Year: 2026
Type: editorial
Abstract: Surgical artificial intelligence (AI) is typically validated on one patient population and then deployed unchanged into another, without surgeon input into its design. AI in orthopaedics should be built with surgeons, not simply for them: Surgeons should hold shared authority over the clinical question, data curation, validation, implementation, monitoring and retirement of any tool they use. Specialty-tuned models outperform general-purpose systems on some tasks, but the margin is modest and likely to narrow as generalist models improve. The more durable distinction is who controls the update loop-who can retrain a model on local outcomes, audit its failures and withdraw it when it drifts. Trial evidence shows that a clinician kept in that loop by design, not as an afterthought, outperforms working alone. What determines whether orthopaedic AI fulfils its promise is not model architecture, but who stays accountable to the surgeon at the bedside when the model needs to change.
DOI: 10.1002/jeo2.70920
Authors: Felix C. Oettl, Balint Zsidai, Jacob F. Oeding, Ting Cong, Elmar Herbst, Gergely Pánics, Philipp W. Winkler, Volker Musahl, Eric Hamrin Senorski, Romain Seil, Christophe Ley, Yinan Yu, Thomas Tischer, Stefano Zaffagnini, Umile Giuseppe Longo, Michael T. Hirschmann, Michael Hantes, Kristian Samuelsson
Institutions: Universitätsklinik Balgrist, Sahlgrenska University Hospital, University of Gothenburg, University of Pittsburgh, Gelenkpunkt, Semmelweis University, Fédération Internationale de Football Association, Uzsoki Hospital, Johannes Kepler University of Linz, Kepler Universitätsklinikum, Centre Hospitalier de Luxembourg, University of Luxembourg, Chalmers University of Technology, Malteser Waldkrankenhaus Erlangen, Universitätsmedizin Rostock, Istituto Ortopedico Rizzoli, Università Campus Bio-Medico, Campus Bio Medico University Hospital, University of Basel, Kantonsspital Baselland, Kantonsspital Baselland Standort Bruderholz, University of Thessaly
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $1,850
OpenAlex ID: W7214925514