TY - JOUR
T1 - Big Data and Neuroimaging
AU - Webb-Vargas, Yenny
AU - Chen, Shaojie
AU - Fisher, Aaron
AU - Mejia, Amanda
AU - Xu, Yuting
AU - Crainiceanu, Ciprian
AU - Caffo, Brian
AU - Lindquist, Martin A.
N1 - Funding Information:
Acknowledgements The projects described were supported by the NIH Grants R01 EB012547 and R01 EB016061 from the National Institute of Biomedical Imaging And Bioengineering, and R01 NS060910 from the National Institute of Neurological Disorders and Stroke.
Funding Information:
The projects described were supported by the NIH Grants R01 EB012547 and R01 EB016061 from the National Institute of Biomedical Imaging And Bioengineering, and R01 NS060910 from the National Institute of Neurological Disorders and Stroke.
Publisher Copyright:
© 2017, International Chinese Statistical Association.
PY - 2017/12/1
Y1 - 2017/12/1
N2 - 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.
AB - 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.
KW - Big Data
KW - Data fusion
KW - Dynamic networks
KW - High-dimensional causal inference
KW - High-dimensional computation
KW - High-dimensional inference
KW - Neuroimaging
KW - Shrinkage
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U2 - 10.1007/s12561-017-9195-y
DO - 10.1007/s12561-017-9195-y
M3 - Article
C2 - 29335670
AN - SCOPUS:85019831725
VL - 9
SP - 543
EP - 558
JO - Statistics in Biosciences
JF - Statistics in Biosciences
SN - 1867-1764
IS - 2
ER -