Beyond the Hype: Mapping the Evolution of Artificial Intelligence in General Surgery Through Two Decades of...

Artificial intelligence (AI) has transformed many facets of general surgery. A quantitative bibliometric overview can map publication trends, research fronts, and collaborative patterns to guide future work. Our study provides a comprehensive analysis of the literature on AI in general surgery, identifying key trends and influential contributors.

We retrieved 536 "Article" and "Review" records from Scopus and Web of Science from January 2005 through June 2025. After a rigorous deduplication process, 536 unique publications remained. We analyzed annual scientific production, top journals, authors, keyword co-occurrence, and highly cited papers using descriptive and relational bibliometric analyses.

Annual publications grew exponentially, accelerating significantly after 2019 and peaking at 160 publications in 2024. Annals of Surgery (n = 28), Surgical Endoscopy (n = 25), and Journal of Medical Internet Research (n = 20) were the most productive journals. Palenzuela DL (n = 7), Dayan D (n = 6), and Liu J (n = 6) were the most prolific authors. The most frequent keywords were "Artificial intelligence" (64), "General surgery" (43), and "Surgery" (31). Keyword co-occurrence analysis revealed five thematic clusters: AI language models, clinical outcomes/risk prediction, surgical education, socio-professional themes, and core surgical practice. The most cited articles focused on surgical phase recognition, medical education, and large-language models.

AI in general surgery has seen a period of exponential growth, moving from exploratory discourse to applied research. While research is concentrated among a few authors and journals, its thematic diversity suggests a nascent, fragmented field without a dominant intellectual core. Future work should prioritize prospective validation, data-sharing infrastructures, and ethical frameworks to ensure responsible clinical translation. We propose an ethical-educational-technological (EET) framework to guide the responsible integration of AI into surgical practice and training.