Monitoring Big Data During Mechanical Ventilation in the ICU

被引：6

作者：

Pham

Smallwood

Goligher

Lamberti

Schmidt

Blanch

Walsh

机构：

[1] Division of Critical Care of Anesthesia, Critical Care and Pain Medicine, Boston Children’s Hospital and Harvard Medical School, Boston, MA

来源：

RESPIRATORY CARE | 2020年 / 65卷 / 06期

关键词：

Data science; Machine learning; Mechani cal cal ventilation; Mechanibig data; Neural network;

D O I：

10.4187/respcare.07500

中图分类号：

R4 [临床医学];

学科分类号：

1002 ; 100602 ;

摘要：

The electronic health record allows the assimilation of large amounts of clinical and laboratory data. Big data describes the analysis of large data sets using computational modeling to reveal patterns, trends, and associations. How can big data be used to predict ventilator discontinuation or impending compromise, and how can it be incorporated into the clinical workflow? This article will serve 2 purposes. First, a general overview is provided for the layperson and introduces key concepts, definitions, best practices, and things to watch out for when reading a paper that incorporates machine learning. Second, recent publications at the intersection of big data, machine learning, and mechanical ventilation are presented. © 2020 Daedalus Enterprises.

引用

页码：906 / 910

页数：5

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