Artificial Intelligence in Surgical Training: A Comprehensive Update on Simulation, Assessment, and Emerging...

Area of Science:

• Surgical Education
• Medical Simulation
• Artificial Intelligence in Medicine

Background:

• Artificial intelligence (AI) is increasingly influencing various aspects of medical education.
• Surgical training traditionally relies on apprenticeship models, facing challenges in standardization and accessibility.

Purpose of the Study:

• To summarize recent advancements in AI for surgical education, covering simulation, assessment, and recruitment.
• To explore the challenges and governance issues associated with implementing AI in surgical training.
• To consider future trends and emerging AI technologies impacting surgical education.

Main Methods:

• Review of recent developments in AI-driven surgical simulation platforms.
• Analysis of AI applications in surgical skills assessment and trainee recruitment.
• Examination of literature on barriers to AI implementation in medical education.
• Discussion of emerging technologies like digital twins and generative AI in the context of surgical training.

Main Results:

• AI is enhancing surgical simulation fidelity and providing objective assessment metrics.
• AI tools are being explored for more efficient and equitable surgical trainee recruitment.
• Significant barriers to AI implementation include data privacy, ethical concerns, and the need for robust governance frameworks.
• Emerging technologies promise more personalized and adaptive surgical training experiences.

Conclusions:

• Artificial intelligence offers transformative potential for surgical education, improving training efficiency and outcomes.
• Addressing implementation barriers and establishing clear governance are crucial for successful AI integration.
• Future surgical training will likely incorporate advanced AI tools, including digital twins and generative AI, for enhanced learning and decision support.