皮肤病学中的人工智能:批准应用、临床实施和未来方向的综合综述。

IF 3.5 4区 医学 Q1 DERMATOLOGY
William J Nahm, Nayyab Sohail, Joshua Burshtein, Mohamad Goldust, Maria Tsoukas
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引用次数: 0

摘要

本文全面审查了美国(U.S.)批准的人工智能(AI)在皮肤科的应用。美国食品和药物管理局(FDA)和国际组织,评估其临床实施和对医疗保健服务的影响。我们在全球确定了15个监管部门批准的人工智能设备,其中包括美国fda批准的3个系统。fda批准的设备主要专注于通过专业硬件检测黑色素瘤和皮肤癌,而国际平台强调更广泛的应用、移动可访问性和针对各种皮肤状况的特定工具。除了这些特定的工具,我们还分析了人工智能如何通过筛查系统、诊断支持、管理自动化和实践优化来增强临床皮肤科。人工智能与医学教育的整合可以提供即时反馈,支持住院医师培训,并补充传统教学,而患者教育应用可以通过个性化的内容交付来提高治疗依从性。虽然人工智能在这些领域显示出前景,但成功实施需要解决代表性差异、数据隐私、算法公平性和临床工作流程集成方面的挑战。未来的发展应侧重于标准化的验证方案、多样化的训练集、可靠的现实世界研究以及超越传统绩效指标的患者结果综合评估。人工智能的作用似乎最有效的是增强临床专业知识,特别是在改善获得专业护理和支持临床决策方面。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.

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来源期刊
CiteScore
4.70
自引率
2.80%
发文量
476
审稿时长
3 months
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.
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