is to establish a guideline for reporting on foundation models and large language models in medical research.
  • Developed an international consensus guideline through expert collaboration.
  • Focused on standards for reporting FM and LLM studies.
  • Aimed at improving transparency and reproducibility.
  • Promotes better reporting practices in medical AI research.
  • Enhances comparability of studies for reliable evidence synthesis.

Abstract

The REFINE enables transparent, comparable, and reproducible reporting of FM and LLM studies, supporting reliable evidence synthesis in medical and imaging-focused AI studies.

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Cite This Study

Mese et al. (2026) studied this question.

synapsesocial.com/papers/69a3d747ec16d51705d2dc46https://doi.org/10.4274/dir.2026.263812
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1MEDAI-LLM-SUMM: a reporting checklist for medical text summarization studies using large language models2026 · 2 citations
  2. 2Guidelines for Reporting Studies on Large Language Models in Radiology: An International Delphi Expert Survey2026 · 6 citations
  3. 3Building a Safe and Transparent Workflow for Large Language Model (LLM)-Assisted Clinical Trials and Prediction Models: A Technical Report2025
  4. 4Insufficient reporting quality in large language model studies in the field of radiology2026 · 4 citations
  5. 5Towards Comprehensive Benchmarking of Medical Vision Language Models2025