Literature DB >> 30591356

Big Data Analysis and Machine Learning in Intensive Care Units.

A Núñez Reiz1, M A Armengol de la Hoz2, M Sánchez García3.   

Abstract

Intensive care is an ideal environment for the use of Big Data Analysis (BDA) and Machine Learning (ML), due to the huge amount of information processed and stored in electronic format in relation to such care. These tools can improve our clinical research capabilities and clinical decision making in the future. The present study reviews the foundations of BDA and ML, and explores possible applications in our field from a clinical viewpoint. We also suggest potential strategies to optimize these new technologies and describe a new kind of hybrid healthcare-data science professional with a linking role between clinicians and data.
Copyright © 2018 Elsevier España, S.L.U. y SEMICYUC. All rights reserved.

Entities:  

Keywords:  Análisis secundario de datos clínicos electrónicos; Artificial intelligence; Big Data Analysis; Inteligencia artificial; Machine Learning; Secondary electronic health record data analysis

Mesh:

Year:  2018        PMID: 30591356     DOI: 10.1016/j.medin.2018.10.007

Source DB:  PubMed          Journal:  Med Intensiva (Engl Ed)        ISSN: 2173-5727


  3 in total

1.  Clinical management of sepsis can be improved by artificial intelligence: no.

Authors:  José Garnacho-Montero; Ignacio Martín-Loeches
Journal:  Intensive Care Med       Date:  2020-02-03       Impact factor: 17.440

2.  Which model is superior in predicting ICU survival: artificial intelligence versus conventional approaches.

Authors:  Farzad Mirzakhani; Farahnaz Sadoughi; Mahboobeh Hatami; Alireza Amirabadizadeh
Journal:  BMC Med Inform Decis Mak       Date:  2022-06-26       Impact factor: 3.298

3.  [Covid-19 pandemic and digital transformation in critical care units].

Authors:  F Murillo-Cabezas; E Vigil-Martín; N Raimondi; J Pérez-Fernández
Journal:  Med Intensiva (Engl Ed)       Date:  2020-04-15
  3 in total

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