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Artificial Intelligence in Dermatology Education: Applications, Opportunities, and Strategic Principles for Sustainable Talent DevelopmentOA

中文摘要

Dermatological diagnosis is inherently visual,greatly relying on clinicians′interpretation of images and accumulated experience.Traditional teaching models have long been constrained by limited case diversity,lack of personalization,and inadequate assessment of competency development.Recent advances in artificial intelligence(AI)offer new technological support for dermatology education.To address the risk of fragmented adoption,a process-oriented approach,conceptualizing AI-assisted dermatology education as an integrated system embedded throughout the learning process is adopted.Within this framework,AI is not only examined as an isolated tool but also as a component aligned with educational workflows.AI′s primary applications in dermatology education are analyzed,focusing on its potential to improve standardization so as to expand access to high-quality resources and support competency-based teaching,and facilitate lifelong learning.Meaningful educational benefits emerge when AI is systematically integrated into structured teaching processes.However,associated risks-including data bias,learner overreliance,implementation constraints,and potential impacts on medical humanities education must also be considered.Based on these findings,the strategic principles centered on educational objectives are proposed,emphasizing human-AI collaboration,transparency,and continuous governance to support the sustainable development of dermatology talent.

PENG Leixuan;GAO Canni;LUAN Mei

Department of Dermatology,The First Affiliated Hospital of Xi′an Jiaotong University,Xi′an 710061,ChinaDepartment of Dermatology,The First Affiliated Hospital of Xi′an Jiaotong University,Xi′an 710061,ChinaDepartment of Dermatology,The First Affiliated Hospital of Xi′an Jiaotong University,Xi′an 710061,China

医药卫生

artificial intelligencedermatology educationtalent cultivationsustainability

《International Journal of Plant Engineering and Management》 2026 (1)

P.49-64,16

10.13434/j.cnki.1007-4546.2026.0104

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