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本文引用的文献

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Letter: Deep Neural Networks Can Accurately Detect Blood Loss and Hemorrhage Control Task Success from Video.
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2
A vision transformer for decoding surgeon activity from surgical videos.一种从手术视频中解码外科医生活动的视觉转换器。
Nat Biomed Eng. 2023 Jun;7(6):780-796. doi: 10.1038/s41551-023-01010-8. Epub 2023 Mar 30.
3
Human visual explanations mitigate bias in AI-based assessment of surgeon skills.人类视觉解释可减轻基于人工智能的外科医生技能评估中的偏差。
NPJ Digit Med. 2023 Mar 30;6(1):54. doi: 10.1038/s41746-023-00766-2.
4
A multi-institutional study using artificial intelligence to provide reliable and fair feedback to surgeons.一项使用人工智能为外科医生提供可靠且公平反馈的多机构研究。
Commun Med (Lond). 2023 Mar 30;3(1):42. doi: 10.1038/s43856-023-00263-3.
5
Validation of Machine Learning-Based Automated Surgical Instrument Annotation Using Publicly Available Intraoperative Video.基于机器学习的自动手术器械标注的验证：使用公开的术中视频。
Oper Neurosurg (Hagerstown). 2022 Sep 1;23(3):235-240. doi: 10.1227/ons.0000000000000274. Epub 2022 May 26.
6
Deep Neural Networks Can Accurately Detect Blood Loss and Hemorrhage Control Task Success From Video.深度神经网络可以从视频中准确检测失血情况和出血控制任务的完成情况。
Neurosurgery. 2022 Jun 1;90(6):823-829. doi: 10.1227/neu.0000000000001906. Epub 2022 Mar 25.
7
Utility of the Simulated Outcomes Following Carotid Artery Laceration Video Data Set for Machine Learning Applications.模拟颈动脉切开术后结果视频数据集在机器学习应用中的效用。
JAMA Netw Open. 2022 Mar 1;5(3):e223177. doi: 10.1001/jamanetworkopen.2022.3177.
8
A recurrent machine learning model predicts intracranial hypertension in neurointensive care patients.一种反复出现的机器学习模型可预测神经重症监护病房患者的颅内压升高。
Brain. 2022 Aug 27;145(8):2910-2919. doi: 10.1093/brain/awab453.
9
Prediction of Life-Threatening Intracranial Hypertension During the Acute Phase of Traumatic Brain Injury Using Machine Learning.基于机器学习预测创伤性脑损伤急性期危及生命的颅内高压。
IEEE J Biomed Health Inform. 2021 Oct;25(10):3967-3976. doi: 10.1109/JBHI.2021.3085881. Epub 2021 Oct 5.
10
Automated operative phase identification in peroral endoscopic myotomy.经口内镜下肌切开术的自动手术阶段识别。
Surg Endosc. 2021 Jul;35(7):4008-4015. doi: 10.1007/s00464-020-07833-9. Epub 2020 Jul 27.

In Reply: Deep Neural Networks Can Accurately Detect Blood Loss and Hemorrhage Control Task Success from Video.

作者信息

Kugener Guillaume, Pangal Dhiraj J, Donoho Daniel A

机构信息

Department of Neurosurgery, Keck School of Medicine of the University of California, Los Angeles , California , USA.

Division of Neurosurgery, Center for Neuroscience, Children's National Hospital, Washington , District of Columbia , USA.

出版信息

Neurosurgery. 2023 Sep 1;93(3):e81-e82. doi: 10.1227/neu.0000000000002591. Epub 2023 Jun 30.

DOI:10.1227/neu.0000000000002591
PMID:37387579
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12245218/
Abstract
摘要