Alzheimer's Disease

A multi-target therapeutic framework for Alzheimer's disease: an integrative mechanistic review.

BACKGROUND: Alzheimer's disease (AD) is increasingly recognized as a multifactorial network disorder in which amyloid and tau pathology interact with mitochondrial dysfunction, neuroinflammation, metabolic impairment, vascular dysregulation, and synaptic failure. This review provides an integrative, systems-level synthesis of these mechanisms with emphasis on diagnostic and therapeutic implication...

Hippocampus-centered structural covariance network reorganization in Alzheimer's disease: An individualized graph-based biomarker validated by machine learning.

Alzheimer's disease (AD) is characterized by progressive brain network disintegration, yet quantifying this process at an individual level remains challenging. This study explores the potential of an individualized differential structural covariance network (IDSCN) as a graph theory-based biomarker to capture disease-specific network reorganization. We found that throughout the AD spectrum, signif...

MRI-to-PET synthesis via deep learning for amyloid-β quantification in Alzheimer's disease.

OBJECTIVES: Amyloid-β (Aβ) PET is crucial for diagnosing and monitoring Alzheimer's disease (AD), but its high cost and radiation exposure limit its u...

Latent diffusion autoencoders: Toward efficient and meaningful unsupervised representation learning in medical imaging - a case study on Alzheimer's disease.

This study presents Latent Diffusion Autoencoder (LDAE), a novel encoder-decoder diffusion-based framework for efficient and meaningful unsupervised l...

Are we ready for amyloid-related imaging abnormalities (ARIA) monitoring? A European survey among neuroradiologists and neurologists by the ESNR/EAN Working Group.

OBJECTIVES: Amyloid-lowering immunotherapies can cause amyloid-related imaging abnormalities (ARIA), requiring brain MRI for detection and monitoring....

PyCaret machine learning library with three preprocessing steps after eLORETA source estimation predicts Alzheimer's disease.

Alzheimer's disease (AD) -the most common form of dementia- begins with mild memory loss and gradually progresses, eventually resulting in a generaliz...

Early diagnosis of Alzheimer's disease based on brain morphological changes: A comprehensive approach combining voxel-based morphometry and deep learning.

Deep learning algorithms optimize data by enhancing resolution and suppressing noise associated with biological knowledge. The root issue is that, for...

The role of artificial intelligence in hypertension management.

PURPOSE OF REVIEW: Hypertension remains a leading modifiable risk factor for cardiovascular and renal conditions and dementia. Given its rising global...

Leveraging hemispheric asymmetry in structural MRI with an attention-guided 3D CNN for early prediction of Alzheimer's conversion.

Early identification of mild cognitive impairment (MCI) progressing to Alzheimer's disease (AD) is of paramount importance. Despite the notable advanc...

Synergistic integration of clinical and multi-omics data for early MCI diagnosis using an attention-based graph fusion network.

BACKGROUND: Mild cognitive impairment (MCI), a precursor to Alzheimer's disease (AD), requires precise early diagnosis. Single-omics approaches often ...

Multi-omics integration identifies CACNG3 as a synaptic calcium channel regulator in Alzheimer's disease: Mechanistic insights and therapeutic implications.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline, memory impairment, and impaired daily functio...

Plasma metabolomics identifies lipid mediators linking depression and cognitive decline in late-life depression.

BACKGROUND: Late-life depression (LLD) features recurrent episodes and frequently co-exists with cognitive impairment, which predicts worse outcomes a...

Longitudinal changes in subcortical functional connectivity during Alzheimer's disease progression.

Human cognition and behavior rely on the integration of large-scale neural networks that connect the cerebral cortex and subcortical structures. Emerg...

Dysfunctional resting state network connectivity predicts postoperative delirium after major surgery.

BACKGROUND: Postoperative delirium is associated with increased morbidity, mortality, future cognitive decline, or dementia. Understanding the neural ...

Humane Intelligence in Geropsychiatric Care: Relational Artificial Intelligence, Clinical Wisdom, and the Moral Grid Operational Index.

Artificial intelligence (AI) already influences how older adults are identified for services, supported between provider visits, and referred for care...

Artificial Intelligence and Its Application in the Oral Health Care for People with Disabilities: Toward Inclusive and Equitable Innovation.

This article introduces prosocial artificial intelligence (AI) as a transformative framework for addressing oral health disparities among people with ...

Interpretable machine learning for cognitive impairment screening: Development and external validation of a clinical prediction model based on NHANES data.

BACKGROUND: Cognitive impairment in older adults poses a growing public health challenge, yet accessible screening tools remain limited. We aimed to d...

Machine Learning-Enhanced Hyperspectral Raman Imaging for Label-Free Molecular Atlas of Alzheimer's Brain.

Label-free molecular imaging that enables the construction of a molecular atlas of biological tissues is vital for understanding complex physiological...

Early Alzheimer's disease classification via structure and feature-based graph attention network from multi-center data.

With the increasing Alzheimer's disease (AD) prevalence, morbidity, and mortality, its early diagnosis is particularly important. The multi-modal data...

Smiling difficulties in Alzheimer's disease linked to reduced nucleus accumbens and pallidum brain volume: Deep learning insights.

Patients tend to lose the ability to smile during the course of dementia. However, such impairments have rarely been reported, likely due to challenge...