biostudies-literatureElfer KNHLBI NIH HHSNCI NIH HHSUS FDA100439https://www.ebi.ac.uk/biostudies/studies/S-EPMC12908141biostudies-literatureUnknown37(4)This work puts forth and demonstrates the utility of a reporting framework for collecting and evaluating annotations of medical images used for training and testing artificial intelligence (AI) models in assisting detection and diagnosis. AI has unique reporting requirements, as shown by the AI extensions to the Consolidated Standards of Reporting Trials (CONSORT) and Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) checklists and the proposed AI extensions to the Standards for Reporting Diagnostic Accuracy (STARD) and Transparent Reporting of a Multivariable Prediction model for Individual Prognosis or Diagnosis (TRIPOD) checklists. AI for detection and/or diagnostic image analysis requires complete, reproducible, and transparent reporting of the annotations andModern pathology : an official journal of the United States and Canadian Academy of Pathology, IncReproducible Reporting of the Collection and Evaluation of Annotations for Artificial Intelligence Models.PMC12908141R37 CA225655T32 HL007974Birmingham RDudgeon SNPan TGarcia VEhinger ALy AWen SGardecki EHytopoulos EBlenman KRMElfer KLi XHanna MGGallas BDChen WGreen ULennerz JKSalgado RPeeters DJESaltz JfalseReproducible Reporting of the Collection and Evaluation of Annotations for Artificial Intelligence Models.This work puts forth and demonstrates the utility of a reporting framework for collecting and evaluating annotations of medical images used for training and testing artificial intelligence (AI) models in assisting detection and diagnosis. AI has unique reporting requirements, as shown by the AI extensions to the Consolidated Standards of Reporting Trials (CONSORT) and Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) checklists and the proposed AI extensions to the Standards for Reporting Diagnostic Accuracy (STARD) and Transparent Reporting of a Multivariable Prediction model for Individual Prognosis or Diagnosis (TRIPOD) checklists. AI for detection and/or diagnostic image analysis requires complete, reproducible, and transparent reporting of the annotations and2024-01-01T00:00:00Z2024 Apr2026-07-16T05:12:00.787Z2026-07-09T10:36:50.322ZS-EPMC129081413828622110.1016/j.modpat.2024.100439