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Opening the Black Box: Understanding the Science Behind Big Data and Predictive Analytics
Author(s) -
Ira Hofer,
Eran Halperin,
Maxime Cannesson
Publication year - 2018
Publication title -
anesthesia and analgesia/anesthesia and analgesia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.404
H-Index - 201
eISSN - 1526-7598
pISSN - 0003-2999
DOI - 10.1213/ane.0000000000003463
Subject(s) - big data , data science , predictive analytics , black box , analytics , medicine , internet privacy , computer science , data mining , artificial intelligence
Big data, smart data, predictive analytics, and other similar terms are ubiquitous in the lay and scientific literature. However, despite the frequency of usage, these terms are often poorly understood, and evidence of their disruption to clinical care is hard to find. This article aims to address these issues by first defining and elucidating the term big data, exploring the ways in which modern medical data, both inside and outside the electronic medical record, meet the established definitions of big data. We then define the term smart data and discuss the transformations necessary to make big data into smart data. Finally, we examine the ways in which this transition from big to smart data will affect what we do in research, retrospective work, and ultimately patient care.

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