Is orthopaedics entering the age of generative AI?—A narrative review of current applications, challenges, and future directions

作者
Felix C. Oettl,James A. Pruneski,Bálint Zsidai,Yinan Yu,Ting Cong,Thomas Tischer,Michael T. Hirschmann,Kristian Samuelsson
出处
期刊:Knee Surgery, Sports Traumatology, Arthroscopy [Springer Nature]
标识
DOI:10.1002/ksa.70145
摘要

Abstract Artificial intelligence (AI) in medicine is undergoing a pivotal transformation, evolving from discriminative models that classify data to generative AI systems capable of creating novel content. Generative AI is a type of artificial intelligence that can learn from and mimic large amounts of data to create content such as text, images, music, videos, code, and more. The generative AI paradigm relies on advanced architectures, including large language models (LLMs), which are likely to redefine key processes in the practice of clinical medicine. The imaging‐ and procedure‐heavy specialty of orthopaedic surgery is uniquely positioned to benefit from innovations in spatial reasoning, biomechanical analysis, and procedural planning using generative AI. Key applications are rapidly emerging, like streamlining clinical workflows through automated documentation, the mediation of patient‐provider communication and enhanced interpretability of complex medical information. While an exciting field the current evidence base is quite limited. The continued integration of these technologies promises to enhance surgical precision, democratise access to advanced planning, and ultimately improve patient outcomes. However, realising this potential requires overcoming significant challenges related to the ‘black box’ nature of models, data bias, and evolving regulatory oversight. Rigorous clinical validation through prospective trials will be essential to ensure the safe, effective, and equitable implementation of generative AI in the future of orthopaedic care. Level of Evidence Level V.
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