A practical guide to the implementation of AI in orthopaedic research part 8: Resource management checklist for AI-driven research projects in orthopaedics
Review article, 2026
Artificial intelligence (AI) is transforming a multitude of medical fields, including orthopaedic surgery. AI-driven approaches such as machine learning, deep learning, natural language processing and large language models are being increasingly employed across various aspects of orthopaedic practice, offering innovative solutions for diagnostics, patient care and surgical training. To successfully execute an AI-driven orthopaedic project, the initial step involves defining the aim and rationale of the project. The study must be designed to answer a clinically relevant topic in a way that influences the behavior of the health professional and leads to better patient outcomes. Once this planning phase is complete, selecting the most appropriate AI model becomes crucial, as models differ in applications, costs and required staff expertise. After model selection, successful AI implementation demands ongoing monitoring and adaptation to ensure optimal performance and reliability. Achieving the best and most ethical outcomes requires interdisciplinary collaboration, combining clinical expertise with technological proficiency. Ultimately, a comprehensive approach to AI integration can lead to transformative advancements in orthopaedic surgery and medical research, paving the way for improved patient care and innovative treatment solutions.
Author
Umile Giuseppe Longo
Campus Bio-Medico University
Fondazione Policlinico Universitario Campus Bio-Medico
Benedetta Bandini
Campus Bio-Medico University
Fondazione Policlinico Universitario Campus Bio-Medico
Maristella Saccomanno
University of Brescia
Università degli Studi di Brescia
Pieter D'Hooghe
Aspetar Orthopaedic and Sports Medicine Hospital
Balint Zsidai
Sahlgrenska University Hospital
University of Gothenburg
Skåne University Hospital
Jacob F. Oeding
University of Gothenburg
Felix Oettl
University of Zürich
Hospital for Special Surgery - New York
Kristian Samuelsson
Sahlgrenska University Hospital
University of Gothenburg
Alessandro De Sire
Magna Græcia University
Robert Feldt
University of Gothenburg
Chalmers, Computer Science and Engineering (Chalmers), Software Engineering (Chalmers)
Yinan Yu
Chalmers, Computer Science and Engineering (Chalmers), Functional Programming
University of Gothenburg
Journal of Experimental Orthopaedics
2197-1153 (eISSN)
Vol. 13 1 e70623Subject Categories (SSIF 2025)
Orthopaedics
DOI
10.1002/jeo2.70623