History and progress of hypotheses and clinical trials for Alzheimer's disease
PP Liu, Y Xie, XY Meng, JS Kang - Signal transduction and targeted …, 2019 - nature.com
Alzheimer's disease (AD) is a neurodegenerative disease characterized by progressive
memory loss along with neuropsychiatric symptoms and a decline in activities of daily life. Its …
memory loss along with neuropsychiatric symptoms and a decline in activities of daily life. Its …
Alzheimer's disease: past, present, and future
Although dementia has been described in ancient texts over many centuries (eg,“Be kind to
your father, even if his mind fail him.”–Old Testament: Sirach 3: 12), our knowledge of its …
your father, even if his mind fail him.”–Old Testament: Sirach 3: 12), our knowledge of its …
Deep learning encodes robust discriminative neuroimaging representations to outperform standard machine learning
Recent critical commentaries unfavorably compare deep learning (DL) with standard
machine learning (SML) approaches for brain imaging data analysis. However, their …
machine learning (SML) approaches for brain imaging data analysis. However, their …
Understanding disease progression and improving Alzheimer's disease clinical trials: Recent highlights from the Alzheimer's Disease Neuroimaging Initiative
DP Veitch, MW Weiner, PS Aisen, LA Beckett… - Alzheimer's & …, 2019 - Elsevier
Introduction The overall goal of the Alzheimer's Disease Neuroimaging Initiative (ADNI) is to
validate biomarkers for Alzheimer's disease (AD) clinical trials. ADNI is a multisite …
validate biomarkers for Alzheimer's disease (AD) clinical trials. ADNI is a multisite …
Magnetoencephalography for brain electrophysiology and imaging
S Baillet - Nature neuroscience, 2017 - nature.com
We review the aspects that uniquely characterize magnetoencephalography (MEG) among
the techniques available to explore and resolve brain function and dysfunction. While …
the techniques available to explore and resolve brain function and dysfunction. While …
Multi-omics integration in biomedical research–A metabolomics-centric review
Recent advances in high-throughput technologies have enabled the profiling of multiple
layers of a biological system, including DNA sequence data (genomics), RNA expression …
layers of a biological system, including DNA sequence data (genomics), RNA expression …
[HTML][HTML] Layer-wise relevance propagation for explaining deep neural network decisions in MRI-based Alzheimer's disease classification
Deep neural networks have led to state-of-the-art results in many medical imaging tasks
including Alzheimer's disease (AD) detection based on structural magnetic resonance …
including Alzheimer's disease (AD) detection based on structural magnetic resonance …
Alzheimer's disease risk genes and mechanisms of disease pathogenesis
We review the genetic risk factors for late-onset Alzheimer's disease (AD) and their role in
AD pathogenesis. More recent advances in understanding of the human genome …
AD pathogenesis. More recent advances in understanding of the human genome …
Genome-wide association analysis of 19,629 individuals identifies variants influencing regional brain volumes and refines their genetic co-architecture with cognitive …
Volumetric variations of the human brain are heritable and are associated with many brain-
related complex traits. Here we performed genome-wide association studies (GWAS) of 101 …
related complex traits. Here we performed genome-wide association studies (GWAS) of 101 …
Machine learning framework for early MRI-based Alzheimer's conversion prediction in MCI subjects
Mild cognitive impairment (MCI) is a transitional stage between age-related cognitive
decline and Alzheimer's disease (AD). For the effective treatment of AD, it would be …
decline and Alzheimer's disease (AD). For the effective treatment of AD, it would be …