人工智能与扩展现实在血管外科医生培训中的应用述评

IF 4.4 Q1 Medicine
Joanna Halman, Sonia Tencer, Mariusz Siemiński
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引用次数: 0

摘要

背景:血管外科从开放到血管内技术的快速转变显著减少了受训者高风险的开放手术。基于模拟的培训,特别是结合虚拟现实(VR)和人工智能(AI)的培训,为弥合这一技能差距提供了一种有希望的方法。目的:本综述旨在评估目前关于扩展现实(XR)和人工智能在血管外科医生培训中的整合的证据,重点是技术技能发展、绩效评估和教育结果。方法:我们回顾了关于人工智能和x射线增强外科教育的文献,重点是经过验证的认知学习理论、模拟方法和特定手术培训。这篇综述涵盖了普通、神经外科、骨科和血管手术的研究,以及最近的系统综述和共识声明。结果:基于vr的培训加速了技能学习,减少了程序错误,提高了技术和非技术技能。人工智能平台提供实时反馈、性能基准和客观技能评估。在血管外科中,高保真模拟已被证明对颈动脉支架置入、EVAR、rAAA管理和外周干预的训练有效。针对患者的预演、触觉反馈和混合现实工具进一步提高了真实感和准备程度。然而,成本、数据安全、算法偏差和缺乏长期结果数据等挑战仍然存在。结论:XR和人工智能技术通过提供可扩展的、基于证据的替代传统培训方法,正在改变血管外科教育。未来的课程整合应侧重于道德使用,彻底验证,并与认知学习框架保持一致。结合VR、模拟、尸体实验室和监督实践的结构化方法可能是培训下一代血管外科医生最安全、最有效的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Artificial Intelligence and Extended Reality in the Training of Vascular Surgeons: A Narrative Review.

Artificial Intelligence and Extended Reality in the Training of Vascular Surgeons: A Narrative Review.

Background: The rapid shift from open to endovascular techniques in vascular surgery has significantly decreased trainee exposure to high-stakes open procedures. Simulation-based training, especially that incorporating virtual reality (VR) and artificial intelligence (AI), provides a promising way to bridge this skill gap.

Objective: This narrative review aims to assess the current evidence on the integration of extended reality (XR) and AI into vascular surgeon training, focusing on technical skill development, performance evaluation, and educational results.

Methods: We reviewed the literature on AI- and XR-enhanced surgical education across various specialties, focusing on validated cognitive learning theories, simulation methods, and procedure-specific training. This review covered studies on general, neurosurgical, orthopedic, and vascular procedures, along with recent systematic reviews and consensus statements.

Results: VR-based training speeds up skill learning, reduces procedural mistakes, and enhances both technical and non-technical skills. AI-powered platforms provide real-time feedback, performance benchmarking, and objective skill evaluations. In vascular surgery, high-fidelity simulations have proven effective for training in carotid artery stenting, EVAR, rAAA management, and peripheral interventions. Patient-specific rehearsal, haptic feedback, and mixed-reality tools further improve realism and readiness. However, challenges like cost, data security, algorithmic bias, and the absence of long-term outcome data remain.

Conclusions: XR and AI technologies are transforming vascular surgical education by providing scalable, evidence-based alternatives to traditional training methods. Future integration into curricula should focus on ethical use, thorough validation, and alignment with cognitive learning frameworks. A structured approach that combines VR, simulation, cadaver labs, and supervised practice may be the safest and most effective way to train the next generation of vascular surgeons.

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