Clinical utility of cerebrospinal fluid biomarkers in the diagnosis of early Alzheimer's disease

K Blennow, B Dubois, AM Fagan, P Lewczuk… - Alzheimer's & …, 2015 - Elsevier
Several potential disease-modifying drugs for Alzheimer's disease (AD) have failed to show
any effect on disease progression in clinical trials, conceivably because the AD subjects are …

Estrogen: a master regulator of bioenergetic systems in the brain and body

JR Rettberg, J Yao, RD Brinton - Frontiers in neuroendocrinology, 2014 - Elsevier
Estrogen is a fundamental regulator of the metabolic system of the female brain and body.
Within the brain, estrogen regulates glucose transport, aerobic glycolysis, and mitochondrial …

Brain MRI analysis for Alzheimer's disease diagnosis using an ensemble system of deep convolutional neural networks

J Islam, Y Zhang - Brain informatics, 2018 - Springer
Alzheimer's disease is an incurable, progressive neurological brain disorder. Earlier
detection of Alzheimer's disease can help with proper treatment and prevent brain tissue …

Hierarchical feature representation and multimodal fusion with deep learning for AD/MCI diagnosis

HI Suk, SW Lee, D Shen… - NeuroImage, 2014 - Elsevier
For the last decade, it has been shown that neuroimaging can be a potential tool for the
diagnosis of Alzheimer's Disease (AD) and its prodromal stage, Mild Cognitive Impairment …

Alzheimer's disease multiclass diagnosis via multimodal neuroimaging embedding feature selection and fusion

Y Zhang, S Wang, K **a, Y Jiang, P Qian… - Information …, 2021 - Elsevier
Alzheimer's disease (AD) will become a global burden in the coming decades according to
the latest statistical survey. How to effectively detect AD or MCI (mild cognitive impairment) …

Multimodal classification of Alzheimer's disease and mild cognitive impairment

D Zhang, Y Wang, L Zhou, H Yuan, D Shen… - Neuroimage, 2011 - Elsevier
Effective and accurate diagnosis of Alzheimer's disease (AD), as well as its prodromal stage
(ie, mild cognitive impairment (MCI)), has attracted more and more attention recently. So far …

Multi-modal multi-task learning for joint prediction of multiple regression and classification variables in Alzheimer's disease

D Zhang, D Shen… - NeuroImage, 2012 - Elsevier
Many machine learning and pattern classification methods have been applied to the
diagnosis of Alzheimer's disease (AD) and its prodromal stage, ie, mild cognitive impairment …

BrainAGE in Mild Cognitive Impaired Patients: Predicting the Conversion to Alzheimer's Disease

C Gaser, K Franke, S Klöppel, N Koutsouleris, H Sauer… - PloS one, 2013 - journals.plos.org
Alzheimer's disease (AD), the most common form of dementia, shares many aspects of
abnormal brain aging. We present a novel magnetic resonance imaging (MRI)-based …

Artificial intelligence for Alzheimer's disease: promise or challenge?

C Fabrizio, A Termine, C Caltagirone, G Sancesario - Diagnostics, 2021 - mdpi.com
Decades of experimental and clinical research have contributed to unraveling many
mechanisms in the pathogenesis of Alzheimer's disease (AD), but the puzzle is still …

Multi-modal neuroimaging feature selection with consistent metric constraint for diagnosis of Alzheimer's disease

X Hao, Y Bao, Y Guo, M Yu, D Zhang, SL Risacher… - Medical image …, 2020 - Elsevier
The accurate diagnosis of Alzheimer's disease (AD) and its early stage, eg, mild cognitive
impairment (MCI), is essential for timely treatment or possible intervention to slow down AD …