AIMC Topic: Alzheimer Disease

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Multi-omics Mendelian randomization and machine learning identify candidate therapeutic targets for Alzheimer's and Parkinson's diseases.

Mammalian genome : official journal of the International Mammalian Genome Society
Neurodegenerative diseases (NDDs), including Alzheimer's disease (AD) and Parkinson's disease (PD), are major public health challenges lacking effective therapies. To identify potential drug targets, we integrated large-scale genome-wide association ...

Alzheimer's disease prediction via an explainable CNN using genetic algorithm and SHAP values.

PloS one
Convolutional neural networks (CNNs) are widely recognized for their high precision in image classification. Nevertheless, the lack of transparency in these black-box models raises concerns in sensitive domains such as healthcare, where understanding...

Targeting CXCL8 in post-traumatic stress disorder and Alzheimer's disease: insights from cross-disorder molecular analysis.

Annals of medicine
BACKGROUND: Emerging clinical evidence indicates that post-traumatic stress disorder (PTSD) may accelerate Alzheimer's disease progression, yet the molecular mechanisms linking these disorders remain poorly understood.

Dopamine Self-Polymerization-Assisted Oriented Antibody Immobilization on a Transistor for Alzheimer's Disease Diagnosis.

Analytical chemistry
Antibody transistor biosensors show promise for early Alzheimer's disease (AD) diagnosis due to their single molecule detection capability. However, the random attachment of a payload to antigen-binding fragments (Fab) during biosensor preparation ca...

Artificial Intelligence-Enhanced Multi-Algorithm R Shiny Application for Predictive Modeling and Analytics: Case Study of Alzheimer Disease Diagnostics.

JMIR aging
BACKGROUND: Artificial intelligence (AI) has demonstrated superior diagnostic accuracy compared with medical practitioners, highlighting its growing importance in health care. SMART-Pred (Shiny Multi-Algorithm R Tool for Predictive Modeling) is an in...

An overview of gene and cell therapy approaches for Alzheimer's disease.

Metabolic brain disease
Alzheimer's disease (AD), acknowledged as the leading cause of dementia, is defined by the accumulation of amyloid plaques and neurofibrillary tangles (NFTs) in the brain. This condition presents a significant challenge to global health due to its co...

Pattern and structural detection in grayscale images through the application of quantile graphs in higher-dimensional spaces.

Scientific reports
Deep Learning (DL) and Machine Learning (ML) algorithms are adept at managing and classifying a wide range of data formats, including time series, text, and images, addressing challenges in both supervised and unsupervised learning. However, the prac...

Cortical layer multi-parameter analysis of neurovascular impairments in AD/ADRD rodent model with in vivo optical imaging.

Translational neurodegeneration
BACKGROUND: Neurovascular biomarkers have the potential to enhance early diagnosis of Alzheimer's disease (AD) and AD-related dementias (ADRD), as cerebrovascular alterations often precede neurodegeneration. However, their clinical application remain...

A Framework for Identifying Serum Exosomal Lipid Biomarkers in Alzheimer's Disease.

ACS chemical neuroscience
The escalating global burden of Alzheimer's disease (AD), projected to reach $16.9 trillion by 2050 with disproportionate impacts on low- and middle-income countries and racial minorities, underscores an urgent need for accessible early detection too...

Lightweight Vision Transformer with transfer learning for interpretable Alzheimer's disease severity assessment.

Scientific reports
Early and reliable diagnostic tools are critical for slowing the progression of Alzheimer's disease (AD), a neurodegenerative disorder characterized by memory loss and cognitive decline. This study introduces, ViTTL, lightweight deep learning framewo...