Related Experiment Video
Updated: Jan 17, 2026

Introduction of an Integrated Pathology Image Management, Artificial Intelligence, and Reporting System
Published on: July 11, 2025
The STARD-AI reporting guideline for diagnostic accuracy studies using artificial intelligence
Viknesh Sounderajah1,2, Ahmad Guni1,2, Xiaoxuan Liu3,4
1Institute of Global Health Innovation, Imperial College London, London, UK.
None:
The Standards for Reporting Diagnostic Accuracy (STARD) 2015 statement facilitates transparent and complete reporting of diagnostic test accuracy studies. However, there are unique considerations associated with artificial intelligence (AI)-centered diagnostic test studies. The STARD-AI statement, which was developed through a multistage, multistakeholder process, provides a minimum set of criteria that allows for comprehensive reporting of AI-centered diagnostic test accuracy studies. The process involved a literature review, a scoping survey of international experts, and a patient and public involvement and engagement initiative, culminating in a modified Delphi consensus process involving over 240 international stakeholders and a consensus meeting. The checklist was subsequently finalized by the Steering Committee and includes 18 new or modified items in addition to the STARD 2015 checklist items. Authors are encouraged to provide descriptions of dataset practices, the AI index test and how it was evaluated, as well as considerations of algorithmic bias and fairness. The STARD-AI statement supports comprehensive and transparent reporting in all AI-centered diagnostic accuracy studies, and it can help key stakeholders to evaluate the biases, applicability and generalizability of study findings.
Related Concept Videos
Receiver Operating Characteristic Plot
Sensitivity, Specificity, and Predicted Value
Sensitivity is the...

