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 …

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 …

Single-cell genomics and regulatory networks for 388 human brains

PS Emani, JJ Liu, D Clarke, M Jensen, J Warrell… - Science, 2024 - science.org
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 …

Improving the classification of alzheimer's disease using hybrid gene selection pipeline and deep learning

N Mahendran, PMDR Vincent, K Srinivasan… - Frontiers in …, 2021 - frontiersin.org
Alzheimer's is a progressive, irreversible, neurodegenerative brain disease. Even with
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

N Mahendran, DRV PM - Computational and Structural Biotechnology …, 2023 - Elsevier
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 …

Machine learning framework for the prediction of Alzheimer's disease using gene expression data based on efficient gene selection

A El-Gawady, MA Makhlouf, BBS Tawfik, H Nassar - Symmetry, 2022 - mdpi.com
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 …

[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 …

Applying Proteomics and Computational Approaches to Identify Novel Targets in Blast-Associated Post-Traumatic Epilepsy

JL Browning, KA Wilson, O Shandra, X Wei… - International Journal of …, 2024 - mdpi.com
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 …

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 …

Automated classification of Alzheimer's disease based on deep belief neural networks

K Nanthini, A Tamilarasi, D Sivabalaselvamani… - Neural Computing and …, 2024 - Springer
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 …