Dementia

From prediction to mechanism: Explainable AI uncovers plasma and CSF proteomic signatures of Alzheimer's disease.

Alzheimer's disease (AD) plasma and cerebrospinal fluid (CSF) proteomics can distinguish AD from cognitively normal controls, but the generalizability of machine learning performance and the recurrence of biological signals across datasets require cautious interpretation. We developed an explainable artificial intelligence framework spanning two fluids and four ADNI proteomic datasets, covering 20...

A computational model to describe multi-regional brain architecture during neurodegeneration in Alzheimer's disease.

We previously proposed an MRI-based machine learning model to describe the mesoscopic architecture of the human brain to aid in classifying subjects as having non-AD related pathology (nADrp) or AD related pathology (ADrp), including mild cognitive impairment (MCI) and Alzheimer's disease (AD). The method, developed on data from patients scanned at 1.5T showed high performance, but did not general...

Intelligent fall risk prediction and real-time warning system for elderly care based on multimodal deep learning and wearable sensor fusion.

Falls remain a leading cause of injury-related morbidity and mortality among adults aged 65 and older, and these human and economic costs keep rising ...

ActiTect: a generalizable machine learning pipeline for REM sleep behavior disorder screening through standardized actigraphy.

Isolated rapid eye movement sleep behavior disorder (iRBD) is a major prodromal marker of α-synucleinopathies, often preceding the clinical onset of P...

The landscape of knowledge graph and LLM-augmented knowledge graph applications in dementia caregiving support: a scoping review.

BACKGROUND AND OBJECTIVES: Dementia's rising prevalence places an immense burden on caregivers. Knowledge Graphs (KGs) and Large Language Model (LLM)-...

Clinically reported covert cerebrovascular disease and risk of neurological disease: a whole-population cohort of 367 988 people using natural language processing.

BACKGROUND: The relevance of covert cerebrovascular disease (CCD) in practice is uncertain, partly because estimation of risk in whole clinical popula...

Hybrid deep learning model for brain age prediction using time-distributed convolutional and bidirectional LSTM networks.

Brain age prediction has gained significant attention due to its strong correlation with neurological and cognitive disorders. The discrepancy between...

Alzheimer's disease-cancer research (inception to 2025): trends, themes, translational pathways, and insights from highly cited studies.

Alzheimer's disease-cancer research (ADCR) has gained increasing attention due to paradoxical epidemiological associations and shared yet oppositely r...

Multi-scale Radiomic Fingerprint: Quantifying Spatial Changes in Biology.

Traditional radiomic studies build texture matrices using single-voxel increments. However, useful information may emerge when radiomic features are i...

Slow-wave-modulated high-frequency oscillations reveal early network abnormalities in pre-pathological 5XFAD mice.

Alzheimer's disease (AD) is characterized by progressive disruption of large-scale neural networks, leading to abnormal brain oscillatory activity, ye...

Disparities in Engagement with an Artificial Intelligence-Based Chat Intervention Post-appendectomy.

PURPOSE: Artificial intelligence (AI)-based text messaging, or "chat," in post-appendectomy care has been shown to decrease preventable emergency depa...

Streetview greenspace types and dementia risk in older adults: The Multi-Ethnic Study of Atherosclerosis.

BACKGROUND: Greenspace has been associated with lower dementia risk but most studies have used satellite-derived measures that cannot distinguish vege...

Caregiver Preferences for AI-Supported Telemedicine in Pediatric Palliative Care: A Discrete Choice Experiment.

BackgroundAsynchronous telemedicine may support home-based pediatric palliative care (PPC) by improving access to professional guidance and reducing c...

A large dataset of brain imaging linked to health systems data: curation and access to a whole system national cohort from NHS Scotland.

We present the design and implementation of a data curation framework to generate a large-scale clinical brain imaging dataset suitable for artificial...

Dementia transition in early cognitive decline trajectories (DETECT) study: a prospective longitudinal study protocol.

BACKGROUND: Mild cognitive impairment is widely recognized as a high-risk state associated with a progression to dementia. Although previous studies h...

Machine Learning-Enhanced Ultrasensitive Immuno-CRISPR Array Facilitates Early Diagnosis of Alzheimer's Disease by Detecting Multiple Plasma Biomarkers.

Early and accurate diagnosis of Alzheimer's disease (AD) remains a significant challenge due to the multifactorial and dynamic nature of its pathology...

Evolution of Chatbots as an Educational and Supportive Digital Intervention for Family Caregivers of People With Dementia: Protocol for a Systematic Integrative Review.

BACKGROUND: Most people with dementia reside in the community and are cared for by family members. Family caregivers play an essential role in support...

Scan-wise generalized PET denoising with contrastive adversarial learning.

Objective.Deep learning has significantly advanced low-count positron emission tomography (PET) denoising. However, models trained on specific distrib...

Digital Resources for Traversing the Landscape of Human Aging: Databases, Key Computational Strategies, and Artificial Intelligence.

By 2050, nearly 20% of the global population will exceed 60 years old, experiencing compromised physiological and functional abilities, neurological d...

Prevalence and a LASSO-derived prediction model for screening-positive mild cognitive impairment among older adults in Wuhan.

This study aimed to investigate the prevalence of screening-positive mild cognitive impairment (s-MCI) and to develop a parsimonious prediction model ...