Department of Urology and Kidney Transplant, GOM, Reggio Calabria, Italy.
Department of Urology, Catherine and Joseph Aresty Department of Urology, USC Institute of Urology, Keck School of Medicine, University of Southern California, Los Angeles, California, USA.
Curr Opin Urol. 2020 Nov;30(6):817-822. doi: 10.1097/MOU.0000000000000824.
PURPOSE OF REVIEW: Surgical training has dramatically changed over the last decade. It has become not only the way to prepare surgeons for their everyday work, but also a way to certify their skills thus increasing patient safety. This article reviews advances in the use of machine learning and artificial intelligence applied to virtual reality based surgical training over the last 5 years. RECENT FINDINGS: Eight articles have been published which met the inclusion criteria. This included six articles about the use of machine learning and artificial intelligence for assessment purposes and two articles about the possibility of teaching applications, including one review and one original research article. All the research articles pointed out the importance of machine learning and artificial intelligence for the stratification of trainees, based on their performance on basic tasks or procedures simulated in a virtual reality environment. SUMMARY: Machine learning and artificial intelligence are designed to analyse data and use them to take decisions that typically require human intelligence. Evidence in literature is still scarce about this technology applied to virtual reality and existing manuscripts are mainly focused on its potential to stratify surgical performance and provide synthetic feedbacks about it. In consideration of the exponential growth of computer calculation capabilities, it is possible to expect a parallel increase of research about this topic within the next few years.
目的综述:在过去的十年中,外科手术培训发生了巨大的变化。它不仅是为外科医生日常工作做准备的一种方式,也是一种认证他们技能的方式,从而提高了患者的安全性。本文综述了过去 5 年来应用机器学习和人工智能于虚拟现实基础外科培训的进展。
最近发现:有 8 篇文章符合纳入标准。其中 6 篇文章讨论了机器学习和人工智能在评估方面的应用,另外 2 篇文章讨论了教学应用的可能性,包括一篇综述和一篇原始研究文章。所有的研究文章都指出了机器学习和人工智能在外科技能分层中的重要性,其依据是学员在虚拟现实环境中模拟的基本任务或操作中的表现。
总结:机器学习和人工智能旨在分析数据并利用这些数据做出通常需要人类智能才能做出的决策。文献中的证据仍然很少涉及这项技术在虚拟现实中的应用,现有的论文主要集中在其分层外科手术表现和提供综合反馈的潜力上。考虑到计算机计算能力的指数级增长,在未来几年内,我们有可能会看到关于这一主题的研究数量呈指数级增长。
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