机器学习、深度学习和闭环设备-麻醉输送。
Machine Learning, Deep Learning, and Closed Loop Devices-Anesthesia Delivery.
机构信息
University of California Los Angeles, David Geffen School of Medicine, Los Angeles, CA, USA; Department of Anesthesiology and Perioperative Medicine, Ronald Reagan UCLA Medical Center, 757 Westwood Plaza, Suite 3325, Los Angeles, CA 90095-7403, USA.
Edwards Lifesciences, Irvine, CA, USA; Critical Care R&D, 1 Edwards Way, Irvine, CA 92614, USA.
出版信息
Anesthesiol Clin. 2021 Sep;39(3):565-581. doi: 10.1016/j.anclin.2021.03.012. Epub 2021 Jul 12.
Abstract
With the tremendous volume of data captured during surgeries and procedures, critical care, and pain management, the field of anesthesiology is uniquely suited for the application of machine learning, neural networks, and closed loop technologies. In the past several years, this area has expanded immensely in both interest and clinical applications. This article provides an overview of the basic tenets of machine learning, neural networks, and closed loop devices, with emphasis on the clinical applications of these technologies.
摘要
随着手术和程序、重症监护和疼痛管理过程中捕获的大量数据，麻醉学领域非常适合应用机器学习、神经网络和闭环技术。在过去几年中，该领域在兴趣和临床应用方面都有了极大的扩展。本文概述了机器学习、神经网络和闭环设备的基本原理，并重点介绍了这些技术的临床应用。
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本文引用的文献
1
Development and validation of a deep neural network model to predict postoperative mortality, acute kidney injury, and reintubation using a single feature set.
NPJ Digit Med. 2020 Apr 20;3:58. doi: 10.1038/s41746-020-0248-0. eCollection 2020.
2
Machine Learning Prediction of Postoperative Emergency Department Hospital Readmission.
Anesthesiology. 2020 May;132(5):968-980. doi: 10.1097/ALN.0000000000003140.
3
Deep learning interpretation of echocardiograms.
NPJ Digit Med. 2020 Jan 24;3:10. doi: 10.1038/s41746-019-0216-8. eCollection 2020.
4
Artificial Intelligence in Anesthesiology: Current Techniques, Clinical Applications, and Limitations.
Anesthesiology. 2020 Feb;132(2):379-394. doi: 10.1097/ALN.0000000000002960.
5
An automated machine learning-based model predicts postoperative mortality using readily-extractable preoperative electronic health record data.
Br J Anaesth. 2019 Dec;123(6):877-886. doi: 10.1016/j.bja.2019.07.030. Epub 2019 Oct 15.
6
Machine learning in anaesthesia: reactive, proactive… predictive!
Br J Anaesth. 2019 Oct;123(4):401-403. doi: 10.1016/j.bja.2019.07.009. Epub 2019 Aug 20.
7
Feasibility of closed-loop titration of norepinephrine infusion in patients undergoing moderate- and high-risk surgery.
Br J Anaesth. 2019 Oct;123(4):430-438. doi: 10.1016/j.bja.2019.04.064. Epub 2019 Jun 27.
8
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9
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10
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