Dementia

A 60-second interpretable voice model for early dementia screening.

Early detection of cognitive impairment in assisted living is hindered by time-intensive tools like the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA). We present a 60-second voice-based screening model that analyzes picture descriptions to estimate dementia risk. While recent deep learning approaches have shown promise on similar tasks, their lack of interpretab...

AI and Chatbot-Supported Interventions for Physical Activity and Obesity-Related Lifestyle Behaviors: Scoping Review With Attention to Family Involvement.

BACKGROUND: AI-enabled chatbots and related conversational systems can facilitate human-computer interaction through natural language, personalization, and automated support. In pediatric health promotion, these tools have the potential to provide scalable and flexible approaches to support physical activity (PA) and related lifestyle behavior change within family contexts. However, evidence regar...

Patient and Family Perspectives on Generative AI Tools in Rare Diseases: Exploratory Mixed Methods Online Survey.

BACKGROUND: Generative artificial intelligence (GenAI) tools are widely accessible to the public, who are engaging with them for a wide range of healt...

Development and Validation of a Machine Learning Classification Algorithm for Differentiating Frontotemporal Dementia from Alzheimer's Disease Using Automated Brain MRI Volumetry.

BACKGROUND AND PURPOSE: Frontotemporal dementia (FTD) is characterized by frontal and anterior temporal lobe atrophy and progressive changes in behavi...

Understanding end-user contexts and identifying design preferences of an artificial intelligence-based clinical decision support tool for early autism detection.

OBJECTIVES: Building on innovations for autism detection-where artificial intelligence (AI)-based models monitor clinical data within electronic healt...

MRI-free amyloid PET quantification using a deep learning model and white matter reference.

BackgroundAccurate quantification of standardized uptake value ratio (SUVR) in amyloid PET is essential for Alzheimer's disease (AD) diagnosis but typ...

Ethical Considerations of Artificial Intelligence in Dementia Research: A Review of Reviews.

BACKGROUND AND OBJECTIVES: To examine the ethical considerations related to artificial intelligence technologies in dementia across diagnostic, manage...

Single-cell multiomics connects 3D genome and transcriptome alterations in Alzheimer's disease.

Alzheimer's disease (AD) disrupts brain function through cell type-specific transcriptomic and epigenomic alterations, yet the contribution of three-d...

Nursing as social control: An ethical perspective on care in dystopian contexts.

This article offers a comprehensive analysis of the representations of nursing and healthcare in contemporary and classic dystopian literature and fil...

Mathematical mapping of circadian genes in Alzheimer's disease.

Sleep-wake disturbances commonly occur in Alzheimer's disease (AD). However, the precise mechanisms underlying the breakdown of the circadian gene net...

A comparative evaluation of multiple enlarged perivascular space segmentation tools.

BACKGROUND: Enlarged perivascular spaces (ePVS) are a marker of cerebral small vessel disease, potentially reflecting reduced waste clearance. Because...

A multimodal machine learning model integrating plasma biomarkers and MRI metrics for non-invasive prediction of amyloid-β pathology in mild cognitive impairment.

BackgroundAccurate, non-invasive prediction of cerebral amyloid-β (Aβ) pathology in mild cognitive impairment (MCI) remains challenging yet critical f...

Early Detection of Cognitive Impairment Using Time-Frequency Analysis of Fine Motor Accelerometry.

PURPOSE: Early detection of cognitive decline is essential for timely diagnosis and treatment. This study aimed to evaluate whether upper-limb movemen...

Alzheimer's disease risk prediction via perceptual deformable attention generative adversarial network with large foundation models.

Predicting the risk of Alzheimer's disease (AD) is fundamental for early-stage intervention. Nevertheless, most methods struggle to extract multi-omic...

Real-world deployment of remote sleep monitoring technologies reveals distinct patterns associated with cognitive decline.

Examining sleep patterns in relation to chronological ageing and dementia can provide insights for risk screening. Integrating predictive models with ...

DeepPlaque: a scalable multimodal platform for Aβ pathology and cell analysis in Alzheimer's disease.

Histological analysis is essential for understanding disease pathology and the microenvironment, particularly in Alzheimer's disease (AD), characteriz...

Integrated bioinformatics and experimental analysis identify apoptosis- and pyroptosis-related hub genes as candidate diagnostic biomarkers in Alzheimer's disease.

Apoptosis and pyroptosis-mediated neuronal death represent major pathogenic mechanisms underlying Alzheimer's disease (AD). Given the potential crosst...

Feature integration of [18F]FDG PET brain imaging using deep learning for sensitive cognitive decline detection.

BACKGROUND: Distinguishing individuals with cognitive decline (CD), including early Alzheimer's disease, from cognitively normal (CN) individuals is e...

Neural network-enhanced investigation of ferroptosis and druggability in early-onset alzheimer's disease.

Alzheimer's disease (AD) is a complex neurodegenerative disorder which is multifactorial in nature. Some of its characteristics are slow cognitive dec...

Brain Region-Centered MultiModal Hypergraph Fusion for MCI Conversion Prediction.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder, with mild cognitive impairment (MCI) as its prodromal stage. Accurate MCI conver...