The Application of artificial intelligence in periprosthetic joint infection

• For the first time, we systematically and comprehensively elaborated on the relevant progress of AI technology in the prevention, diagnosis, and treatment of PJI. • We focused on reviewing the applications and prospects of AI technologies such as machine learning and robotic technology in the risk prediction of PJI, the diagnosis combined with various existing technologies, and the field of treatment. • This paper summarized and expounds the current challenges and future development directions of AI in PJI field. Periprosthetic joint infection (PJI) represents one of the most devastating complications following total joint arthroplasty, often necessitating additional surgeries and antimicrobial therapy, and potentially leading to disability. This significantly increases the burden on both patients and the healthcare system. Given the considerable suffering caused by PJI, its prevention and treatment have long been focal points of concern. However, challenges remain in accurately assessing individual risk, preventing the infection, improving diagnostic methods, and enhancing treatment outcomes. The development and application of artificial intelligence (AI) technologies have introduced new, more efficient possibilities for the management of many diseases. In this article, we review the applications of AI in the prevention, diagnosis, and treatment of PJI, and explore how AI methodologies might achieve individualized risk prediction, improve diagnostic algorithms through biomarkers and pathology, and enhance the efficacy of antimicrobial and surgical treatments. We hope that through multimodal AI applications, intelligent management of PJI can be realized in the future.