重症监护病房急性肾损伤预测的机器学习

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2022-09-01 DOI:10.1053/j.ackd.2022.06.005
Eric R. Gottlieb , Mathew Samuel , Joseph V. Bonventre , Leo A. Celi , Heather Mattie
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引用次数: 5

摘要

机器学习是人工智能的一个领域,在这个领域中,计算机被训练来通过复杂的数学算法进行预测或识别数据中的模式。它在重症监护中有很大的潜力来预测预后,如急性肾损伤,并可用于预后和建议管理策略。机器学习也可以作为一种研究工具来推进我们对急性肾损伤的临床和生化理解。在这篇综述中,我们介绍了机器学习的基本概念,并回顾了这些领域的最新研究。
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Machine Learning for Acute Kidney Injury Prediction in the Intensive Care Unit

Machine learning is the field of artificial intelligence in which computers are trained to make predictions or to identify patterns in data through complex mathematical algorithms. It has great potential in critical care to predict outcomes, such as acute kidney injury, and can be used for prognosis and to suggest management strategies. Machine learning can also be used as a research tool to advance our clinical and biochemical understanding of acute kidney injury. In this review, we introduce basic concepts in machine learning and review recent research in each of these domains.

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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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