William J Nahm, Nayyab Sohail, Joshua Burshtein, Mohamad Goldust, Maria Tsoukas
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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.</p>","PeriodicalId":13950,"journal":{"name":"International Journal of Dermatology","volume":" ","pages":""},"PeriodicalIF":3.5000,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Artificial Intelligence in Dermatology: A Comprehensive Review of Approved Applications, Clinical Implementation, and Future Directions.\",\"authors\":\"William J Nahm, Nayyab Sohail, Joshua Burshtein, Mohamad Goldust, Maria Tsoukas\",\"doi\":\"10.1111/ijd.17847\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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. 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Artificial Intelligence in Dermatology: A Comprehensive Review of Approved Applications, Clinical Implementation, and Future Directions.
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.
期刊介绍:
Published monthly, the International Journal of Dermatology is specifically designed to provide dermatologists around the world with a regular, up-to-date source of information on all aspects of the diagnosis and management of skin diseases. Accepted articles regularly cover clinical trials; education; morphology; pharmacology and therapeutics; case reports, and reviews. Additional features include tropical medical reports, news, correspondence, proceedings and transactions, and education.
The International Journal of Dermatology is guided by a distinguished, international editorial board and emphasizes a global approach to continuing medical education for physicians and other providers of health care with a specific interest in problems relating to the skin.