Artificial intelligence in planned orthopaedic care

Abstract

The integration of artificial intelligence (AI) into orthopaedic care has gained considerable interest in recent years, evidenced by the growing body of literature boasting wide-ranging applications across the perioperative setting. This includes automated diagnostic imaging, clinical decision-making tools, optimisation of implant design, robotic surgery, and remote patient monitoring. Collectively, these advances propose to enhance patient care and improve system efficiency. Musculoskeletal pathologies represent the most significant contributor to global disability, with roughly 1.71 billion people afflicted, leading to an increasing volume of patients awaiting planned orthopaedic surgeries. This has exerted a considerable strain on healthcare systems globally, compounded by both the COVID-19 pandemic and the effects of an ageing population. Subsequently, patients face prolonged waiting times for surgery, with further deterioration and potentially poorer outcomes as a result. Furthermore, incorporating AI technologies into clinical practice could provide a means of addressing current and future service demands. This review aims to present a clear overview of AI applications across preoperative, intraoperative, and postoperative stages to elucidate its potential to transform planned orthopaedic care.

Keywords: Artificial intelligence; Deep learning; Machine learning; Planned orthopaedic care.

Figure 1

The applications of artificial intelligence in planned orthopaedic care discussed in this article. AI = artificial intelligence, OA = osteoarthritis, TKA = total knee arthroplasty, THA = total hip arthroplasty, NLP = natural language processing, EPR = electronic patient records, PROM = patient-reported outcome measure,, AR = augmented reality.