Artificial intelligence‐based approaches to augmenting and automating surgical training
Artificial intelligence is a promising tool for augmenting surgical training and improving the objectivity and scalability of surgical skill assessment and feedback. To date, AI models are adept at detecting relatively large differences in surgical performance and providing rudimentary feedback. Further work is required to create models capable of doing more fine-tuned skill assessments and generating more detailed, constructive feedback.
Authors
- Ludovica Cella
- Jasmine Lin (ORCID: https://orcid.org/0000-0002-2198-1296)
- Mitchell G. Goldenberg (ORCID: https://orcid.org/0000-0002-4601-5721)
- Andrew J. Hung
Institutions
- University of Southern California (US)
- Cedars-Sinai Medical Center (US)
- Humanitas University (IT)
- IRCCS Humanitas Research Hospital (IT)
Publication Details
- Journal
- British Journal of Urology
- Published
- 2026-03-12
- DOI
- https://doi.org/10.1111/bju.70229
- Primary Topic
- Surgical Simulation and Training
- Type
- article
- Field-Weighted Citation Impact
- 0.00