TY - JOUR
T1 - Full exploitation of high dimensionality in brain imaging
T2 - The JPND working group statement and findings
AU - Adams, Hieab H.H.
AU - Roshchupkin, Gennady V.
AU - DeCarli, Charles
AU - Franke, Barbara
AU - Grabe, Hans J.
AU - Habes, Mohamad
AU - Jahanshad, Neda
AU - Medland, Sarah E.
AU - Niessen, Wiro
AU - Satizabal, Claudia L.
AU - Schmidt, Reinhold
AU - Seshadri, Sudha
AU - Teumer, Alexander
AU - Thompson, Paul M.
AU - Vernooij, Meike W.
AU - Wittfeld, Katharina
AU - Ikram, M. Arfan
N1 - Publisher Copyright:
© 2019 The Authors
PY - 2019/12
Y1 - 2019/12
N2 - Advances in technology enable increasing amounts of data collection from individuals for biomedical research. Such technologies, for example, in genetics and medical imaging, have also led to important scientific discoveries about health and disease. The combination of multiple types of high-throughput data for complex analyses, however, has been limited by analytical and logistic resources to handle high-dimensional data sets. In our previous EU Joint Programme–Neurodegenerative Disease Research (JPND) Working Group, called HD-READY, we developed methods that allowed successful combination of omics data with neuroimaging. Still, several issues remained to fully leverage high-dimensional multimodality data. For instance, high-dimensional features, such as voxels and vertices, which are common in neuroimaging, remain difficult to harmonize. In this Full-HD Working Group, we focused on such harmonization of high-dimensional neuroimaging phenotypes in combination with other omics data and how to make the resulting ultra-high-dimensional data easily accessible in neurodegeneration research.
AB - Advances in technology enable increasing amounts of data collection from individuals for biomedical research. Such technologies, for example, in genetics and medical imaging, have also led to important scientific discoveries about health and disease. The combination of multiple types of high-throughput data for complex analyses, however, has been limited by analytical and logistic resources to handle high-dimensional data sets. In our previous EU Joint Programme–Neurodegenerative Disease Research (JPND) Working Group, called HD-READY, we developed methods that allowed successful combination of omics data with neuroimaging. Still, several issues remained to fully leverage high-dimensional multimodality data. For instance, high-dimensional features, such as voxels and vertices, which are common in neuroimaging, remain difficult to harmonize. In this Full-HD Working Group, we focused on such harmonization of high-dimensional neuroimaging phenotypes in combination with other omics data and how to make the resulting ultra-high-dimensional data easily accessible in neurodegeneration research.
KW - Genetics
KW - High-dimensional
KW - Neuroimaging
KW - Omics
KW - Voxel-based morphometry
KW - Voxels
UR - http://www.scopus.com/inward/record.url?scp=85063480768&partnerID=8YFLogxK
U2 - 10.1016/j.dadm.2019.02.003
DO - 10.1016/j.dadm.2019.02.003
M3 - Article
AN - SCOPUS:85063480768
SN - 2352-8729
VL - 11
SP - 286
EP - 290
JO - Alzheimer's and Dementia: Diagnosis, Assessment and Disease Monitoring
JF - Alzheimer's and Dementia: Diagnosis, Assessment and Disease Monitoring
ER -