Is orthopaedics entering the age of generative AI?—A narrative review of current applications, challenges, and future directions
Reviewartikel, 2025

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.

orthopaedic surgery

generative AI

large language models

artificial intelligence

surgical planning

Författare

Felix C. Oettl

Universität Zürich

James Pruneski

Tripler Regional Med Center

Bálint Zsidai

Sahlgrenska universitetssjukhuset

Skånes universitetssjukhus (SUS)

Göteborgs universitet

Yinan Yu

Chalmers, Data- och informationsteknik, Funktionell programmering

Göteborgs universitet

Ting Cong

University of Pittsburgh

Thomas Tischer

Universität Rostock

Malteser Waldkrankenhaus Erlangen

Michael T. Hirschmann

Universität Basel

Kantonsspital Baselland

Kristian Samuelsson

Sahlgrenska universitetssjukhuset

Göteborgs universitet

Knee Surgery, Sports Traumatology, Arthroscopy

0942-2056 (ISSN) 1433-7347 (eISSN)

Vol. In Press

Ämneskategorier (SSIF 2025)

Hälso- och sjukvårdsorganisation, hälsopolitik och hälsoekonomi

Ortopedi

Artificiell intelligens

DOI

10.1002/ksa.70145

PubMed

41144723

Mer information

Senast uppdaterat

2025-11-11