Dementia

Amyloid-β and phosphorylated-tau accumulation in retrosplenial cortex of young Alzheimer's disease model: Impact on network activity.

BackgroundThe retrosplenial cortex (RSC) is a cortical area that functions as a key component of the...

Modeling Zero-Dose Children in Ethiopia: A Machine Learning Perspective on Model Performance and Predictor Variables.

BACKGROUND: Despite progress in childhood vaccination, many children in low- and middle-income count...

Developing a Multimodal Screening Algorithm for Mild Cognitive Impairment and Early Dementia in Home Health Care: Protocol for a Cross-Sectional Case-Control Study Using Speech Analysis, Large Language Models, and Electronic Health Records.

BACKGROUND: Mild cognitive impairment and early dementia (MCI-ED) are frequently unrecognized in rou...

Multimodal fusion and explainability of artificial intelligence models in Alzheimer's Disease detection.

The integration of multimodal data has emerged as a powerful strategy for enhancing the accuracy and...

Multi-dimensional EEG analysis reveals distinct neurophysiological patterns in Alzheimer's and frontotemporal dementia.

AI-driven framework for accurate detection of Alzheimer's disease in EEG.

Alzheimer's Disease (AD) is a rapidly growing neurodegenerative disorder that severely impairs cogni...

Investigating the Utility of Explainable Artificial Intelligence for Neuroimaging-Based Dementia Diagnosis and Prognosis.

Artificial intelligence and neuroimaging enable accurate dementia prediction but often involve 'blac...

Biases in an artificial intelligence image-generator's depictions of healthy aging and Alzheimer's.

OBJECTIVE: This content analysis study investigates potential biases in image generation by 2 artifi...

Artificial Intelligence-Assisted Clinical Decision Support System in Telemedical Wound Care: A Randomized Controlled Trial.

BACKGROUND: Chronic wounds are increasingly prevalent due to an aging population and rising chronic ...

Functional and Clinical: An Explainable Deep Learning Model for Multimodal Alzheimer's Disease Classification.

PURPOSE: Functional magnetic resonance imaging (fMRI) and deep learning models can classify Alzheime...

Towards a speech-based digital biomarker for cognitive impairment: speech as a proxy for cognitive assessment.

With the growing prevalence of cognitive decline in ageing populations, accessible and scalable scre...

Alzheimer's disease diagnosis support for brain perfusion SPECT scans in a real-world clinical cohort.

BackgroundDementia diagnosis is challenging and often delayed. Brain imaging techniques such as sing...

The role of dentists in the recognition of neurodegenerative and systemic conditions with neurological involvement.

Dentists are often the first healthcare providers to observe subtle orofacial and behavioral changes...

Molecular features of human pathological tau distinguish tauopathy-associated dementias.

In Alzheimer's disease (AD), pathological tau protein shows a progressive accumulation of post-trans...

Development and Validation of a Machine Learning Model for Dementia Staging in a Heterogeneous Cognitive Impairment Cohort Using Multimodal Features.

RATIONALE AND OBJECTIVES: With the emergence of disease-modifying therapies, precise staging of deme...

Towards the development of a management protocol for subjective cognitive decline: Insights from a cross-sectional and longitudinal analysis of multimodal data from a memory clinic.

BackgroundSubjective cognitive decline (SCD) represents the first early symptomatic stage of Alzheim...

Ethical Knowledge, Challenges, and Institutional Strategies Among Medical AI Developers and Researchers: Focus Group Study.

BACKGROUND: As artificial intelligence (AI) becomes increasingly embedded in clinical decision-makin...

Mechanisms and biomarkers of poststroke cognitive impairment.

Poststroke cognitive impairment is a common neurological complication in stroke patients, characteri...

Dementia severity index: A threshold-based approach to classifying dementia levels using resting state EEG.

BACKGROUND: Alzheimer's Disease (AD) and FrontoTemporal Dementia (FTD) are dementia conditions that ...

Converse or reverse? Machine-learning modeling for disease progression: A study based on Alzheimer's disease continuum cohort.

INTRODUCTION: Longitudinal trajectories from healthy aging to Mild Cognitive Impairment and Alzheime...

Generating synthetic MRI scans for improving Alzheimer's disease diagnosis.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder and the leading cause of dement...