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• Use of artificial intelligence in surgical research has continued to significantly rise. • Current trends include greater use of advanced deep learning and generative models. • Marked growth in surgical oncology suggest priorities in advancing cancer research. The methods of artificial intelligence (AI) used in academic surgical research has not been previously evaluated. We aimed to systematically assess AI techniques used in surgery research. Cross-sectional analysis of peer-reviewed abstracts presented at annual scientific meetings from 2020 to 2024. Abstracts were reviewed for AI utilization and categorized by methodology. Of 6,113 abstracts included, 110 (1.8%) involved AI. AI-based studies quadrupled over the five-year period (p<0.001). 43% (47/107) utilized simpler machine learning techniques, which decreased from 62% in 2020 to 33% in 2024. Meanwhile, complex deep learning/neural network frameworks (8% to 15%), generative AI (0% to 21%) and robotic integration (0 to 10%) increased. Surgical oncologic specialties have grown in AI-derived studies (8% to 25%). AI-related research in surgery has flourished and comprises almost 5% of presented studies. AI use mirrors historical paradigm shifts towards more complex techniques and have surged in advancing cancer research.
Bauzon et al. (2026) studied this question.