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

Results — Model Performance

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

Other Information

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


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