Dementia

Multimodal radiomics of precisely segmented hippocampal subfields: Iron deposition and structural biomarkers for early diagnosis of Alzheimer's disease.

Profiling imaging biomarkers of prodromal Alzheimer's disease (AD) against AD dementia may aid earlier diagnosis, yet approaches jointly capturing iron-related pathology and hippocampal subfield heterogeneity remain scarce. We developed a hippocampal-subfield multimodal radiomics framework integrating quantitative susceptibility mapping (QSM) and 3D T1-weighted MRI. A primary cohort of 92 particip...

Towards Cognitive Impairment Screening in Elderly Communities with Audio-Visual Modal Disentangled Representation Learning.

Alzheimer's disease (AD) is pressing global health concerns, for which early diagnosis is critical to effective intervention. However, conventional approaches, including neuropsychological assessments and neuroimaging techniques, are resource-intensive and impractical for community-level screening. In contrast, artificial intelligence-driven behavioral analyses, including speech pattern and facial...

A deep joint-learning proteomics model for diagnosis of six conditions associated with dementia.

Co-pathology is a common feature of neurodegenerative diseases that complicates diagnosis, treatment and clinical management. However, sensitive, spec...

Multi-Omics Analysis for Identifying Glial Dysfunction-Associated Genes as Therapeutic Targets and Drug Candidates in Alzheimer's Disease.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by cognitive decline, amyloid-β plaques, and neurofibrillary tangle...

AI-enabled digital phenotyping for Alzheimer's disease: a review of multimodal sensor integration and symptom trajectories.

Cross entropy gradient analysis for Alzheimer's disease assessment.

BackgroundAlzheimer's disease (AD) involves progressive cognitive decline associated with disrupted coordination and information exchange across brain...

Polygenic and polysocial risk scores in post-type 2 diabetes dementia: Risk stratification and predictive modeling in the UK Biobank cohort.

BackgroundDementia is a common complication of type 2 diabetes mellitus (T2DM), influenced by both genetic susceptibility and social disadvantages. Wh...

Artificial intelligence for battlefield triage in large-scale combat operations: Opportunities, limits, and ethical considerations.

Large-scale combat operations (LSCOs) impose major constraints on battlefield medical systems, combining sustained casualty inflow, degraded communica...

Comparative Mortality Risk of Aripiprazole, Olanzapine, Quetiapine, and Risperidone in Alzheimer's Disease: A Real‑World Retrospective Cohort Study with Treatment Effect Heterogeneity Analysis.

BACKGROUND: Second-generation antipsychotics (SGAs) are frequently used off-label to manage behavioral symptoms in Alzheimer's disease (AD), despite o...

Circulatory dietary and gut-derived metabolites predict early cognitive decline.

INTRODUCTION: A key component of disease prevention is the identification of at-risk individuals. Microbial dysbiosis in the early stages of cognitive...

Quantitative pathology and APOE genotype reveal dementia risk and progression in Lewy body disease.

Dementia in Lewy body diseases (LBD) is common and arises through heterogeneous and incompletely understood pathways. Evidence suggests contributions ...

The Deep Learning Revolution in Neuroimaging: Insights from a Bibliometric Analysis (2014-2024).

This paper presents a bibliometric analysis of the fast-growing area of deep learning in neuroimaging. Using data from the Scopus database, we analyze...

Closed-loop transcranial ultrasound stimulation based on NREM and REM sleep for bidirectional modulation of sleep neural oscillation and memory.

Sleep plays an important role in memory integration. Closed-loop physical stimulation during rapid eye movement (REM) or non-rapid eye movement (NREM)...

Parvalbumin Neuron-Targeted Loss of Alzheimer's Disease Risk Gene BIN1 Is Insufficient to Drive Cognitive or Network Excitability Changes.

Bridging integrator 1 (BIN1) is one of the strongest genetic risk factors for Alzheimer's disease (AD), yet its function in the brain and role in AD r...

Screening for Alzheimer's disease in the community using an AI-driven screening platform: design of the PREDICTOM study.

BACKGROUND: Recent developments in physiological, imaging and digital biomarkers combined with the approval of new disease-modifying drugs against Alz...

Enriched resting-state EEG prediction of cognitive decline in prodromal Alzheimer's disease: a machine-learning approach.

OBJECTIVE: We evaluated the accuracy of standard machine learning (ML) algorithms in predicting 1-year cognitive decline in Alzheimer's disease patien...

Ultrastructural Evidence of Altered Dendritic Morphology in the Prefrontal Cortex of Alzheimer's Model Rats.

Alzheimer's disease (AD) is a neurodegenerative disorder with synaptic pathology as a core theme in aging-related research. Conventional imaging and l...

Multimodal AI for Alzheimer Disease Diagnosis: Systematic Review of Datasets, Models, and Modalities.

BACKGROUND: Early detection of Alzheimer disease (AD) is essential for timely intervention; yet, diagnostic performance varies widely across modalitie...

Research on Alzheimer's Disease Risk Assessment Models and Biomarker Screening Based on Bioinformatics Analysis and Machine Learning Algorithms.

INTRODUCTION: Alzheimer's Disease (AD) is among the most prevalent neurodegenerative disorders globally, yet effective early diagnostic strategies rem...

Emerging Roles of Small-molecule Derivatives in Modulating Neurodegenerative Pathways: From Molecular Targets to Therapeutic Applications.

Neurodegenerative disorders such as Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and Huntington's disease involve progress...