Alzheimer's Disease

The emerging role of oligodendrocytes in Alzheimer's disease: Integrating bibliometric insights with molecular pathogenesis.

BackgroundOligodendrocytes (OLs) have received relatively limited attention in Alzheimer's disease (AD) research; however, recent studies highlight their significant role in AD pathology, particularly in neuroinflammation and myelin integrity.ObjectiveTo bibliometrically analyze oligodendrocyte research in AD.MethodsLiterature was retrieved from Web of Science and Scopus on July 8, 2025. CiteSpace...

Peripheral immune and vascular inflammatory signatures precede Alzheimer's disease onset: A serum proteomic study.

BackgroundNeuroinflammation plays an important role in the pathogenesis of Alzheimer's disease, but systemic immune alterations preceding clinical onset remain insufficiently characterized. Peripheral immune and vascular inflammatory processes may influence the central nervous system through endothelial dysfunction and blood-brain barrier vulnerability. Serum proteomics offers a minimally invasive...

Reliability and readability of AI platforms for pediatric health advice: a comparative analysis.

Large language models (LLMs) are increasingly used as a first-line source of information for everyday questions, including pediatric health guidance, ...

Multi-dimensional risk prediction and genetic architecture of aspiration pneumonia: a population-based analysis.

BACKGROUND: Aspiration pneumonia represents a significant but understudied cause of morbidity and mortality, particularly among aging populations with...

Gray matter brain age predicts cognitive outcome one year after ischemic stroke.

BackgroundPredicting post-stroke cognitive impairment (PSCI) remains challenging.ObjectiveThis study validated two brain age metrics-Gray Matter Brain...

A Voyage on Computer Aided Intelligent Algorithms for the Segmentation of Brain Tissues for Neurodisorder Diagnosis.

Neurodisorders pose a considerable burden to global health, frequently requiring early treatment and diagnosis to avoid irreversible cognitive and mot...

OCT-based optic neuropathy diagnosis using explainable and privacy-preserving machine learning.

Glaucoma shares similarities with neurodegenerative conditions like dementia, Parkinson's disease, and ischaemic optic neuropathy, which affect ocular...

Targeting Tau-Mitochondrial Crosstalk in Alzheimer's Disease: Integrative Multi-Omics and Artificial Intelligence-Driven Tools for the Development of Disease-Modifying Therapeutics.

Alzheimer's disease (AD) is a progressive neurodegenerative illness marked by cognitive impairment, synaptic dysfunction and neuronal death. Tau prote...

Identification and Validation of Glycosylation-Related Biomarkers in the Hippocampus for Alzheimer's Disease Diagnosis and Drug Repurposing.

As a crucial type of post-translational modification, glycosylation plays a fundamental role in maintaining cellular homeostasis and is closely associ...

EEG microstate dynamics and metal metabolism in Parkinson's disease dementia: an exploratory study with machine learning-assisted sensitivity analysis.

BACKGROUND: Electroencephalogram (EEG) microstates effectively characterise cognitive-related brain networks, and metal homeostasis is crucial for mai...

A Comprehensive Self-Medication Management System to Reduce Medication Errors Among People Living With Dementia: Mixed Methods Feasibility and Usability Study.

BACKGROUND: Medication adherence is a critical challenge for people living with dementia and their caregivers. Standard care relies on appropriate med...

Developments in the design and therapeutic applications of GSK3β inhibitors.

Glycogen synthase kinase-3β (GSK3β) has emerged as one of the most thoroughly validated therapeutic targets in modern drug discovery, with dysregulati...

AI-driven multimodal retinal imaging for early detection and risk stratification of vascular and neurodegenerative diseases.

Systemic vascular and neurodegenerative disorders are important causes of disability and death worldwide, mainly because of the late stage of diagnosi...

An Automated Framework and Medical Intelligent System for MRI-Based Alzheimer's Diagnosis Classification.

In the era of artificial intelligence (AI), Alzheimer's disease (AD) can be diagnosed through magnetic resonance imaging (MRI) at accurate times and w...

Dementia Prediction Using Gait Analysis and Machine Learning.

Dementia is a progressive neurodegenerative disorder affecting millions of people worldwide. Early prediction of dementia, especially during the mild ...

A Zoo of AI Transparency Indicators: What Do Users Want (and Need) in Hospitals?

Artificial intelligence (AI), whether generative, specialized, or agent-based, is increasingly integrated into the daily lives of many citizens. In he...

Predicting future dementia from routine clinical MRI and linked healthcare data.

BACKGROUND: Early identification of individuals at risk of dementia is essential for preventive care and timely enrolment into disease-modifying inter...

Artificial intelligence for detection and staging of Alzheimer's disease using retinal images.

This is a protocol for a Cochrane Review (diagnostic). The objectives are as follows: To determine the diagnostic accuracy of AI algorithm-based retin...

Decoding shared pathogenic networks of oxidative stress in neuropsychiatric disorders to prioritize multi-target therapeutics from natural products.

BACKGROUND: Neurodegenerative and psychiatric disorders, including Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD), and ...

Prediction of cognitive impairment through speech data analysis: A comparative evaluation of deep learning models.

BACKGROUND: The early detection of cognitive impairments, such as mild cognitive impairment (MCI) and Alzheimer's disease (AD), is essential for timel...