Predicting Brain Amyloid Using Multivariate Morphometry Statistics, Sparse Coding, and Correntropy: Validation in 1,101 Individuals From the ADNI and OASIS Databases

Predicting Brain Amyloid Using Multivariate Morphometry Statistics, Sparse Coding, and Correntropy: Validation in 1,101 Individuals From the ADNI and OASIS Databases

Biomarker assisted preclinical/early detection and intervention in Alzheimer’s disease (AD) may be the key to therapeutic breakthroughs. One of the presymptomatic hallmarks of AD is the accumulation of beta-amyloid (Aβ) plaques in the human brain. However, current methods to detect Aβ pathology are...

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Bibliographic Details
Main Authors: Jianfeng Wu, Qunxi Dong, Jie Gui, Jie Zhang, Yi Su, Kewei Chen, Paul M. Thompson, Richard J. Caselli, Eric M. Reiman, Jieping Ye, Yalin Wang
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-08-01
Series:Frontiers in Neuroscience
Subjects:
Alzheimer’s disease
hippocampal multivariate morphometry statistics
Dictionary and Correntropy-induced Sparse Coding
beta-amyloid burden
ADNI and OASIS database
Online Access:https://www.frontiersin.org/articles/10.3389/fnins.2021.669595/full

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https://www.frontiersin.org/articles/10.3389/fnins.2021.669595/full

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