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<p>Artificial intelligence (AI) is increasingly reshaping the landscape of orthopedic surgery, with notable applications in knee replacement surgery (KRS), particularly in robotic-assisted interventions. AI-driven tools are enhancing preoperative planning, intraoperative precision, and postoperative outcome prediction. Despite growing literature, no comprehensive bibliometric evaluation has mapped the evolution, collaborative structures, and thematic focus of AI in KRS—especially regarding robotic technologies. A bibliometric analysis was conducted using the Scopus database, including English-language original research articles published up to March 22, 2025. The search combined AI-related keywords with “knee replacement” and “knee arthroplasty.” Bibliometric tools—VOSviewer and Bibliometrix—were employed to explore publication trends, prolific authors, global collaboration, conceptual structures, and thematic evolution, with special attention to robotic applications. The final dataset comprised 4,216 articles, with an annual growth rate of 13.17%, peaking in 2024. The United States led in output, followed by Japan and the UK. Bradford’s Law revealed six core journals, including The Journal of Arthroplasty and Knee Surgery, Sports Traumatology, Arthroscopy. Lotka’s Law confirmed a highly dispersed authorship, with Mont MA as the most productive author. Robust collaborations were observed in North America and Europe, with increasing contributions from Asia. Conceptual mapping identified “total knee arthroplasty” and “machine learning” as core themes, while robotics, personalized surgical alignment, and predictive analytics emerged as dominant research frontiers. This study provides the first bibliometric map of AI integration in KRS, highlighting global contributions, conceptual trends, and the rising prominence of robotic-assisted technologies. These findings offer actionable insights for orthopedic surgeons, clinical researchers, and innovators aiming to harness AI and robotics to advance knee arthroplasty practices.</p>

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Mapping the integration of artificial intelligence in knee replacement surgery: a data-driven bibliometric analysis with emphasis on robotic innovation

  • 期刊论文

  • 发表日期：

    2026年1月20日

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  • Zenat A. Khired,
  • Manal Mohamed Elhassan Taha

摘要

Artificial intelligence (AI) is increasingly reshaping the landscape of orthopedic surgery, with notable applications in knee replacement surgery (KRS), particularly in robotic-assisted interventions. AI-driven tools are enhancing preoperative planning, intraoperative precision, and postoperative outcome prediction. Despite growing literature, no comprehensive bibliometric evaluation has mapped the evolution, collaborative structures, and thematic focus of AI in KRS—especially regarding robotic technologies. A bibliometric analysis was conducted using the Scopus database, including English-language original research articles published up to March 22, 2025. The search combined AI-related keywords with “knee replacement” and “knee arthroplasty.” Bibliometric tools—VOSviewer and Bibliometrix—were employed to explore publication trends, prolific authors, global collaboration, conceptual structures, and thematic evolution, with special attention to robotic applications. The final dataset comprised 4,216 articles, with an annual growth rate of 13.17%, peaking in 2024. The United States led in output, followed by Japan and the UK. Bradford’s Law revealed six core journals, including The Journal of Arthroplasty and Knee Surgery, Sports Traumatology, Arthroscopy. Lotka’s Law confirmed a highly dispersed authorship, with Mont MA as the most productive author. Robust collaborations were observed in North America and Europe, with increasing contributions from Asia. Conceptual mapping identified “total knee arthroplasty” and “machine learning” as core themes, while robotics, personalized surgical alignment, and predictive analytics emerged as dominant research frontiers. This study provides the first bibliometric map of AI integration in KRS, highlighting global contributions, conceptual trends, and the rising prominence of robotic-assisted technologies. These findings offer actionable insights for orthopedic surgeons, clinical researchers, and innovators aiming to harness AI and robotics to advance knee arthroplasty practices.