Neurology

Dementia

Latest AI and machine learning research in dementia for healthcare professionals.

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A multi-view learning approach with diffusion model to synthesize FDG PET from MRI T1WI for diagnosis of Alzheimer's disease.

INTRODUCTION: This study presents a novel multi-view learning approach for machine learning (ML)-bas...

Improving Multiscale Fuzzy Entropy Robustness in EEG-Based Alzheimer's Disease Detection via Amplitude Transformation.

This study investigates the effectiveness of amplitude transformation in enhancing the performance a...

AlzGenPred - CatBoost-based gene classifier for predicting Alzheimer's disease using high-throughput sequencing data.

AD is a progressive neurodegenerative disorder characterized by memory loss. Due to the advancement ...

Deep learning analysis of fMRI data for predicting Alzheimer's Disease: A focus on convolutional neural networks and model interpretability.

The early detection of Alzheimer's Disease (AD) is thought to be important for effective interventio...

A Machine learning classification framework using fused fractal property feature vectors for Alzheimer's disease diagnosis.

Alzheimer's disease (AD) profoundly affects brain tissue and network structures. Analyzing the topol...

Portable, low-field magnetic resonance imaging for evaluation of Alzheimer's disease.

Portable, low-field magnetic resonance imaging (LF-MRI) of the brain may facilitate point-of-care as...

Brain Network Classification for Accurate Detection of Alzheimer's Disease via Manifold Harmonic Discriminant Analysis.

Mounting evidence shows that Alzheimer's disease (AD) manifests the dysfunction of the brain network...

Psychosocial effects of a humanoid robot on informal caregivers of people with dementia: A randomised controlled trial with nested interviews.

BACKGROUND: Dementia rates are rising globally, impacting healthcare systems and society. The care o...

Developing a prediction model for cognitive impairment in older adults following critical illness.

BACKGROUND: New or worsening cognitive impairment or dementia is common in older adults following an...

Estimating global phase synchronization by quantifying multivariate mutual information and detecting network structure.

In neuroscience, phase synchronization (PS) is a crucial mechanism that facilitates information proc...

Time Efficiency and Ergonomic Assessment of a Robotic Wheelchair Transfer System.

: Caregivers experience high rates of occupational injuries, especially during wheelchair transfers,...

Use of Artificial Intelligence in Imaging Dementia.

Alzheimer's disease is the most common cause of dementia in the elderly population (aged 65 years an...

BPEN: Brain Posterior Evidential Network for trustworthy brain imaging analysis.

The application of deep learning techniques to analyze brain functional magnetic resonance imaging (...

Effective Alzheimer's disease detection using enhanced Xception blending with snapshot ensemble.

Alzheimer's disease (AD), a prevalent neurodegenerative disorder, leads to progressive dementia, whi...

Deep-learning assessment of hippocampal magnetic susceptibility in Alzheimer's disease.

BACKGROUND: Quantitative susceptibility mapping (QSM) is pivotal for analyzing neurodegenerative dis...

Identification and cognitive function prediction of Alzheimer's disease based on multivariate pattern analysis of hippocampal volumes.

BACKGROUND: Alzheimer's disease (AD) is strongly associated with slowly progressive hippocampal atro...

Machine learning based on event-related oscillations of working memory differentiates between preclinical Alzheimer's disease and normal aging.

OBJECTIVE: To apply machine learning approaches on EEG event-related oscillations (ERO) to discrimin...

Identifying shared diagnostic genes and mechanisms in vascular dementia and Alzheimer's disease via bioinformatics and machine learning.

BACKGROUND: Alzheimer's disease (AD) and vascular dementia (VaD) share overlapping pathophysiologica...

Multi-scale multimodal deep learning framework for Alzheimer's disease diagnosis.

Multimodal neuroimaging data, including magnetic resonance imaging (MRI) and positron emission tomog...

Establishing a machine learning dementia progression prediction model with multiple integrated data.

OBJECTIVE: Dementia is a significant medical and social issue in most developed countries. Practical...

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