# Bibliometric mapping of artificial intelligence research in surgical education (1997–2025)

## TL;DR

This paper maps the growth and trends of AI research in surgical education from 1997 to 2025, highlighting key themes and geographic disparities.

## Contribution

The study provides a comprehensive bibliometric analysis of AI in surgical education, identifying emerging and mature research themes.

## Key findings

- AI research in surgical education has grown at an annual rate of 18.39%.
- Human-robot interaction and AI-based simulation training are the most influential research topics.
- International collaboration in this field is limited, with 25.17% of publications involving multiple countries.

## Abstract

Artificial intelligence (AI) is rapidly transforming surgical education, yet comprehensive analysis of research trends in this field remains limited.

We analyzed publications from the Web of Science Core Collection using “surgery” AND “education” AND “artificial intelligence” as search terms (1997–2025). Bibliometric indicators were analyzed using the bibliometrix package in R.

We identified 572 publications by 3,228 authors across 332 journals, with an 18.39% annual growth rate. The United States and United Kingdom led research output, with Harvard University as the top contributing institution. “Augmented reality”, “video”, and “performance” emerged as mature research themes (motor themes), while large language models represent recent emerging topics. International collaboration accounted for 25.17% of publications, predominantly among developed nations. Citation analysis revealed human-robot interaction and AI-based simulation training as the most influential research topics.

AI research in surgical education shows rapid growth but significant geographic disparities exist. Future efforts should focus on developing personalized learning systems and addressing the global digital divide in AI-enhanced surgical education.