Alzheimer's Disease

Perspectives and Experiences of Family Caregivers Using Supportive Mobile Apps in Dementia Care: Meta-Synthesis of Qualitative Research.

BACKGROUND: Supportive mobile apps are effective tools for family caregivers of persons with dementia to obtain online information and psychological support. Nevertheless, details about the experiences of family caregivers of persons with dementia using mobile apps are limited.

Alzheimer's disease digital biomarkers multidimensional landscape and AI model scoping review.

As digital biomarkers gain traction in Alzheimer's disease (AD) diagnosis, understanding recent advancements is crucial. This review conducts a bibliometric analysis of 431 studies from five online databases: Web of Science, PubMed, Embase, IEEE Xplore, and CINAHL, and provides a scoping review of 86 artificial intelligence (AI) models. Research in this field is supported by 224 grants across 54 d...

Discovery of Novel Anti-Acetylcholinesterase Peptides Using a Machine Learning and Molecular Docking Approach.

OBJECTIVE: Alzheimer's disease poses a significant threat to human health. Currenttherapeutic medicines, while alleviate symptoms, fail to reverse the...

Optimizing Dementia Diagnosis Through Distance-Correlation Feature Space and Dimensionality Reduction.

The reduction of dimensionality in machine learning and artificial intelligence problems constitutes a pivotal element in the simplification of models...

Massively parallel genetic perturbation suggests the energetic structure of an amyloid-β transition state.

Amyloid aggregates are pathological hallmarks of many human diseases, but how soluble proteins nucleate to form amyloids is poorly understood. Here, w...

An ensemble-based 3D residual network for the classification of Alzheimer's disease.

Alzheimer's disease (AD) is a common type of dementia, with mild cognitive impairment (MCI) being a key precursor. Early MCI diagnosis is crucial for ...

Detecting label noise in longitudinal Alzheimer's data with explainable artificial intelligence.

Reliable classification of cognitive states in longitudinal Alzheimer's Disease (AD) studies is critical for early diagnosis and intervention. However...

Early Alzheimer's Detection Through Voice Analysis: Harnessing Locally Deployable LLMs via , a privacy-preserving diagnostic system.

Diagnosing Alzheimer's Disease (AD) early and cost-effectively is crucial. Recent advancements in Large Language Models (LLMs) like ChatGPT have made ...

SLR: A Modified Logistic Regression Model with Sinkhorn Divergence for Alzheimer's Disease Classification.

Logistic regression is a widely used model in machine learning, particularly as a baseline for binary classification tasks due to its simplicity, effe...

An AI-assisted fluorescence microscopic system for screening mitophagy inducers by simultaneous analysis of mitophagic intermediates.

Mitophagy, the selective autophagic elimination of mitochondria, is essential for maintaining mitochondrial quality and cell homeostasis. Impairment o...

Dynamically weighted graph neural network for detection of early mild cognitive impairment.

Alzheimer's disease (AD) is a prevalent neurodegenerative disease that primarily affects the elderly population. The early detection of mild cognitive...

Towards Real-World Dementia Care: Encouraging Activity Engagement Using an Intelligent Humanoid Robot.

Humanoid social assistive robotics (SARs) can promote activity engagement for older adults living with dementia. Few studies, however, evaluate the ca...

Development of a neural network-based risk prediction model for mild cognitive impairment in older adults with functional disability.

BACKGROUND: Mild Cognitive Impairment (MCI) is a critical transitional stage between normal aging and Alzheimer's disease, and its early identificatio...

Role of astroglia and microglia in Alzheimer's disease and multiple therapeutic interventions.

Alzheimer's disease (AD) is characterized by deposition of amyloid-β (Aβ) and neurofibrillary tangles (NFTs) formed by aggregates of hyperphosphorylat...

Selection, visualization, and explanation of deep features from resting-state fMRI for Alzheimer's disease diagnosis.

Despite the remarkable achievements of deep learning networks in analyzing neuroimaging data for various tasks linked to brain functions and disorders...

Integrative single-cell and cell-free plasma RNA transcriptomics identifies biomarkers for early non-invasive AD screening.

INTRODUCTION: Data-driven omics approaches have rapidly advanced our understanding of the molecular heterogeneity of Alzheimer's disease (AD). However...

In Silico Screening of Small Molecule Inhibitors for Amyloid-β Aggregation.

The self-aggregation of amyloid-β (Aβ) into fibrils is a hallmark of Alzheimer's disease (AD). Inhibition of Aβ aggregation with small molecule compou...

The Innovation Paradox in Emerging Pharmaceutical Markets: Barriers and Opportunities for Sustainable Development.

Emerging pharmaceutical markets like Brazil, India, and China have seen significant growth due to rising medication demand, expanding middle-class acc...

Distinct brain atrophy progression subtypes underlie phenoconversion in isolated REM sleep behaviour disorder.

BACKGROUND: Synucleinopathies include a spectrum of disorders varying in features and severity, including idiopathic/isolated REM sleep behaviour diso...

Operationalizing postmortem pathology-MRI association studies in Alzheimer's disease and related disorders with MRI-guided histology sampling.

Postmortem neuropathological examination, while the gold standard for diagnosing neurodegenerative diseases, often relies on limited regional sampling...