The Role of Artificial Intelligence in Hip and Knee Arthroplasty: A Systematic Literature Review

Abstract

Background: The rapid advancement of artificial intelligence (AI) is significantly impacting orthopaedic surgery, especially hip and knee arthroplasty. Machine learning and deep learning are increasingly being used to improve diagnostic accuracy, enhance surgical planning, support surgical navigation, and assist in postoperative care.

Method: A systematic literature review was conducted using the PRISMA guidelines to examine AI applications in hip and knee arthroplasty.

Results: The search identified 290 studies across two databases, of which 56 met the inclusion criteria. The findings were evaluated across three clinical phases: preoperative, intraoperative, and postoperative. In the preoperative phase, AI contributes to the automated interpretation of imaging studies, patient selection, risk stratification, and the personalised planning of implants. Navigation systems and robot-assisted surgical solutions increase procedural accuracy and optimise implant placement during surgery. In the postoperative phase, AI models can predict recovery outcomes, support personalised rehabilitation, and monitor the risk of complications.

Conclusion: Artificial intelligence is revolutionising hip and knee arthroplasty by improving surgical precision, enabling a patient-centred approach, and enhancing outcome prediction across the entire continuum of care. Further research to overcome current limitations and expand application areas will allow AI to play an even greater role in the future of orthopaedic surgery.