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The application of artificial intelligence in alzheimer's research
Q Zhao, H Xu, J Li, FA Rajput… - Tsinghua Science and …, 2023 - ieeexplore.ieee.org
Alzheimer's disease (AD) is an irreversible and neurodegenerative disease that slowly
impairs memory and neurocognitive function, but the etiology of AD is still unclear. With the …
impairs memory and neurocognitive function, but the etiology of AD is still unclear. With the …
The ROSMAP project: aging and neurodegenerative diseases through omic sciences
AP Pérez-González, AL García-Kroepfly… - Frontiers in …, 2024 - frontiersin.org
The Religious Order Study and Memory and Aging Project (ROSMAP) is an initiative that
integrates two longitudinal cohort studies, which have been collecting clinicopathological …
integrates two longitudinal cohort studies, which have been collecting clinicopathological …
Single-cell genomics and regulatory networks for 388 human brains
Single-cell genomics is a powerful tool for studying heterogeneous tissues such as the
brain. Yet little is understood about how genetic variants influence cell-level gene …
brain. Yet little is understood about how genetic variants influence cell-level gene …
Improving the classification of alzheimer's disease using hybrid gene selection pipeline and deep learning
Alzheimer's is a progressive, irreversible, neurodegenerative brain disease. Even with
prominent symptoms, it takes years to notice, decode, and reveal Alzheimer's. However …
prominent symptoms, it takes years to notice, decode, and reveal Alzheimer's. However …
[HTML][HTML] Deep belief network-based approach for detecting Alzheimer's disease using the multi-omics data
Alzheimer's disease (AD) is the most uncertain form of Dementia in terms of finding out the
mechanism. AD does not have a vital genetic factor to relate to. There were no reliable …
mechanism. AD does not have a vital genetic factor to relate to. There were no reliable …
Machine learning framework for the prediction of Alzheimer's disease using gene expression data based on efficient gene selection
In recent years, much research has focused on using machine learning (ML) for disease
prediction based on gene expression (GE) data. However, many diseases have received …
prediction based on gene expression (GE) data. However, many diseases have received …
[HTML][HTML] A machine learning approach to unmask novel gene signatures and prediction of Alzheimer's disease within different brain regions
A Sharma, P Dey - Genomics, 2021 - Elsevier
Alzheimer's disease (AD) is a progressive neurodegenerative disorder whose aetiology is
currently unknown. Although numerous studies have attempted to identify the genetic risk …
currently unknown. Although numerous studies have attempted to identify the genetic risk …
Applying Proteomics and Computational Approaches to Identify Novel Targets in Blast-Associated Post-Traumatic Epilepsy
Traumatic brain injury (TBI) can lead to post-traumatic epilepsy (PTE). Blast TBI (bTBI) found
in Veterans presents with several complications, including cognitive and behavioral …
in Veterans presents with several complications, including cognitive and behavioral …
Unearthing of key genes driving the pathogenesis of Alzheimer's disease via bioinformatics
X Zhao, H Yao, X Li - Frontiers in Genetics, 2021 - frontiersin.org
Alzheimer's disease (AD) is a neurodegenerative disease with unelucidated molecular
pathogenesis. Herein, we aimed to identify potential hub genes governing the pathogenesis …
pathogenesis. Herein, we aimed to identify potential hub genes governing the pathogenesis …
Automated classification of Alzheimer's disease based on deep belief neural networks
When it comes to the causes of dementia, Alzheimer's disease is the most mysterious. There
is no central genetic component connected to Alzheimer's disease. Previous approaches …
is no central genetic component connected to Alzheimer's disease. Previous approaches …