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人工智能在泌尿外科领域如何提高外科技能:现状与未来展望。

How the use of the artificial intelligence could improve surgical skills in urology: state of the art and future perspectives.

机构信息

USC Institute of Urology and Catherine & Joseph Aresty Department of Urology, Keck School of Medicine.

AI Center at USC Urology, USC Institute of Urology.

出版信息

Curr Opin Urol. 2021 Jul 1;31(4):378-384. doi: 10.1097/MOU.0000000000000890.

DOI:10.1097/MOU.0000000000000890
PMID:33965984
Abstract

PURPOSE OF REVIEW

As technology advances, surgical training has evolved in parallel over the previous decade. Training is commonly seen as a way to prepare surgeons for their day-to-day work; however, more importantly, it allows for certification of skills to ensure maximum patient safety. This article reviews advances in the use of machine learning and artificial intelligence for improvements of surgical skills in urology.

RECENT FINDINGS

Six studies have been published, which met the inclusion criteria. All articles assessed the application of artificial intelligence in improving surgical training. Different approaches were taken, such as using machine learning to identify and classify suturing gestures, creating automated objective evaluation reports, and determining surgical technical skill levels to predict clinical outcomes. The articles illustrated the continuously growing role of artificial intelligence to address the difficulties currently present in evaluating urological surgical skills.

SUMMARY

Artificial intelligence allows us to efficiently analyze the surmounting data related to surgical training and use it to come to conclusions that normally would require human intelligence. Although these metrics have been shown to predict surgeon expertise and surgical outcomes, evidence is still scarce regarding their ability to directly improve patient outcomes. Considering this, current active research is growing on the topic of deep learning-based computer vision to provide automated metrics needed for real-time surgeon feedback.

摘要

目的综述

随着技术的进步,过去十年外科培训也在不断发展。培训通常被视为外科医生日常工作的准备方式;但更重要的是,它允许对技能进行认证,以确保患者的最大安全。本文综述了机器学习和人工智能在泌尿外科手术技能改进中的应用进展。

最近的发现

发表了六篇符合纳入标准的研究。所有文章都评估了人工智能在改善外科培训中的应用。采取了不同的方法,例如使用机器学习来识别和分类缝合动作、创建自动客观评估报告,以及确定手术技术水平以预测临床结果。这些文章说明了人工智能在解决目前评估泌尿外科手术技能所面临的困难方面的作用不断增强。

总结

人工智能使我们能够有效地分析与外科培训相关的大量数据,并利用这些数据得出通常需要人类智能才能得出的结论。尽管这些指标已经被证明可以预测外科医生的专业知识和手术结果,但关于它们直接改善患者结果的能力的证据仍然很少。有鉴于此,目前正在深入研究基于深度学习的计算机视觉,以提供实时外科医生反馈所需的自动指标。