Machine Learning for Acute Kidney Injury Prediction in the Intensive Care Unit

被引：13

作者：

Gottlieb, Eric R. ^{[1
,2
,3
,7
]}

Samuel, Mathew ^{[4
]}

Bonventre, Joseph V. ^{[1
,2
]}

Celi, Leo A. ^{[2
,3
,4
,5
,6
]}

Mattie, Heather ^{[5
]}

机构：

[1] Brigham & Womens Hosp, Renal Sect, Boston, MA USA

[2] Harvard Med Sch, Boston, MA USA

[3] MIT, Lab Computat Physiol, Cambridge, MA USA

[4] MIT Crit Data, Cambridge, MA USA

[5] Harvard TH Chan Sch Publ Hlth, Boston, MA USA

[6] Beth Israel Deaconess Med Ctr, Boston, MA USA

[7] 75 Francis St,MRB 4, Boston, MA 02114 USA

来源：

ADVANCES IN CHRONIC KIDNEY DISEASE | 2022年 / 29卷 / 05期

关键词：

Machine learning; AKI prediction; ICU Nephrology; Artificial intelligence; Algorithms; MODELS; ICU;

D O I：

10.1053/j.ackd.2022.06.005

中图分类号：

R5 [内科学]; R69 [泌尿科学（泌尿生殖系疾病）];

学科分类号：

1002 ; 100201 ;

摘要：

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.(c) 2022 by the National Kidney Foundation, Inc. All rights reserved.

引用

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页码：431 / 438

页数：8

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