2014 Update of the Alzheimer's Disease Neuroimaging Initiative: a review of papers published since its inception
MW Weiner, DP Veitch, PS Aisen, LA Beckett… - Alzheimer's & …, 2015 - Elsevier
Abstract The Alzheimer's Disease Neuroimaging Initiative (ADNI) is an ongoing,
longitudinal, multicenter study designed to develop clinical, imaging, genetic, and …
longitudinal, multicenter study designed to develop clinical, imaging, genetic, and …
Genetic analysis of quantitative phenotypes in AD and MCI: imaging, cognition and biomarkers
Abstract The Genetics Core of the Alzheimer's Disease Neuroimaging Initiative (ADNI),
formally established in 2009, aims to provide resources and facilitate research related to …
formally established in 2009, aims to provide resources and facilitate research related to …
Multimodal neuroimaging feature learning for multiclass diagnosis of Alzheimer's disease
The accurate diagnosis of Alzheimer's disease (AD) is essential for patient care and will be
increasingly important as disease modifying agents become available, early in the course of …
increasingly important as disease modifying agents become available, early in the course of …
Early diagnosis of Alzheimer's disease with deep learning
The accurate diagnosis of Alzheimer's disease (AD) plays a significant role in patient care,
especially at the early stage, because the consciousness of the severity and the progression …
especially at the early stage, because the consciousness of the severity and the progression …
[HTML][HTML] Accurate multimodal probabilistic prediction of conversion to Alzheimer's disease in patients with mild cognitive impairment
Accurately identifying the patients that have mild cognitive impairment (MCI) who will go on
to develop Alzheimer's disease (AD) will become essential as new treatments will require …
to develop Alzheimer's disease (AD) will become essential as new treatments will require …
A novel grading biomarker for the prediction of conversion from mild cognitive impairment to Alzheimer's disease
Objective: Identifying mild cognitive impairment (MCI) subjects who will progress to
Alzheimer's disease (AD) is not only crucial in clinical practice, but also has a significant …
Alzheimer's disease (AD) is not only crucial in clinical practice, but also has a significant …
Domain transfer learning for MCI conversion prediction
Machine learning methods have successfully been used to predict the conversion of mild
cognitive impairment (MCI) to Alzheimer's disease (AD), by classifying MCI converters (MCI …
cognitive impairment (MCI) to Alzheimer's disease (AD), by classifying MCI converters (MCI …
Intrinsic polynomials for regression on Riemannian manifolds
We develop a framework for polynomial regression on Riemannian manifolds. Unlike
recently developed spline models on Riemannian manifolds, Riemannian polynomials offer …
recently developed spline models on Riemannian manifolds, Riemannian polynomials offer …
A vector momenta formulation of diffeomorphisms for improved geodesic regression and atlas construction
This paper presents a novel approach for diffeomorphic image regression and atlas
estimation that results in improved convergence and numerical stability. We use a vector …
estimation that results in improved convergence and numerical stability. We use a vector …
Toward the identification of neurophysiological biomarkers for Alzheimer's disease in down syndrome: A potential role for cross-frequency phase-amplitude coupling …
DB Victorino, J Faber, DJLL Pinheiro… - Aging and …, 2023 - pmc.ncbi.nlm.nih.gov
Cross-frequency coupling (CFC) mechanisms play a central role in brain activity.
Pathophysiological mechanisms leading to many brain disorders, such as Alzheimer's …
Pathophysiological mechanisms leading to many brain disorders, such as Alzheimer's …