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Transforming Surgical Training With AI Techniques for Training, Assessment, and Evaluation: Scoping Review
(JMIR Publications Inc., 2025)
Escobar Castillejos, David
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Barrera Ánimas, Ari Yair
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Noguez, Julieta
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Magana, Alejandra J.
;
Benes, Bedrich
Background: Artificial intelligence (AI) has introduced novel opportunities for assessment and evaluation in surgical training, offering potential improvements that could surpass traditional educational methods. Objective: This scoping review examines the integration of AI in surgical training, assessment, and evaluation, aiming to determine how AI technologies can enhance trainees’ learning paths and performance by incorporating data-driven insights and predictive analytics. In addition, this review examines the current state and applications of AI algorithms in this field, identifying potential areas for future research. Methods: Following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines, the PubMed, Scopus, and Web of Science were searched for studies published between January 2020 and March 18, 2024. Eligibility criteria included English-language full-text articles that investigated the application of AI in surgical training, assessment, or evaluation; non-English texts, reviews, preprints, and studies not addressing AI in surgical education were excluded. After duplicate removal and screening, 56 studies were included in the analysis. Data were structured by categorizing studies according to surgical procedure, AI technique, and training setup. Results were synthesized narratively and summarized in frequency tables. Results: From 1400 initial records, 56 studies met the inclusion criteria. Most were journal articles (84%, 47/56), with the remainder being conference papers (16%, 9/56). AI was most frequently applied in minimally invasive surgery (27%, 15/56), neurosurgery (20%, 11/56), and laparoscopy (16%, 9/56). Common techniques included machine learning (20%, 11/56), clustering (14%, 8/56), deep learning (11%, 6/56), convolutional neural networks (11%, 6/56), and support vector machines (11%, 6/56). Training setups were dominated by simulation platforms (33%, 19/56) and box trainers (24%, 13/56), followed by surgical video analysis (16%, 9/56), and robotic systems such as the da Vinci platform (13%, 7/56). Across studies, AI-enhanced training environments provided automated skill assessment, personalized feedback, and adaptive learning trajectories, with several reporting improvements in trainees’ learning curves and technical proficiency. However, heterogeneity in study design and outcome measures limited comparability, and algorithmic transparency was often lacking. Conclusions: The application of AI in surgical training demonstrates the potential to enhance skill acquisition and support more efficient, personalized, and adaptive learning pathways. Despite encouraging findings, several limitations exist, including small sample sizes, the lack of standardized evaluation metrics, and insufficient external validation of AI models. Future studies should aim to clarify AI methodologies, improve reproducibility, and develop scalable, simulation-based solutions aligned with global education goals. ©The authors ©JMIR Publications Inc.
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Virtual reality and minimal analgesia attenuate pain during spine surgery
(2019)
Mosso Vázquez, José Luis
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Canseco Aguilar, Patricia
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Mosso Lara, Dejanira
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Miller, Ian
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Wiederhold, Brenda
We present progress with 17 cases of virtual reality (VR) therapy to reduce pain and anxiety during interventional treatment under radiology guidance on patients diagnosed with intense and chronic back pain with narrow channel syndrome and lumbar disc hernias. Methodology. Patients under informed consent fitted with a head mounted display (HMD), to allow them to navigate in VR scenarios, lie in a prone position. The procedure begins using minimal analgesia with an intravenous single dose with fentanyl 50 mcg without sedation. We infiltrate locally with local anesthesia (lidocaine 1%); depending on the interventional procedure involved. The interventional procedures were: discography with discolysis with ozone, caudal blockages, and foramina blocks. During the procedure, patients navigate VR scenarios created at the Virtual Reality Medical Center in San Diego (Dr. Brenda Wiederhold). At the end of the procedure, patients recover for one to two hours before leaving the Surgical Center. Results. No statistically significant increase in pain ratings from baseline through procedure were noted, however, a significant decrease was noted post-operatively. The attenuation of pain due to VR distraction in 17 patients allowed the procedure to be non-sedative (Midazolam was not used). Conclusions. Advantages of VR therapy include a high degree of patient satisfaction, minimal risk without sedatives, such as midazolam, maintenance of patient's conscious awareness, stress reduction in the patient, stress reduction in the anesthesiologist, and cooperation with the patient. The noninvasive VR equipment used is portable, reliable, and led to a a better patient–physician relationship. VR therapy during pain treatment is an excellent option in the pain clinic. Chronic pain treated with anti-inflammatories administered directly to the spine and local ozone is an area in which the use of VR can significantly reduce pain. With this experience we demonstrate the cost benefit advantage that also offers satisfaction to patients while offering savings to health institutions. No complications were presented.
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