Latest AI and machine learning research in alzheimer's disease for healthcare professionals.
Explainable Artificial Intelligence (XAI) is gaining popularity in early diagnosis and monitoring of dementia. Herein, we recommend the incorporation of the National Institute of Mental Health's Research Domain Criteria (NIMH-RDoC) framework with XAI-informed diagnostic protocols to help establish diagnosis at early stages of Alzheimer's disease (AD). RDoC has a dimensional structure that extends ...
Verbal fluency tasks are ubiquitous in mild cognitive impairment (MCI) screenings. Yet, their assessment is traditionally limited to valid response counts. This subjective approach constrains analysis to univariate methods and overlooks which semantic memory dimensions are affected, introducing human bias while limiting informativeness. We tackled these gaps with a novel automated framework. Ninet...
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...
Alzheimer's disease (AD) plasma and cerebrospinal fluid (CSF) proteomics can distinguish AD from cognitively normal controls, but the generalizability...
Aging is asynchronous across cells and organs. Here we tested whether plasma proteomics can be used to analyze cell type-specific aging. From analyses...
We previously proposed an MRI-based machine learning model to describe the mesoscopic architecture of the human brain to aid in classifying subjects a...