Big Data and Neuroimaging

Yenny Webb-Vargas, Shaojie Chen, Aaron Fisher, Amanda Mejia, Yuting Xu, Ciprian Crainiceanu, Brian Caffo and Martin A. Lindquist ()
Additional contact information
Yenny Webb-Vargas: Johns Hopkins Bloomberg School of Public Health
Shaojie Chen: Johns Hopkins Bloomberg School of Public Health
Aaron Fisher: Johns Hopkins Bloomberg School of Public Health
Amanda Mejia: Johns Hopkins Bloomberg School of Public Health
Yuting Xu: Johns Hopkins Bloomberg School of Public Health
Ciprian Crainiceanu: Johns Hopkins Bloomberg School of Public Health
Brian Caffo: Johns Hopkins Bloomberg School of Public Health
Martin A. Lindquist: Johns Hopkins Bloomberg School of Public Health

Statistics in Biosciences, 2017, vol. 9, issue 2, No 13, 543-558

Abstract: Abstract Big Data are of increasing importance in a variety of areas, especially in the biosciences. There is an emerging critical need for Big Data tools and methods, because of the potential impact of advancements in these areas. Importantly, statisticians and statistical thinking have a major role to play in creating meaningful progress in this arena. We would like to emphasize this point in this special issue, as it highlights both the dramatic need for statistical input for Big Data analysis and for a greater number of statisticians working on Big Data problems. We use the field of statistical neuroimaging to demonstrate these points. As such, this paper covers several applications and novel methodological developments of Big Data tools applied to neuroimaging data.

Keywords: Big Data; Neuroimaging; High-dimensional computation; High-dimensional inference; High-dimensional causal inference; Data fusion; Shrinkage; Dynamic networks (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s12561-017-9195-y Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:stabio:v:9:y:2017:i:2:d:10.1007_s12561-017-9195-y

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/12561

DOI: 10.1007/s12561-017-9195-y

Access Statistics for this article

Statistics in Biosciences is currently edited by Hongyu Zhao and Xihong Lin

More articles in Statistics in Biosciences from Springer, International Chinese Statistical Association
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().