Transforming Surgical Training With AI Techniques for Training, Assessment, and Evaluation: Scoping Review
importance 4/10
ai assisted
Surgical Simulation and Training surgical training stage: research
Problem
Surgical training assessment and evaluation rely on traditional methods that may be improved by data-driven AI techniques.
Why it matters
Quality of surgical skill assessment directly affects trainee competence and patient safety.
What the AI did
A PRISMA-ScR scoping review of studies (2020–2024) examining how AI algorithms, predictive analytics and data-driven insights enhance surgical trainees' learning paths and performance evaluation.
Results
not stated in source
Impact
Review identifies current AI applications and research gaps; no measured outcome stated.
Record
| Venue | Journal of Medical Internet Research |
|---|---|
| Published | 2025 |
| Work type | article |
| Authors | David Escobar-Castillejos, Ari Yair Barrera-Animas, Julieta Noguez, Alejandra J. Magana, Bedřich Beneš |
| Citations | 22 (OpenAlex, at import time) |
| References | 96 |
| Model or method | not stated in source |
| Organization | not stated in source |
| Primary source | https://doi.org/10.2196/58966 |
| Open access | gold |
| Keywords | surgical training, AI assessment, scoping review, predictive analytics, medical education |
Importance rating
4
real but narrower advance
Surgical skill assessment affects trainee competence and patient safety, but abstract gives no scale or outcomes; a scoping review of 56 studies mapping applications and gaps.