Why
CLAIRE?
Artificial intelligence is increasingly used in diagnostic imaging. Yet inconsistent reporting makes it difficult to determine how models were developed, validated and intended to be used.
Important information on datasets, model training, validation procedures, performance, generalizability and clinical applicability is frequently absent or insufficiently described, limiting reproducibility and critical appraisal.
CLAIRE was developed to address these recurring gaps by providing a unified structure for reporting and assessing the completeness and transparency of AI-based diagnostic imaging research.
The initiative began with the development and initial evaluation of the CLAIRE Framework. It is now entering a broader methodological phase aimed at developing the CLAIRE Statement through evidence review, formal project registration, publication of a development protocol, international stakeholder consultation, consensus methods and subsequent pilot testing.
This staged approach preserves the published framework as CLAIRE's foundation while allowing recommendations to evolve through a transparent and internationally informed process.
CLAIRE Framework
Six principles, 15-item checklist, editorial reference guide and standardized scoring system.
CLAIRE Statement
A broader reporting statement developed through a documented international consensus process.
Read the scientific rationale in a letter from the Research Lead ↗