Checklist for Evaluation of Image-Based Artificial Intelligence Reports in Dermatology: CLEAR Derm Consensus Guidelines From the International Skin Imaging Collaboration Artificial Intelligence Working Group - Barata, Catarina; Betz-Stablein, Brigid; Emre Celebi, M; Codella, Noel; Combalia, Marc; Guitera, Pascale; Gutman, David; Halpern, Allan; Helba, Brian; Kittler, Harald; Kose, Kivanc; Liopyris, Konstantinos; et al. (JAMA Dermatology, 2021)
Importance 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. Objective To consolidate limited existing literature with expert opinion to guide developers and reviewers of dermatology AI. Evidence review 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. Findings A checklist of items was developed that outlines best practices of image-based AI development and assessment in dermatology. Conclusions and relevance Clinically effective AI needs to be fair, reliable, and safe; this checklist of best practices will help both developers and reviewers achieve this goal.