Big Data Analysis and Machine Learning in Intensive Care Units

被引：21
|
作者：
Nunez Reiz, A. [1 ]
Armengol de la Hoz, M. A. [2 ,3 ,4 ]
Sanchez Garcia, M. [1 ]
机构：
[1] Hosp Univ Clin San Carlos, Serv Med Intens, Madrid, Spain
[2] Harvard Med Sch, Beth Israel Deaconess Med Ctr, Dept Anesthesia Crit Care & Pain Med, Boston, MA USA
[3] MIT, Inst Med Engn & Sci, Lab Computat Physiol, 77 Massachusetts Ave, Cambridge, MA 02139 USA
[4] Univ Politecn Madrid, ETSI Telecomunicac, Biomed Technol Ctr CTB, Biomed Engn & Telemed Grp, Madrid, Spain
来源：
MEDICINA INTENSIVA | 2019年 / 43卷 / 07期
关键词：
Big Data Analysis; Machine Learning; Artificial intelligence; Secondary electronic health record data analysis;
D O I：
10.1016/j.medin.2018.10.007
中图分类号：
R4 [临床医学];
学科分类号：
1002 ; 100602 ;
摘要：
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 witha linking role between clinicians and data. (C) 2018 Elsevier Espana, S.L.U. y SEMICYUC. All rights reserved.
引用
收藏
页码：416 / 426
页数：11
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