Checklist for Evaluation of Image-Based Artificial Intelligence Reports in Dermatology

• DOI: 10.1001/jamadermatol.2021.4915
• Publication Date: 2021-12-01T18:03:52Z
• Authors: Roxana Daneshjou; Catarina Barata; Brigid Betz-Stablein; M. Emre Celebi; Noel Codella; Marc Combalia; Pascale Guitera; David Gutman; Allan Halpern; Brian Helba; Harald Kittler; Kivanc Kose; Konstantinos Liop...; Josep Malvehy; Han Seung Seog; H. Peter Soyer; Eric R. Tkaczyk; Philipp Tschandl; Veronica Rotemberg
• Keywords: 0301 basic medicine; 03 medical and health sciences; Consensus; Artificial Intelligence; Humans; Reproducibility of Results; Dermatology; 3. Good health; Checklist

The use of artificial intelligence (AI) is accelerating in all aspects of medicine and has the potential to transform clinical care and dermatology workflows. However, to develop image-based algorithms for dermatology applications, comprehensive criteria establishing development and performance evaluation standards are required to ensure product fairness, reliability, and safety.To consolidate limited existing literature with expert opinion to guide developers and reviewers of dermatology AI.In this consensus statement, the 19 members of the International Skin Imaging Collaboration AI working group volunteered to provide a consensus statement. A systematic PubMed search was performed of English-language articles published between December 1, 2008, and August 24, 2021, for "artificial intelligence" and "reporting guidelines," as well as other pertinent studies identified by the expert panel. Factors that were viewed as critical to AI development and performance evaluation were included and underwent 2 rounds of electronic discussion to achieve consensus.A checklist of items was developed that outlines best practices of image-based AI development and assessment in dermatology.Clinically effective AI needs to be fair, reliable, and safe; this checklist of best practices will help both developers and reviewers achieve this goal.