Opening the black box: Understanding the science behind big data and predictive analytics

Ira S. Hofer*, Eran Halperin, Maxime Cannesson

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

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.

Original languageEnglish
Pages (from-to)1139-1143
Number of pages5
JournalAnesthesia and Analgesia
Volume127
Issue number5
DOIs
StatePublished - 2018
Externally publishedYes

Funding

FundersFunder number
National Institutes of HealthR01 NR013912, PPINNC-2
National Institute of General Medical SciencesR01GM117622
Edwards Lifesciences

    Fingerprint

    Dive into the research topics of 'Opening the black box: Understanding the science behind big data and predictive analytics'. Together they form a unique fingerprint.

    Cite this