Latest AI and machine learning research in alzheimer's disease for healthcare professionals.
OBJECTIVES: Building on innovations for autism detection-where artificial intelligence (AI)-based models monitor clinical data within electronic health records-this study evaluates the context for clinical decision support (CDS) deployment and identifies design preferences. MATERIALS AND METHODS: This observational study utilized contextual inquiry to elicit perspectives from 8 clinicians and twen...
BackgroundAccurate quantification of standardized uptake value ratio (SUVR) in amyloid PET is essential for Alzheimer's disease (AD) diagnosis but typically requires MRI-based segmentation due to subtle uptake differences between gray and white matter.ObjectiveThis study aimed to develop and validate a 3-dimensional deep learning model capable of segmenting these tissues directly from PET images t...
BACKGROUND AND OBJECTIVES: To examine the ethical considerations related to artificial intelligence technologies in dementia across diagnostic, manage...
Alzheimer's disease (AD) disrupts brain function through cell type-specific transcriptomic and epigenomic alterations, yet the contribution of three-d...
This article offers a comprehensive analysis of the representations of nursing and healthcare in contemporary and classic dystopian literature and fil...
Sleep-wake disturbances commonly occur in Alzheimer's disease (AD). However, the precise mechanisms underlying the breakdown of the circadian gene net...
PURPOSE OF REVIEW: Heart failure (HF) is increasingly understood not as a single, uniformly treated diagnosis but as a heterogeneous syndrome requirin...
BACKGROUND: Enlarged perivascular spaces (ePVS) are a marker of cerebral small vessel disease, potentially reflecting reduced waste clearance. Because...
BackgroundAccurate, non-invasive prediction of cerebral amyloid-β (Aβ) pathology in mild cognitive impairment (MCI) remains challenging yet critical f...
PURPOSE: Early detection of cognitive decline is essential for timely diagnosis and treatment. This study aimed to evaluate whether upper-limb movemen...
Predicting the risk of Alzheimer's disease (AD) is fundamental for early-stage intervention. Nevertheless, most methods struggle to extract multi-omic...
Examining sleep patterns in relation to chronological ageing and dementia can provide insights for risk screening. Integrating predictive models with ...
Histological analysis is essential for understanding disease pathology and the microenvironment, particularly in Alzheimer's disease (AD), characteriz...
Apoptosis and pyroptosis-mediated neuronal death represent major pathogenic mechanisms underlying Alzheimer's disease (AD). Given the potential crosst...
BACKGROUND: Distinguishing individuals with cognitive decline (CD), including early Alzheimer's disease, from cognitively normal (CN) individuals is e...
The instability of atherosclerotic plaques, particularly intraplaque hemorrhage (IPH), drives life-threatening cardiovascular events, a process in whi...
Alzheimer's disease (AD) is a complex neurodegenerative disorder which is multifactorial in nature. Some of its characteristics are slow cognitive dec...
Alzheimer's disease (AD) is a progressive neurodegenerative disorder, with mild cognitive impairment (MCI) as its prodromal stage. Accurate MCI conver...
Dual specificity tyrosine phosphorylation-regulated kinase 1A (DYRK1A), a member of the CMGC kinase family, regulates diverse cellular processes and i...
Neurodegenerative diseases such as Alzheimer's disease (AD) and frontotemporal dementia (FTD) exhibit substantial biological and clinical heterogeneit...