Temporal variability of surgical technical skill perception in real robotic surgery
Temporal variability of surgical technical skill perception in real robotic surgery
复制标题
真实机器人手术中手术技术技能感知的时间变化
DOI：
10.1007/s11548-020-02253-5
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发表时间：
2020
影响因子：
3
通讯作者：
Kowalewski, Timothy M.
中科院分区：
文献类型：
--
作者：
Kelly, Jason D.;Nash, Michael;Heller, Nicholas;Lendvay, Thomas S.;Kowalewski, Timothy M.
目的总结评分指标，无论是从人群的非专家，教师外科医生或从自动化的性能指标，已被信任的报告外科医生的技术技能的流行方法。本文的目的是了解是否存在显着的波动，在整个手术footage.MethodsA组的机器人手术的情况下，从常见的人类患者的机器人手术的技术技能评估的外科医生在长时间的手术视频，这原本是12-15分钟的长度，在每个单独的分钟被用来评估感知的技术技能。每个视频的线性混合效应模型被用来比较每一分钟的评级，以了解是否可以检测到随着时间的推移，除了跨和intrarater variation.ResultsModeling的变化随着时间的推移，机器人技能分数的全球评价评估显着贡献的预测模型为11的12名外科医生的分数变化和可靠的测量。这表明，随着时间的推移，在技术技能发生可衡量的变化，在机器人surgery.ConclusionThe研究结果从这项研究提出了问题的最佳持续时间的镜头需要进行评估，以达到一个准确的评级手术技术技能较长的程序。这可能意味着监督机器学习方法的标签噪声不可忽略。将来，除了平均得分外，可能还需要报告外科医生的技能变异性，以正确了解外科医生的整体技能水平。
PurposeSummary score metrics, either from crowds of non-experts, faculty surgeons or from automated performance metrics, have been trusted as the prevailing method of reporting surgeon technical skill. The aim of this paper is to learn whether there exist significant fluctuations in the technical skill assessments of a surgeon throughout long durations of surgical footage.MethodsA set of 12 videos of robotic surgery cases from common human patient robotic surgeries were used to evaluate the perceived technical skill at each individual minute of the surgical videos, which were originally 12–15 min in length. A linear mixed-effects model for each video was used to compare the ratings of each minute to those from every other minute in order to learn whether a change in scores over time can be detected and reliably measured apart from inter- and intrarater variation.ResultsModeling the change over time of the global evaluative assessment of robotic skills scores significantly contributed to the prediction models for 11 of the 12 surgeons. This demonstrates that measurable changes in technical skill occur over time during robotic surgery.ConclusionThe findings from this research raise questions about the optimal duration of footage needed to be evaluated to arrive at an accurate rating of surgical technical skill for longer procedures. This may imply non-negligible label noise for supervised machine learning approaches. In the future, it may be necessary to report a surgeon’s skill variability in addition to their mean score to have proper knowledge of a surgeon’s overall skill level.
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DOI：
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发表时间：
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期刊：
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影响因子：
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DOI：
--
发表时间：
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期刊：
The Journal of craniofacial surgery (Print)
影响因子：
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