VR and machine learning: novel pathways in surgical hands-on training.

Area of Science:

• Medical Education Technology
• Artificial Intelligence in Surgery
• Virtual Reality Simulation

Background:

• Surgical training has evolved significantly, emphasizing skill certification and patient safety.
• Virtual reality (VR) offers immersive platforms for surgical practice and assessment.

Purpose of the Study:

• To review advances in machine learning (ML) and artificial intelligence (AI) applied to VR surgical training over the past five years.
• To explore the current applications and future potential of ML/AI in surgical education.

Main Methods:

• Systematic review of literature published within the last five years.
• Inclusion criteria focused on ML/AI in VR surgical training, specifically for assessment and teaching.

Main Results:

• Six articles focused on ML/AI for performance assessment in VR surgical simulations.
• Two articles explored teaching applications, including one review and one original research.
• Studies highlight ML/AI's role in stratifying trainees based on VR performance.

Conclusions:

• ML and AI show significant potential for analyzing surgical trainee data in VR environments.
• Current literature primarily focuses on performance stratification and feedback generation.
• Continued research is expected due to advancements in computational power and AI capabilities.