ArticleJAMA dermatology2022
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.
Article in JAMA dermatology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07765303 (Skin Pigment Type, Phototype and Photodamage Determination Using Image Analyses Powered by Artificial Intelligence - SPAI Study), which is not on this map. Cited by 77 papers, 7 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Skin Pigment Type, Phototype and Photodamage Determination Using Image Analyses Powered by Artificial Intelligence - SPAI Study
Who cites it
77 citing papers in PubMed, 7 syntheses or guidelines pooled it.
- Artificial Intelligence technologies for assessing skin lesions for referral on the urgent suspected cancer pathway to detect benign lesions and reduce secondary care specialist appointments: early value assessment.Health technology assessment (Winchester, England) · 2026Pooled it
- Use of AI in Identification of Sexually Transmitted Infections and Anogenital Dermatoses: A Systematic Review and Meta-Analysis.JAMA network open · 2025Pooled it
- AI for IMPACTS Framework for Evaluating the Long-Term Real-World Impacts of AI-Powered Clinician Tools: Systematic Review and Narrative Synthesis.Journal of medical Internet research · 2025Pooled it
- Artificial intelligence in the risk prediction models of cardiovascular disease and development of an independent validation screening tool: a systematic review.BMC medicine · 2024Pooled it
- Guidelines, Consensus Statements, and Standards for the Use of Artificial Intelligence in Medicine: Systematic Review.Journal of medical Internet research · 2023Pooled it
- Evaluation of Risk of Bias in Neuroimaging-Based Artificial Intelligence Models for Psychiatric Diagnosis: A Systematic Review.JAMA network open · 2023Pooled it
- Artificial Intelligence for the Classification of Pigmented Skin Lesions in Populations with Skin of Color: A Systematic Review.Dermatology (Basel, Switzerland) · 2023Pooled it
- Smartphone Applications in Dermatology With Special Focus on AI: A European-Continent-Based Review.International journal of dermatology · 2026Review
- Diagnostic Accuracy of Commercial Large Language Models for Anogenital Skin Lesion Images: A Comparative Study of Gemini, Claude, and ChatGPT.The Journal of infectious diseases · 2026Article
- The Evolving Role of Artificial Intelligence in Dermatology: A Meta-Analysis of Diagnostic Performance, Clinical Applications, and Implementation Challenges (2003-2025).Diagnostics (Basel, Switzerland) · 2026Review
- Automated Skin Lesion and Cancer Detection Using Computer Vision: A Comprehensive Review.Bioengineering (Basel, Switzerland) · 2026Review
- Evaluation Frameworks for Clinical AI Incorporating Validation Strategies, Real-World Applicability, and Ethical Principles: Scoping Review.Journal of medical Internet research · 2026Article
- Enhanced Diagnosis of Generalized Pustular Psoriasis With the Legit.Health Device as a Diagnosis Support Tool: Multireader Multicase Study.JMIR dermatology · 2026Article
- Overdiagnosis of Melanoma In Situ.Journal of clinical medicine · 2026Review
- Artificial Intelligence in Non-Surgical Cosmetic Procedures: A Multi-Stakeholder Revolution.Aesthetic plastic surgery · 2026Review
- AI-assisted basal cell carcinoma diagnosis with LC-OCT: A multicentric retrospective study.Journal of the European Academy of Dermatology and Venereology : JEADV · 2026Article
- When AI and Experts Agree on Error: Intrinsic Ambiguity in Dermatoscopic Images.Journal of imaging · 2026Article
- ChatGPT, Gemini, and Claude in clinical and dermoscopic image analysis of basal cell carcinoma and its common mimickers: A comparative performance analysis.JID innovations : skin science from molecules to population health · 2026Article
- Patient Perspectives on the Use of Artificial Intelligence in Malignant Melanoma Diagnosis.Dermatology practical & conceptual · 2026Article
- Assessing public interest in artificial intelligence in dermatology: A Google Trends analysis.JID innovations : skin science from molecules to population health · 2026Article
17 more citing papers are in PubMed but not listed here.
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Authors and funding
19 authors.
Funding
Abstract
importanceThe 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.
objectiveTo 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.
findingsA 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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.