Han Fei, Huang Xiao, Wang Xin, Chen Yong-Feng, Lu Chuang, Li Shasha, Lu Lu, Zhang Da-Wei
Department of Orthopedics Xijing Hospital Air Force Medical University Xi'an China.
Department of Orthopedics The 990th Hospital of the Joint Logistics Support Force Zhumadian China.
MedComm (2020). 2025 Jun 25;6(7):e70260. doi: 10.1002/mco2.70260. eCollection 2025 Jul.
Artificial intelligence (AI) drives transformative changes in orthopedic surgery, steering it toward precision and personalization through intelligent applications in preoperative planning, intraoperative assistance, and postoperative rehabilitation/monitoring. Breakthroughs in deep learning, robotics, and multimodal data fusion have enabled AI to demonstrate significant advantages. Nonetheless, current applications face challenges such as limited real-time decision autonomy, fragmented medical data silos, standardization gaps restricting model generalization, and ethical/regulatory frameworks lagging behind technological advancements. Therefore, a critical analysis of the current status of AI and the acceleration of its clinical translation is urgently required. This study systematically reviews the core advancements, challenges, and future directions of AI in orthopedic surgery from technical, clinical, and ethical perspectives. It elaborates on the "perceptual-decisional-executional" intelligent closed loop formed by algorithmic innovation and hardware upgrades, summarizes AI applications across surgical continuum, analyzes ethical and regulatory challenges, and explores emerging trajectories. This review integrates the end-to-end applications of AI in orthopedics, illustrating its evolution. It introduces an "algorithm-hardware-ethics trinity" framework for technical translation, providing methodological guidance for interdisciplinary collaboration. Additionally, it evaluates the combined efficacy of diverse algorithms and devices through practical cases and details of future research frontiers, aiming to inform researchers of current landscapes and guide subsequent investigations.
人工智能（AI）推动了骨科手术的变革性变化，通过在术前规划、术中辅助以及术后康复/监测中的智能应用，将其导向精准化和个性化。深度学习、机器人技术和多模态数据融合方面的突破使人工智能展现出显著优势。尽管如此，当前的应用面临着诸如实时决策自主性有限、医疗数据孤岛碎片化、限制模型泛化的标准化差距以及伦理/监管框架落后于技术进步等挑战。因此，迫切需要对人工智能的现状进行批判性分析，并加速其临床转化。本研究从技术、临床和伦理角度系统回顾了人工智能在骨科手术中的核心进展、挑战及未来方向。阐述了由算法创新和硬件升级形成的“感知-决策-执行”智能闭环，总结了人工智能在整个手术连续过程中的应用，分析了伦理和监管挑战，并探索了新兴轨迹。本综述整合了人工智能在骨科中的端到端应用，展示了其发展历程。介绍了一个用于技术转化的“算法-硬件-伦理三位一体”框架，为跨学科合作提供方法指导。此外，通过实际案例和未来研究前沿细节评估了各种算法和设备的综合效果，旨在让研究人员了解当前情况并指导后续研究。
