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This article reviews how artificial intelligence supports AI-enabled prevention, diagnosis, and treatment strategies, including individualized risk prediction, multimodal diagnostic algorithms using biomarkers and pathology, and improved management of antimicrobial and surgical treatment 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describe AI’s role in diagnosing and treating PJI?",{"text":72,"@type":64},"It summarizes AI-based diagnostic approaches across biomarkers, pathology, imaging, and microbiology, and discusses how AI can support antimicrobial resistance prediction and improve antimicrobial and surgical treatment outcomes.","https://schema.org",{"og:url":32,"og:type":75,"og:title":10,"og:site_name":45,"og:description":12},"article",{"robots":77,"canonical":32},"index,follow",{"doc_id":79,"site_id":7},434348,1790713886,{"code":4,"msg":82,"data":83},"success",[84,88,92,96,101,106,110,115,120,123,126],{"id":22,"doc_module":4,"doc_module_name":25,"category_name":85,"show_sort_weight":86,"slug":87},"Story & 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Advanced Research  \njournal [homepage: www. elsevier. com/locate/jare](homepage: www. elsevier. com/locate/jare)  \nThe Application of artificial intelligence in periprosthetic joint infection Pengcheng Li a, 1, Yan Wang a, 1, Runkai Zhao a, 1, Lin Hao a, 1, Wei Chai a, Chen Jiying a,  \nZeyu Feng a, Quanbo Ji a,b,c,⁎, Guoqiang Zhang a,⁎  \na Department of Orthopaedics, General Hospital of Chinese People’s Liberation Army, Beijing 100853, China b Beijing National Research Center for Information Science and Technology (BNRist), Beijing, China c Department of Automation, Tsinghua University, Beijing, China  \n\n| h i g h l i g h t s\u003Cbr>• For the first time, we systematically and comprehensively elaborated on the relevant progress of AI technology in the prevention, diagnosis, and treatment of PJI.\u003Cbr>• 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.\u003Cbr>• This paper summarized and expounds the current challenges and future development directions of AI in PJI field. |  | g r a p h i c a l a b s t r a c t\u003Cbr>|  |\n| --- | --- | --- | --- |\n| a r t i c l e i n f o |  |  | a b s t r a c t |\n| Article history:\u003Cbr>Received 6 January 2025\u003Cbr>Revised 6 March 2025\u003Cbr>Accepted 20 March 2025\u003Cbr>Available online 28 March 2025 |  |  | 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.\u003Cbr>© 2025 The Author(s). Published by Elsevier B.V. on behalf of Cairo University. This is an open access article under the CC BY-NC-ND license ([http://creativecommons.org/licenses/by-nc-nd/4.0/](http://creativecommons.org/licenses/by-nc-nd/4.0/)). |\n| Keywords:\u003Cbr>Periprosthetic joint infection\u003Cbr>Artificial intelligence\u003Cbr>Joint\u003Cbr>Arthroplasty |  |  |  |\n\n⁎ Corresponding authors.  \nE-mail addresses: [quanbo301@163.com](quanbo301@163.com) (Q. Ji), [gqzhang301orth@163.com](gqzhang301orth@163.com) (G. Zhang).  \n1 These authors contributed equally to this work.  \n[https://doi.org/10.1016/j.jare.2025.03.039](https://doi.org/10.1016/j.jare.2025.03.039)  \n2090-1232/© 2025 The Author(s). Published by Elsevier B.V. on behalf of Cairo University.  \nThis is an open access article under the CC BY-NC-ND license ([http://creativecommons.org/licenses/by-nc-nd/4.0/](http://creativecommons.org/licenses/by-nc-nd/4.0/)).  \nP. Li, Y. Wang, R. Zhao et al. Journal of Advanced Research 79 (2026) 633–659 Contents  \nIntroduction ........................................................................................................... 634  \nSearch strategy ........................................................................................................ 636  \nApplication in PJI prevention .......","cbCaifkZifbgrdEV","https://ap.wps.com/l/cbCaifkZifbgrdEV","pdf",3805248,27,"English","# Introduction\n# Search strategy\n# Application in PJI prevention\n## PJI risk prediction\n## Primary PJI\n## PJI recurrence\n## PJI patient education\n## PJI screening\n# PJI diagnosis\n## Biomarker-based diagnosis\n## Pathology-based diagnosis\n## Imaging-based diagnosis\n## Microbiology-based diagnosis\n# Application in PJI treatment\n## Predicting antibiotic resistance\n## Based on susceptibility testing\n## Based on nucleic acids\n## Based on phenotypes","[{\"question\":\"Why is periprosthetic joint infection (PJI) clinically important?\",\"answer\":\"PJI is a devastating complication after total joint arthroplasty that can require additional surgeries and antimicrobial therapy and may lead to disability, increasing strain on patients and healthcare systems.\"},{\"question\":\"What does the article cover regarding AI in PJI prevention?\",\"answer\":\"It reviews AI applications for risk prediction and related prevention topics, including primary PJI, recurrence, patient education, and screening.\"},{\"question\":\"How does the article describe AI’s role in diagnosing and treating PJI?\",\"answer\":\"It summarizes AI-based diagnostic approaches across biomarkers, pathology, imaging, and microbiology, and discusses how AI can support antimicrobial resistance prediction and improve antimicrobial and surgical treatment outcomes.\"}]","The Application of Artificial Intelligence in Periprosthetic Joint Infection | PDF",1790668704,68]