Dementia

Vision Transformer-Based Segmentation of Abdominal Subcutaneous and Visceral Fat on MRI.

The purpose of this study is to validate a deep learning-based vision transformer for automated quantification and segmentation of abdominal adipose tissue from T1-weighted MRI. This study included abdominal T1 MRI volumes from 107 participants (mean age, 49.9 years; 35 males, 72 females; BMI range, 18.2-49.6) who were midlife adults enrolled in a prospective study assessing the link between abdom...

Cognitive Reserve in rural and urban populations: Insights from two aging cohorts in southern India.

BACKGROUND: There are no Indian studies estimating Cognitive Reserve (CR) across rural and urban aging populations. METHODS: We estimated CR from two ongoing aging studies in rural (CBR-SANSCOG, n = 4459) and urban (CBR-TLSA, n = 663) southern India. We used years of education (YOE), job skill level (JSL), social network diversity (SND) and multilingualism (ML) as factors and assigned weights base...

Balancing Speed and Sensitivity: Echo-Planar Accelerated MRI for ARIA-H Screening in Anti-Aβ Therapeutics.

The recent advent of anti-amyloid-β monoclonal antibodies has introduced new demands for MRI-based screening of amyloid-related imaging abnormalities,...

Touch Modulates Gamma-Band Network Dynamics in the Infant Brain.

Touch is a foundational sensory modality in early development, playing a pivotal role in shaping social, emotional, and cognitive functions. This stud...

Contextualizing Socioeconomic Status Effects on Adolescent Brain Structure and Cognitive Skills: Evidence From the ABCD Study.

Youths' socioeconomic status (SES) correlates with academic, cognitive, and neural outcomes, partly driven by influences on the developmental environm...

GPND-AI NULISA: A 15-Protein AI classifier for diagnosis and co-pathology profiling across neurodegenerative diseases.

INTRODUCTION: Accurate clinical diagnosis of neurodegenerative diseases remains challenging, particularly when individuals have mixed pathologies. We ...

Bibliometric analysis of Alzheimer's and dementia research in Latin America.

INTRODUCTION: Dementia is increasing rapidly in Latin America and the Caribbean (LAC), but research output remains limited. Tracking publication trend...

Multimodal deep learning neuroimaging approach to enhance CT-based diagnosis of Alzheimer's disease.

Neuroimaging plays a critical role in the diagnosis of Alzheimer's disease (AD), with Magnetic Resonance Imaging (MRI) and Positron Emission Tomograph...

Discovering non-linear dynamics of miRNAs in Alzheimer's disease-related cognitive impairment: a cross-species approach with explainable machine learning.

BACKGROUND: MicroRNA (miRNA) biomarker studies in Alzheimer's disease (AD) typically assume monotonic relationships between expression levels and dise...

Interpretable Deep Survival Analysis of Alzheimer's Disease via Metabolic Genetic Variants.

BACKGROUND: Alzheimer's disease (AD) is a progressive neurodegenerative disease. Traditional models for estimating AD onset cannot capture nonlinear i...

Large Language Model and Pediatric Neurosurgery - A Neurosurgeon's Perspective on the Artificial Nervous System.

Large language models (LLMs) are rapidly transforming healthcare, yet their implications for pediatric neurosurgery remain underexplored. This narrati...

Interpretable multivariate survival models: Improving predictions for conversion from mild cognitive impairment to Alzheimer's disease via data fusion and machine learning.

Accurately predicting which individuals with mild cognitive impairment (MCI) will progress to Alzheimer's disease (AD) can improve patient care. This ...

Machine learning to diagnose, classify and predict phenoconversion in isolated REM sleep behavior disorder.

Rapid eye movement (REM) sleep behaviour disorder (RBD), particularly its idiopathic/isolated form (iRBD), is a prodromal marker for α-synucleinopathi...

Assessment of Large Language Models for Tracheostomy Care in Pediatrics: ChatGPT vs Claude.

INTRODUCTION: This study aimed to evaluate the accuracy, completeness, clarity, and relevance of responses provided by two freely available large lang...

Development of a community home-based dual-supplier cooperation care model for people with dementia based on an intelligent decision-assistance system: protocol of a 1-year randomised controlled trial in China.

INTRODUCTION: Dementia imposes significant care and financial burdens on families and countries globally. While high-quality home-based care is crucia...

Data-driven thresholds for standardized classification of severe Alzheimer's disease neuropathology using digital neuropathology.

Alzheimer's disease neuropathological changes (ADNC)-operationalized with semi-quantitative parameters-represent the consensus-based gold standard for...

Dementia screening with the Rivermead Behavioural Memory Test: A machine learning analysis.

BackgroundWith the advent of anti-amyloid-β monoclonal antibody therapies and the growing societal burden of dementia, early identification of Alzheim...

Brain PET in the era of anti-amyloid-β antibody therapy for Alzheimer disease.

Here the current and emerging roles of brain positron emission tomography (PET) in Alzheimer's disease (AD) in the era of anti-amyloid-β antibody ther...

Adaptive neighborhood aggregation graph neural network for early diagnosis of Alzheimer's disease.

Early diagnosis of Alzheimer's disease (AD) is crucial for timely intervention but remains challenging due to subtle and heterogeneous brain alteratio...

A frontotemporal dementia-like phenotype in schizophrenia: links to striatal dopamine and iron accumulation.

Some schizophrenia patients share characteristics with behavioral variant frontotemporal dementia (bvFTD) including gray matter volume (GMV) similarit...