在医学教育面临资源紧张与个性化需求激增的双重挑战下，局部解剖学教学亟待变革。本文中我们聚焦胸前壁局部解剖学，探索以人工智能为核心引擎的教学新范式。该范式坚守“虚实结合、实地解剖为本”的核心理念，深度重塑教学目标，构建“学生-计算机-教师”三位一体的智慧教学闭环。依托DeepSeek等智能技术的强大支撑，融合小组协作、分支教学、闯关考评等互动方式，实现从目标设定、计划定制、活动实施、任务达成、成果交流、多维评价到反思迭代的全流程智慧化转型。新范式以医学生为中心，通过数智化手段激发个性化深度学习潜能，无缝整合基础解剖知识与临床应用场景（如乳腺癌手术关键解剖、乳房重建皮瓣设计），显著提升临床决策能力，科研创新思维与医学人文素养，为智慧医学教育开辟新路径。 

Facing of mounting resource constraints and rising demands for personalization in medical education, regional anatomy teaching urgently requires transformation. In this paper, we focus on the regional anatomy of the thoracic wall, in order to explore a novel AI-driven teaching paradigm. Anchored in the core principle of “virtual-real integration with cadaveric dissection as the cornerstone,” the paradigm redefines educational objective  and constructs an intelligent, closed-loop teaching model integrating students, computers, and instructors. Leveraging the robust support of digital intelligence (e.g. , DeepSeek), this paradigm incorporates interactive method including group collaboration, branching instruction, and gamified assessments. It achieves a comprehensive intelligent transformation of the entire teaching process—from goal setting and plan customization to activity implementation, task completion, outcome exchange, multidimensional evaluation, and reflective iteration. This new paradigm centers on medical students and leverages digital intelligence to activate deep personalized learning potential. It seamlessly integrates fundamental anatomical knowledge with clinical scenarios (e.g. , key anatomy in breast cancer surgery, flap design in breast reconstruction), and significantly enhances clinical decision-making abilities, scientific research and innovative thinking, as well as medical humanistic literacy, paving a new path for intelligent medical education.