A practical guide to the implementation of AI in orthopaedic research part 8: Resource management checklist for AI-driven research projects in orthopaedics
Reviewartikel, 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.
Författare
Umile Giuseppe Longo
Università Campus Bio-Medico di Roma
Fondazione Policlinico Universitario Campus Bio-Medico
Benedetta Bandini
Università Campus Bio-Medico di Roma
Fondazione Policlinico Universitario Campus Bio-Medico
Maristella Saccomanno
Universita degli Studi di Brescia
Università degli Studi di Brescia
Pieter D'Hooghe
Aspetar Orthopaedic and Sports Medicine Hospital
Balint Zsidai
Sahlgrenska universitetssjukhuset
Göteborgs universitet
Skånes universitetssjukhus (SUS)
Jacob F. Oeding
Göteborgs universitet
Felix Oettl
Universität Zürich
Hospital for Special Surgery - New York
Kristian Samuelsson
Sahlgrenska universitetssjukhuset
Göteborgs universitet
Alessandro De Sire
Universita degli studi Magna Graecia di Catanzaro
Robert Feldt
Göteborgs universitet
Chalmers, Data- och informationsteknik, Software Engineering
Yinan Yu
Chalmers, Data- och informationsteknik, Funktionell programmering
Göteborgs universitet
Journal of Experimental Orthopaedics
2197-1153 (eISSN)
Vol. 13 1 e70623Ämneskategorier (SSIF 2025)
Ortopedi
DOI
10.1002/jeo2.70623