Prasetia Renaldi, Liu Felly, Hananto Joshua Edward, Purwana Siti Zainab Bani, Kholinne Erica, Dilogo Ismail Hadisoebroto
Department of Orthopaedics - Traumatology, Hasan-Sadikin General Hospital, Universitas Padjadjaran, Bandung, Indonesia.
Faculty of Medicine, Hasan-Sadikin General Hospital, Universitas Padjadjaran, Bandung, Indonesia.
J Orthop Surg (Hong Kong). 2026 Jan-Apr;34(1):10225536261424034. doi: 10.1177/10225536261424034. Epub 2026 Feb 12.
Generative artificial intelligence (AI) is a powerful class of machine learning that moves beyond simply analysing data to actually creating new and original content, such as medical images or clinical text. The use of generative AI is varied in orthopaedic surgery. Generative AI moves us from one-size-fits-all surgical planning to highly personalised surgical blueprints for each patient's unique anatomy and condition. While generative AI in surgery is new, it can provide real-time intelligent help to a surgeon's skill and decision-making. Most practitioners see the use of AI as a tool to improve diagnosis and treatment, with some expressing their concern that it will conversely worsen diagnosis and treatment. With its use and potential, the use of generative AI currently should be supervised and validated, as it has been shown that sometimes the generated content does not reference to any actual source. Policies and economic values are also detrimental to the integration of AI technologies in clinical orthopaedics. Ethical issues, practitioners view and perspective, and the high overall cost of AI technology use, are among the barriers that may emerge. This comprehensive review addresses the opportunities, challenges, and future direction of integrating generative AI in orthopaedic surgery.
生成式人工智能(AI)是一类强大的机器学习技术,它不仅能简单地分析数据,还能实际创建新的原创内容,如医学图像或临床文本。生成式AI在骨科手术中的应用多种多样。生成式AI使我们从一刀切的手术规划转变为针对每个患者独特解剖结构和病情的高度个性化手术蓝图。虽然手术中的生成式AI尚属新生事物,但它可以为外科医生的技能和决策提供实时智能帮助。大多数从业者将AI的使用视为改善诊断和治疗的工具,也有一些人担心它会反过来使诊断和治疗恶化。鉴于其用途和潜力,目前生成式AI的使用应受到监督和验证,因为已经表明有时生成的内容并未参考任何实际来源。政策和经济价值也不利于AI技术在临床骨科中的整合。伦理问题、从业者的观点和看法,以及AI技术使用的高昂总成本,都是可能出现的障碍。这篇综述探讨了在骨科手术中整合生成式AI的机遇、挑战和未来方向。