Disease progression modelling of Alzheimer’s disease using probabilistic principal components analysis

Disease progression modelling of Alzheimer’s disease using probabilistic principal components analysis

The recent biological redefinition of Alzheimer’s Disease (AD) has spurred the development of statistical models that relate changes in biomarkers with neurodegeneration and worsening condition linked to AD. The ability to measure such changes may facilitate earlier diagnoses for affected individual...

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Bibliographic Details
Main Authors: Martin Saint-Jalmes, Victor Fedyashov, Daniel Beck, Timothy Baldwin, Noel G. Faux, Pierrick Bourgeat, Jurgen Fripp, Colin L. Masters, Benjamin Goudey
Format: Article
Language:English
Published: Elsevier 2023-09-01
Series:NeuroImage
Subjects:
Alzheimer’s disease
Disease progression modeling
Latent disease time
Principal components analysis
Machine learning
Online Access:http://www.sciencedirect.com/science/article/pii/S1053811923004305

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