CLAIM 2024 Items The 44 items of the CLAIM 2024 guideline are listed below, grouped by section. Select any item from the sidebar or the table to view its definition, explanation, elaboration, and illustrative examples.
Title / Abstract Item Title Item 1 Identification as a study of AI methodology
Abstract Item Title Item 2 Summary of study design, methods, results, and conclusions
Introduction Item Title Item 3 Scientific and/or clinical background Item 4 Study aims, objectives, and hypotheses
Methods — Study Design Item Title Item 5 Prospective or retrospective study Item 6 Study goal
Methods — Data Item Title Item 7 Data sources Item 8 Inclusion and exclusion criteria Item 9 Data pre-processing Item 10 Selection of data subsets Item 11 De-identification methods Item 12 How missing data were handled Item 13 Image acquisition protocol
Methods — Reference Standard Item Title Item 14 Definition of methods used to obtain reference standard Item 15 Rationale for choosing the reference standard Item 16 Source of reference standard annotations Item 17 Annotation of test set Item 18 Measures of inter- and intra-rater variability
Methods — Data Partitions Item Title Item 19 How data were assigned to partitions Item 20 Level at which partitions are disjoint
Methods — Testing Data Item Title Item 21 Intended sample size
Methods — Model Item Title Item 22 Detailed description of model Item 23 Software libraries, frameworks, and packages Item 24 Initialization of model parameters
Methods — Training Item Title Item 25 Details of training approach Item 26 Method of selecting the final model Item 27 Ensembling techniques
Methods — Evaluation Item Title Item 28 Metrics of model performance Item 29 Statistical measures of significance and uncertainty Item 30 Robustness or sensitivity analysis Item 31 Methods for explainability or interpretability Item 32 Evaluation on internal data Item 33 Testing on external data Item 34 Clinical trial registration
Results — Data Item Title Item 35 Numbers of patients or examinations included and excluded Item 36 Demographic and clinical characteristics
Item Title Item 37 Performance metrics and measures of statistical uncertainty Item 38 Estimates of diagnostic performance and their precision Item 39 Failure analysis of incorrect results
Discussion Item Title Item 40 Study limitations Item 41 Implications for practice
Item Title Item 42 Reference to full study protocol or additional technical details Item 43 Availability of software, trained model, and/or data Item 44 Sources of funding and other support; role of funders
Table of contents