Big data in systemic sclerosis: Great potential for the future.
Systemic sclerosis
big data
methodology
rare diseases
registries
Journal
Journal of scleroderma and related disorders
ISSN: 2397-1991
Titre abrégé: J Scleroderma Relat Disord
Pays: England
ID NLM: 101685427
Informations de publication
Date de publication:
Oct 2020
Oct 2020
Historique:
received:
14
07
2019
accepted:
30
04
2020
entrez:
6
4
2022
pubmed:
1
10
2020
medline:
1
10
2020
Statut:
ppublish
Résumé
Since it was first used in 1997, the term "big data" has been popularized; however, the concept of big data is relatively new to medicine. Big data refers to a method and technique to systematically retrieve, collect, manage, and analyze very large and complex sets of structured and unstructured data that cannot be sufficiently processed using traditional methods of processing data. Integrating big data in rare diseases with low prevalence and incidence, like systemic sclerosis is of particular importance. We conducted a literature review of use of big data in systemic sclerosis. The volume of data on systemic sclerosis has grown steadily in the recent years; however, big data methods have not been readily used. This inexhaustible source of data needs to be used more to unleash its full potential.
Identifiants
pubmed: 35382520
doi: 10.1177/2397198320929805
pii: 10.1177_2397198320929805
pmc: PMC8922620
doi:
Types de publication
Journal Article
Review
Langues
eng
Pagination
172-177Informations de copyright
© The Author(s) 2020.
Déclaration de conflit d'intérêts
Declaration of conflicting interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
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