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<p>This study aims to employ bibliometric analysis methods to systematically review the current research progress, developmental trajectory, and emerging research hotspots in artificial intelligence-integrated robot-assisted spine surgery (AI-RASS), thereby providing visualized support for future research planning. A total of 588 publications related to AI-RASS were extracted from the Web of Science Core Collection (WoSCC) database between 2005 and 2025.The study employed tools such as Bibliometrix, CiteSpace, VOSviewer, and Scimago Graphica to analyze publication trends, international collaboration networks, and research hotspots, generating visualized maps that elucidate the knowledge framework and conceptual structure of this field. The annual average growth rate of publication volume is 24.22%, reaching its peak in 2025. The USA, China, and Germany have the highest number of published papers, with high H-indexes, strong collaboration intensity, and significant impact. Switzerland has the highest average citation frequency per paper. In terms of total co-citation frequency, Spine ranks highest among journals in this field. Although scholarly interest continues to grow, notable gaps remain in areas such as high-quality prospective multicenter randomized controlled trials, international collaboration, ethical oversight, and rigorous cost-effectiveness evaluations. It is essential to establish comprehensive databases and international big data sharing platforms, advance methodologically rigorous clinical trial research, develop corresponding ethical frameworks, and create innovative yet accessible AI-integrated surgical protocols to promote deep integration of AI and RASS. The AI-RASS research has garnered significant attention over the past two decades. This study employed bibliometric and visualization analysis methods to systematically examine the evolutionary trends in AI-RASS research. Future developments in this field should prioritize the following directions: strengthening interdisciplinary collaboration, establishing a systematic clinical evaluation framework, creating comprehensive clinical research databases, and developing evidence-based ethical guidelines; simultaneously enhancing international and institutional cooperation to ensure alignment between technological advancement and patient safety.</p>

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Global research trends in artificial intelligence-integrated robot-assisted spine surgery: a bibliometric and visualized analysis

  • 期刊论文

  • 发表日期：

    2026年7月27日

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  • Yin He,
  • Xu Liu,
  • Dawei Ren,
  • Zhilin Li

摘要

This study aims to employ bibliometric analysis methods to systematically review the current research progress, developmental trajectory, and emerging research hotspots in artificial intelligence-integrated robot-assisted spine surgery (AI-RASS), thereby providing visualized support for future research planning. A total of 588 publications related to AI-RASS were extracted from the Web of Science Core Collection (WoSCC) database between 2005 and 2025.The study employed tools such as Bibliometrix, CiteSpace, VOSviewer, and Scimago Graphica to analyze publication trends, international collaboration networks, and research hotspots, generating visualized maps that elucidate the knowledge framework and conceptual structure of this field. The annual average growth rate of publication volume is 24.22%, reaching its peak in 2025. The USA, China, and Germany have the highest number of published papers, with high H-indexes, strong collaboration intensity, and significant impact. Switzerland has the highest average citation frequency per paper. In terms of total co-citation frequency, Spine ranks highest among journals in this field. Although scholarly interest continues to grow, notable gaps remain in areas such as high-quality prospective multicenter randomized controlled trials, international collaboration, ethical oversight, and rigorous cost-effectiveness evaluations. It is essential to establish comprehensive databases and international big data sharing platforms, advance methodologically rigorous clinical trial research, develop corresponding ethical frameworks, and create innovative yet accessible AI-integrated surgical protocols to promote deep integration of AI and RASS. The AI-RASS research has garnered significant attention over the past two decades. This study employed bibliometric and visualization analysis methods to systematically examine the evolutionary trends in AI-RASS research. Future developments in this field should prioritize the following directions: strengthening interdisciplinary collaboration, establishing a systematic clinical evaluation framework, creating comprehensive clinical research databases, and developing evidence-based ethical guidelines; simultaneously enhancing international and institutional cooperation to ensure alignment between technological advancement and patient safety.