Big Data Defined: A Practical Review for Neurosurgeons.

Clinical practice Data science Machine learning Registry

Journal

World neurosurgery
ISSN: 1878-8769
Titre abrégé: World Neurosurg
Pays: United States
ID NLM: 101528275

Informations de publication

Date de publication:
Jan 2020
Historique:
received: 02 10 2018
revised: 16 09 2019
accepted: 17 09 2019
pubmed: 29 9 2019
medline: 29 1 2020
entrez: 29 9 2019
Statut: ppublish

Résumé

Modern science and healthcare generate vast amounts of data, and, coupled with the increasingly inexpensive and accessible computing, a tremendous opportunity exists to use these data to improve care. A better understanding of data science and its relationship to neurosurgical practice will be increasingly important as we transition into this modern "big data" era. A review of the literature was performed for key articles referencing big data for neurosurgical care or related topics. In the present report, we first defined the nature and scope of data science from a technical perspective. We then discussed its relationship to the modern neurosurgical practice, highlighting key references, which might form a useful introductory reading list. Numerous challenges exist going forward; however, organized neurosurgery has an important role in fostering and facilitating these efforts to merge data science with neurosurgical practice.

Sections du résumé

BACKGROUND BACKGROUND
Modern science and healthcare generate vast amounts of data, and, coupled with the increasingly inexpensive and accessible computing, a tremendous opportunity exists to use these data to improve care. A better understanding of data science and its relationship to neurosurgical practice will be increasingly important as we transition into this modern "big data" era.
METHODS METHODS
A review of the literature was performed for key articles referencing big data for neurosurgical care or related topics.
RESULTS RESULTS
In the present report, we first defined the nature and scope of data science from a technical perspective. We then discussed its relationship to the modern neurosurgical practice, highlighting key references, which might form a useful introductory reading list.
CONCLUSIONS CONCLUSIONS
Numerous challenges exist going forward; however, organized neurosurgery has an important role in fostering and facilitating these efforts to merge data science with neurosurgical practice.

Identifiants

pubmed: 31562965
pii: S1878-8750(19)32522-7
doi: 10.1016/j.wneu.2019.09.092
pii:
doi:

Types de publication

Journal Article Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

e842-e849

Commentaires et corrections

Type : CommentIn
Type : CommentIn

Informations de copyright

Copyright © 2019 Elsevier Inc. All rights reserved.

Auteurs

Mohamad Bydon (M)

Department of Neurosurgery, Mayo Clinic, Rochester, Minnesota, USA.

Clemens M Schirmer (CM)

Department of Neurosurgery, Geisinger Health System, Wilkes-Barre, Pennsylvania, USA.

Eric K Oermann (EK)

Department of Neurosurgery, Mount Sinai Health System, New York, New York, USA.

Ryan S Kitagawa (RS)

Department of Neurosurgery, University of Texas Health Science Center, Houston, Texas, USA.

Nader Pouratian (N)

Department of Neurosurgery, University of California, Los Angeles, Medical Center, Los Angeles, California, USA.

Jason Davies (J)

Department of Neurosurgery, State University of New York, Buffalo, New York, USA.

Ashwini Sharan (A)

Department of Neurosurgery, Thomas Jefferson University Hospital, Philadelphia, Pennsylvania, USA.

Lola B Chambless (LB)

Department of Neurosurgery, Vanderbilt University Medical Center, Nashville, Tennessee, USA. Electronic address: lola.chambless@vanderbilt.edu.

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Classifications MeSH