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A multivariate nonlinear mixed effects model for longitudinal image analysis: Application to amyloid...

A multivariate nonlinear mixed effects model for longitudinal image analysis: Application to amyloid...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_4912927

A multivariate nonlinear mixed effects model for longitudinal image analysis: Application to amyloid imaging

About this item

Full title

A multivariate nonlinear mixed effects model for longitudinal image analysis: Application to amyloid imaging

Publisher

United States: Elsevier Inc

Journal title

NeuroImage (Orlando, Fla.), 2016-07, Vol.134, p.658-670

Language

English

Formats

Publication information

Publisher

United States: Elsevier Inc

More information

Scope and Contents

Contents

It is important to characterize the temporal trajectories of disease-related biomarkers in order to monitor progression and identify potential points of intervention. These are especially important for neurodegenerative diseases, as therapeutic intervention is most likely to be effective in the preclinical disease stages prior to significant neuron...

Alternative Titles

Full title

A multivariate nonlinear mixed effects model for longitudinal image analysis: Application to amyloid imaging

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_4912927

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_4912927

Other Identifiers

ISSN

1053-8119

E-ISSN

1095-9572

DOI

10.1016/j.neuroimage.2016.04.001

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