Dementia

Predictive value of the Alzheimer polygenic risk score on cognitive decline in patients with mild cognitive impairment and Alzheimer's disease dementia.

BACKGROUND: Polygenic risk scores for Alzheimer's disease (AD-PRS) are widely used to estimate genetic susceptibility to AD, but their relationship with the rate of cognitive decline (CD) after clinical onset remains insufficiently characterized. OBJECTIVES: To examine the association between AD-PRS and longitudinal CD across the AD spectrum and to evaluate the predictive contribution of individua...

Integrative machine learning and single-nucleus transcriptomics reveal MAPK-centered neuronal responses underlying the potential Alzheimer's disease risk of GenX.

Hexafluoropropylene oxide-dimer acid (GenX or HFPO-DA) is a novel per- and polyfluoroalkyl substance developed as a replacement for legacy compounds, yet its potential neurotoxic effects remain poorly understood. In this study, we combined bibliometric profiling, in silico target prediction, in vivo behavioral assessments, single-nucleus RNA sequencing (snRNA-seq), network biology, machine learnin...

Bidirectional cross-modal attention with adaptive gating for multimodal alzheimer's disease classification.

Alzheimer's disease (AD) is a neurodegenerative disorder, and mild cognitive impairment (MCI) represents a transitional stage between AD and cognitive...

Bridging the islands of innovation: A machine-assisted Semantic-Bibliometric review and conceptual roadmap for closed-loop digital dementia care.

BACKGROUND: Artificial intelligence (AI), extended reality (XR), and socially assistive robotics (SAR) are each advancing Alzheimer's disease (AD) res...

Unraveling the molecular Nexus of Alzheimer's Disease and HIV encephalitis: The role of cellular senescence and transcriptional regulation.

Alzheimer's disease (AD) and HIV-associated neurocognitive disorder (HAND) share progressive cognitive decline. Their common molecular mechanisms rema...

Somalia's lifeline: Digitalization and AI.

Somalia's fragile health system, strained by decades of conflict, climate shocks, and persistently low immunization coverage, remains dangerously vuln...

Development and validation of machine learning models to predict risk of undiagnosed dementia using healthcare claims and electronic health record data.

BackgroundApproximately half of people living with Alzheimer's disease and related dementias are undiagnosed.ObjectiveTo develop and validate algorith...

From voxel discovery to regional interaction: A multi-level interpretable framework for Alzheimer's disease diagnosis.

Alzheimer's disease (AD) is an irreversible neurodegenerative disorder where early diagnosis serves as the only viable window for effective interventi...

A preliminary analysis of relationship between dual-task gait and age-related cognitive ability using neural network models.

BackgroundAging causes declines in cognitive and motor functions, often manifested in altered gait. Dual-task gait is a sensitive marker for early fun...

Rational drug design for Alzheimer's disease: from approved therapies to next-generation clinical candidates and AI-guided innovation.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by multifactorial pathology, including amyloid-β (Aβ) aggregation, ...

Integrative machine learning reveals telomere-associated gene modules reflecting neuronal dysregulation in Alzheimer's disease.

BackgroundTelomere dysfunction contributes to cellular aging and genome instability, but telomere-associated transcription in Alzheimer's disease (AD)...

Quantifying generalization error in machine learning prediction of cognitive decline.

BACKGROUND: Predicting cognitive decline as a continuum, from healthy age-related decline to mild cognitive impairment and dementia, enables more prec...

Artificial intelligence-based 3D segmentation of tangle-associated TDP-43 in neurodegeneration.

TAR DNA-binding protein 43 (TDP-43) inclusions are often associated with hyperphosphorylated tau, thus neurofibrillary tangles as the hallmark of Alzh...

Effect of genetic factors on [18F]FDG PET metabolic phenotypes in dementia with Lewy bodies.

BACKGROUND: Neuroimaging with [18F]FDG PET can support the diagnosis of Dementia with Lewy Bodies (DLB), but it remains unclear how genetic factors in...

Data-driven trajectories of atrophy explain clinical heterogeneity across Lewy body diseases.

BACKGROUND: Lewy body diseases (LBD) collectively share α-synuclein Lewy pathology, yet present wide clinical heterogeneity, with overlapping motor an...

miRNA-mRNA Interaction Network Analysis in Alzheimer's Disease for Biomarker Discovery.

Alzheimer's disease (AD) is a complex neurodegenerative disorder characterized by widespread dysregulation of gene expression and regulatory pathways....

Two-stage deep learning framework for the restoration of incomplete-ring PET images.

Positron Emission Tomography (PET) is an important molecular imaging tool widely used in medicine. Traditional PET systems rely on complete detector r...

A Generalized Approach to Solving Deep Learning-Based Quantitative Susceptibility Mapping and Quantitative Blood Oxygen Level Dependent Magnitude (QSM + qBOLD or QQ) for Oxygen Extraction Fraction (OEF) Mapping Across Diverse Acquisition Schemes.

PURPOSE: QQ, a recently proposed oxygen extraction fraction (OEF) mapping technique combining quantitative susceptibility mapping (QSM) and quantitati...

Developing an integrated algorithm to support autism diagnostic decisions: Model performance and statistical fairness.

BACKGROUND: Best practices in diagnosing autism spectrum disorder require an expert diagnostician to integrate multiple sources of information, includ...

Super-Resolution of Through-Plane Undersampled MRIs in Alzheimer's Disease Diagnosis.

Alzheimer's disease is a complex neurodegenerative disorder and the leading cause of dementia worldwide. Learning-based techniques applied to magnetic...