*Result*: Artificial Intelligence in Dermatology: A Comprehensive Review of Approved Applications, Clinical Implementation, and Future Directions.
Title:
Artificial Intelligence in Dermatology: A Comprehensive Review of Approved Applications, Clinical Implementation, and Future Directions.
Authors:
Nahm WJ; New York University Grossman School of Medicine, New York, New York, USA., Sohail N; University of Illinois College of Medicine Rockford, Rockford, Illinois, USA., Burshtein J; Department of Dermatology, University of Illinois College of Medicine at Chicago, Chicago, Illinois, USA., Goldust M; Department of Dermatology, Yale University School of Medicine, New Haven, Connecticut, USA., Tsoukas M; Department of Dermatology, University of Illinois College of Medicine at Chicago, Chicago, Illinois, USA.
Source:
International journal of dermatology [Int J Dermatol] 2025 Sep; Vol. 64 (9), pp. 1568-1583. Date of Electronic Publication: 2025 May 19.
Publication Type:
Journal Article; Review
Language:
English
Journal Info:
Publisher: Blackwell Science Country of Publication: England NLM ID: 0243704 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1365-4632 (Electronic) Linking ISSN: 00119059 NLM ISO Abbreviation: Int J Dermatol Subsets: MEDLINE
Imprint Name(s):
Publication: Oxford : Blackwell Science
Original Publication: Philadelphia, Lippincott.
Original Publication: Philadelphia, Lippincott.
MeSH Terms:
References:
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Contributed Indexing:
Keywords: DermaSensor; MelaFind; Nevisense; algorithmic fairness; artificial intelligence; electrical impedance spectroscopy; machine learning; melanoma; multispectral imaging
Entry Date(s):
Date Created: 20250519 Date Completed: 20250808 Latest Revision: 20250808
Update Code:
20260130
DOI:
10.1111/ijd.17847
PMID:
40387622
Database:
MEDLINE
*Further Information*
*This comprehensive review examines artificial intelligence (AI) applications in dermatology, approved by the United States (U.S.) Food and Drug Administration (FDA) and international organizations, evaluating their clinical implementation and impact on healthcare delivery. We identified fifteen regulatory-approved AI devices globally, including three FDA-approved systems in the U.S. The FDA-approved devices primarily focused on melanoma and skin cancer detection through specialized hardware, while international platforms emphasized broader applications, mobile accessibility, and condition-specific tools for managing various skin conditions. Beyond these specific tools, we analyzed how AI can enhance clinical dermatology through screening systems, diagnostic support, administrative automation, and practice optimization. AI's integration into medical education can provide immediate feedback, support resident training, and complement traditional instruction, while patient education applications can improve treatment adherence through personalized content delivery. While AI shows promise across these domains, successful implementation requires addressing challenges in representation disparities, data privacy, algorithmic fairness, and clinical workflow integration. Future development should focus on standardized validation protocols, diverse training sets, robust real-world studies, and comprehensive assessment of patient outcomes beyond traditional performance metrics. AI's role appears most effective as augmentation to clinical expertise, particularly in improving access to specialized care and supporting clinical decision-making.
(© 2025 the International Society of Dermatology.)*