Literature DB >> 32457178

Monitoring Big Data During Mechanical Ventilation in the ICU.

Craig D Smallwood1,2.   

Abstract

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.
Copyright © 2020 by Daedalus Enterprises.

Keywords:  big data; data science; machine learning; mechanical ventilation; neural network

Mesh:

Year:  2020        PMID: 32457178     DOI: 10.4187/respcare.07500

Source DB:  PubMed          Journal:  Respir Care        ISSN: 0020-1324            Impact factor:   2.258


  2 in total

Review 1.  Data harnessing to nurture the human mind for a tailored approach to the child.

Authors:  Saheli Chatterjee Misra; Kaushik Mukhopadhyay
Journal:  Pediatr Res       Date:  2022-09-30       Impact factor: 3.953

2.  Influence of Dexmedetomidine on Diaphragm Function and Postoperative Outcomes in ICU Patients with Mechanical Ventilation.

Authors:  Chengda Zhao; Meihua Huang; Baiyun Wang; Huanhui Zhong; Wen Meng
Journal:  Evid Based Complement Alternat Med       Date:  2021-10-25       Impact factor: 2.629

  2 in total

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