Latest AI and machine learning research in dementia for healthcare professionals.
Alzheimer's disease (AD) is a progressive neurodegenerative disorder and the leading cause of dementia globally. Early prediction, prior to the onset of symptoms, is critical for enabling timely interventions. We present a machine learning framework that predicts future AD conversion in cognitively normal (CN) individuals using only structural magnetic resonance imaging (MRI) data. The approach le...
Alzheimer's disease (AD) is a progressive neurodegenerative disorder that severely affects memory, cognition, and behavioral functions, making early and accurate stage classification essential for timely clinical intervention and treatment planning. Conventional MRI-based diagnostic approaches are often limited by noise sensitivity, manual interpretation, and insufficient capability to model compl...
OBJECTIVES: Social determinants of health (SDOH) may improve Alzheimer's disease (AD) risk prediction by capturing upstream contextual risk beyond rou...
Identifying individuals at risk of Alzheimer's disease (AD), particularly in the preclinical and early stages, remains challenging. Although deep lear...
Explainable Artificial Intelligence (XAI) is gaining popularity in early diagnosis and monitoring of dementia. Herein, we recommend the incorporation ...
We introduce a quantitative pipeline for region-level explanations of an Alzheimer's prediction model using four post hoc explainable AI (XAI) methods...
OBJECTIVE: Reliable assessment of cerebral amyloid-β (Aβ) deposition is essential for the diagnosis and management of Alzheimer's disease (AD). This s...
Alzheimer's disease (AD) is a neurodegenerative disorder characterized by progressive cognitive impairment and memory loss. The underlying mechanisms ...
INTRODUCTION: Seizure control is the primary therapeutic goal in pediatric epilepsy, yet its multidimensional impact on health-related quality of life...
BACKGROUND: Although large language models (LLMs) show potential for patient education, their accuracy, usability, and comprehensibility lack validati...
BACKGROUND: Family caregivers experience conflicts in caring for people with Alzheimer's dementia (PWD; e.g., siblings disagreeing, advocating with pr...
Heparan sulfate (HS) proteoglycans are abundant, sulfation-patterned glycosaminoglycans on brain cells and the neurovascular unit that interact with a...
BackgroundThe systemic, metabolic, lifestyle factors have established associations with Alzheimer's disease (AD) through epidemiologic and AD-specific...
BACKGROUND: Everyday listening ability is essential for individual health and well-being. Age-related hearing loss (ARHL) is associated with reduced c...
The quick and accurate diagnosis of Alzheimer's disease (AD) and Frontotemporal Dementia (FTD) is a significant and unresolved challenge in clinical n...
UNLABELLED: Mild cognitive impairment (MCI) is a heterogeneous condition, with up to 40% of patients progressing to dementia within three years of cli...
PURPOSE: Amyloid (A) deposition represents a specific pathological hallmark of Alzheimer's disease (AD). Clinical diagnostic protocols frequently rely...
With the rapid development of artificial intelligence and medical image analysis, MRI-based automated diagnosis has provided an effective approach for...
IMPORTANCE: Cognitive impairment (CI) is often underdetected in primary care due to time and resource constraints. Passive analysis of clinical dialog...
BACKGROUND AND OBJECTIVES: Population aging and the rising prevalence of Alzheimer's Disease and Related Dementias (AD/ADRD) have created an urgent ne...