Artificial intelligence and machine learning in robotic, teleoperated, and remote surgery: a bibliometric and knowledge mapping analysis (2015-2025).

Artificial intelligence (AI) and machine learning (ML) technologies are rapidly transforming telesurgery by enhancing robotic-assisted surgical systems, remote surgical communication, image-guided interventions, and intelligent decision-making. The integration of AI-driven algorithms with telesurgical platforms has accelerated research activity across medicine, robotics, engineering, and computer science. However, the global research landscape, collaborative structure, and emerging thematic trends of AI- and ML-enabled telesurgery remain insufficiently explored. Therefore, the present study aimed to perform a comprehensive bibliometric and knowledge mapping analysis of global research on AI and ML applications in robotic, teleoperated, and remote surgery published between 2015 and 2025. A bibliometric analysis was conducted using the Scopus database on 28 May 2026. Articles published between 2015 and 2025 related to AI, machine learning, robotic surgery, teleoperation, and telesurgery were retrieved using predefined search terms. Only English-language research articles were included. Bibliometric indicators including annual publication trends, citation analysis, leading journals, productive authors, institutions, funding agencies, country collaborations, co-citation analysis, and keyword co-occurrence analysis were evaluated. Visualization and network mapping were performed using VOSviewer software (version 1.6.20). A total of 2,201 publications were identified from 112 countries. Scientific output demonstrated substantial exponential growth, increasing from 85 publications in 2015 to 1,167 publications in 2025. Medicine (29%), computer science (24%), and engineering (20%) represented the dominant research areas. Journal of Robotic Surgery emerged as the leading publication source, while China and the United States were identified as the most influential contributing countries. Keyword co-occurrence analysis highlighted major research themes including robotic surgery, deep learning, machine learning, intelligent robotics, teleoperation, and minimally invasive surgery. Overlay visualization demonstrated a recent shift toward AI-driven autonomous systems, computer vision, surgical workflow analysis, and intelligent robotic platforms. Co-citation analysis further revealed strong interdisciplinary foundations involving surgical sciences, robotics, computer vision, and advanced deep learning methodologies. Research on AI and ML applications in robotic, teleoperated, and remote surgery has grown rapidly over the last decade and is increasingly characterized by strong interdisciplinary collaboration and technological innovation. Emerging trends suggest a transition from conventional robotic-assisted surgery toward intelligent, data-driven, and semi-autonomous telesurgical systems. The findings of this bibliometric study provide valuable insights into the evolving scientific landscape of intelligent telesurgery and may support future research, clinical translation, technological development, and policy planning in robotic-assisted remote surgical care.