Multiscale Adaptive Regression Models for Neuroimaging Data.
about
Spatially Varying Coefficient Model for Neuroimaging Data with Jump DiscontinuitiesA semi-parametric nonlinear model for event-related fMRI.Spatiotemporal linear mixed effects modeling for the mass-univariate analysis of longitudinal neuroimage data.Multiscale adaptive generalized estimating equations for longitudinal neuroimaging dataBayesian spatial transformation models with applications in neuroimaging data.SGPP: spatial Gaussian predictive process models for neuroimaging dataTensor Regression with Applications in Neuroimaging Data Analysis.FVGWAS: Fast voxelwise genome wide association analysis of large-scale imaging genetic data.Impact of sex and gonadal steroids on neonatal brain structure.TwinMARM: two-stage multiscale adaptive regression methods for twin neuroimaging data.Multiscale adaptive marginal analysis of longitudinal neuroimaging data with time-varying covariates.Group-wise FMRI activation detection on DICCCOL landmarksFunctional-mixed effects models for candidate genetic mapping in imaging genetic studies.Local Tests for Identifying Anisotropic Diffusion Areas in Human Brain with DTI.Sex differences in grey matter atrophy patterns among AD and aMCI patients: results from ADNILongitudinal High-Dimensional Principal Components Analysis with Application to Diffusion Tensor Imaging of Multiple Sclerosis.Spatially Weighted Principal Component Analysis for Imaging Classification.Spatially Weighted Principal Component Regression for High-Dimensional Prediction.Multivariate semiparametric spatial methods for imaging data.Diffusion tensor imaging-based characterization of brain neurodevelopment in primatesOptimally-Discriminative Voxel-Based Morphometry significantly increases the ability to detect group differences in schizophrenia, mild cognitive impairment, and Alzheimer's disease.More insights into early brain development through statistical analyses of eigen-structural elements of diffusion tensor imaging using multivariate adaptive regression splines.Single-index varying coefficient model for functional responsesMassively parallel nonparametric regression, with an application to developmental brain mapping.Common variants in psychiatric risk genes predict brain structure at birth.Extraction of dynamic functional connectivity from brain grey matter and white matter for MCI classification.Discussion of the paper "Clustering Random Curves Under Spatial Interdependence with Application to Service Accessibility" by Jiang and Serban.MULTISCALE ADAPTIVE SMOOTHING MODELS FOR THE HEMODYNAMIC RESPONSE FUNCTION IN FMRI.SR-HARDI: Spatially Regularizing High Angular Resolution Diffusion ImagingTAILOR THE LONGITUDINAL ANAYSIS FOR NIH LONGITUDINAL NORMAL BRAIN DEVELOPMENTAL STUDY.MWPCR: Multiscale Weighted Principal Component Regression for High-dimensional Prediction.FSEM: Functional Structural Equation Models for Twin Functional Data
P2860
Q28651378-DF593F1C-1333-4DF9-886F-650A631149F2Q30371389-B41A6D1A-EFCC-4B27-A518-3B3DEA79A982Q30486156-47FD745A-22C5-4E9A-8CB4-F7E9A3E3F8C2Q30586512-7BB749CB-90D9-429A-AD00-82A2F18C8492Q30677984-E5565A73-FB25-4FE7-968A-CAEA5171E121Q30700256-7D9CB600-62FC-4047-95BC-3E2FBF89E61BQ30813361-9FDB69DF-3A47-4856-A4AE-9221FA847BAEQ30961457-655E295A-0826-4809-A0EE-53F0BC4632A4Q34129590-3F07884C-6A41-460E-B53D-680AF5554EF1Q34144322-1C7A2771-4681-4664-BE3A-0C29CB9046D2Q34253546-DE00CA91-56FA-4FDC-9E44-321B117CDE6AQ34389562-0CCEA118-51FF-477F-A6FE-46F6D9328F3AQ34536512-55EFDBDD-EC58-478E-BE24-40CDEDB57992Q34794904-FC95B62B-C9D5-4E9A-B622-5F681BC9291CQ34901300-D6B833A4-B47C-4A34-9FBE-FC2119C95A36Q35046724-19589F25-F1FC-4EF1-9FBE-F89BBB99F986Q35741349-30782B48-2C3B-41E3-B8D0-6B2328922F56Q35879648-70402705-02CF-4AFD-9985-B17BF41E59ACQ36333882-BF003973-3C4E-4664-95A5-D998796EE6C4Q36443967-F356D79A-EEC2-451C-9F75-329310FAD59EQ37025490-7C0F7385-EEE5-40C3-A50E-8457D6E17743Q37227868-C5DF79D5-34A5-4B4B-87F5-26B0E6966C26Q37322415-6DAA9D43-E422-459E-8894-75043253F005Q37661500-7FDC41EE-C938-4CFB-A9DE-A99B7BE5CBD2Q37688290-7A469817-B031-4992-8365-0292153432EBQ38700565-1C9FA350-6AA2-4756-8ADE-E8360ABBC2E2Q41252937-D87380B4-1E0D-4AA1-9F17-FB4A956D1399Q41950281-538A530A-C0E1-4C98-8918-0556998594FFQ42146673-70769D01-2DC8-4A2D-BFA7-E7451FCCB5F8Q43007344-5C0C47C9-8EE8-4F58-B7D0-EFEDF47C16C6Q47131107-45DBA18F-8B02-469D-8009-32FD9FD9E049Q57446193-22654E3B-A36D-4312-B7C3-97BEDFAF1030
P2860
Multiscale Adaptive Regression Models for Neuroimaging Data.
description
2011 nî lūn-bûn
@nan
2011 թուականի Սեպտեմբերին հրատարակուած գիտական յօդուած
@hyw
2011 թվականի սեպտեմբերին հրատարակված գիտական հոդված
@hy
2011年の論文
@ja
2011年論文
@yue
2011年論文
@zh-hant
2011年論文
@zh-hk
2011年論文
@zh-mo
2011年論文
@zh-tw
2011年论文
@wuu
name
Multiscale Adaptive Regression Models for Neuroimaging Data.
@ast
Multiscale Adaptive Regression Models for Neuroimaging Data.
@en
Multiscale Adaptive Regression Models for Neuroimaging Data.
@nl
type
label
Multiscale Adaptive Regression Models for Neuroimaging Data.
@ast
Multiscale Adaptive Regression Models for Neuroimaging Data.
@en
Multiscale Adaptive Regression Models for Neuroimaging Data.
@nl
prefLabel
Multiscale Adaptive Regression Models for Neuroimaging Data.
@ast
Multiscale Adaptive Regression Models for Neuroimaging Data.
@en
Multiscale Adaptive Regression Models for Neuroimaging Data.
@nl
P2093
P2860
P1476
Multiscale Adaptive Regression Models for Neuroimaging Data.
@en
P2093
Hongtu Zhu
John H Gilmore
P2860
P304
P356
10.1111/J.1467-9868.2010.00767.X
P577
2011-09-01T00:00:00Z