Related Experiment Video
Updated: Jul 10, 2026
Automatic Surgery in Transcatheter Aortic Valve Replacement Using Augmented Reality
Published on: August 9, 2024
Artificial intelligence applications in surgical education and training: a systematic review
Talia Tene1, Paulina Elizabeth Valverde Aguirre2, Ángel Floresmilo Parreño Urquizo3
1Department of Chemistry, Universidad Técnica Particular de Loja, Loja, Ecuador.
Introduction:
Surgical training is shifting toward scalable, data-driven education as operative complexity and patient safety expectations increase. AI can support objective feedback and cognitive guidance.
Methodology:
We conducted a PRISMA-guided systematic review using a PICO framework and searched PubMed, Scopus, and IEEE Xplore for peer-reviewed studies published between 2020 and 2025.
Results:
Of 1,109 records, 21 studies met the inclusion criteria. Included studies covered simulation-based, robotic, laparoscopic, and computer-assisted training using deep learning/computer vision, tutoring or predictive models, and language-based tools. Performance outcomes predominated (81.0%) over engagement-related outcomes (19.0%), and reported effects were mainly positive (76.2%) or increased (23.8%).
Discussion:
Evidence suggests near-term, task-specific gains when AI provides objective measurement and feedback, but comparability is limited by heterogeneous endpoints, small samples, and single-center designs.
Conclusion:
AI-enabled surgical education shows promise for objective assessment and adaptive instruction, but multicenter longitudinal studies with standardized metrics are still needed.