Reproducible Reporting of the Collection and Evaluation of Annotations for Artificial Intelligence Models
This work advances 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 CONSORT (Consolidated Standards of Reporting Trials) and SPIRIT (Standard Protocol Items