Neurology

Dementia

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

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A Transcriptomics-Based Machine Learning Model Discriminating Mild Cognitive Impairment and the Prediction of Conversion to Alzheimer's Disease.

The clinical spectrum of Alzheimer's disease (AD) ranges dynamically from asymptomatic and mild cogn...

Optimizing early diagnosis by integrating multiple classifiers for predicting brain stroke and critical diseases.

Machine learning has gained attention in the medical field. Continuous efforts are being made to dev...

An intelligent magnetic resonance imagining-based multistage Alzheimer's disease classification using swish-convolutional neural networks.

Alzheimer's disease (AD) refers to a neurological disorder that causes damage to brain cells and res...

Application and effectiveness of adaptive AI in elderly healthcare.

BACKGROUND: In addressing elderly healthcare issues, cognitive impairment can cause significant disr...

Ultrasensitive Detection of Blood-Based Alzheimer's Disease Biomarkers: A Comprehensive SERS-Immunoassay Platform Enhanced by Machine Learning.

Accurate and early disease detection is crucial for improving patient care, but traditional diagnost...

Machine learning-based predictive model for post-stroke dementia.

BACKGROUND: Post-stroke dementia (PSD), a common complication, diminishes rehabilitation efficacy an...

Unveiling the decision making process in Alzheimer's disease diagnosis: A case-based counterfactual methodology for explainable deep learning.

BACKGROUND: The field of Alzheimer's disease (AD) diagnosis is undergoing significant transformation...

Comparison of machine learning algorithms for automatic prediction of Alzheimer disease.

BACKGROUND: Alzheimer disease is a progressive neurological disorder marked by irreversible memory l...

Assessing polyomic risk to predict Alzheimer's disease using a machine learning model.

INTRODUCTION: Alzheimer's disease (AD) is the most common form of dementia in the elderly. Given tha...

G-Protein Signaling in Alzheimer's Disease: Spatial Expression Validation of Semi-supervised Deep Learning-Based Computational Framework.

Systemic study of pathogenic pathways and interrelationships underlying genes associated with Alzhei...

Prediction and clustering of Alzheimer's disease by race and sex: a multi-head deep-learning approach to analyze irregular and heterogeneous data.

Early detection of Alzheimer's disease (AD) is crucial to maximize clinical outcomes. Most disease p...

Using interpretable deep learning radiomics model to diagnose and predict progression of early AD disease spectrum: a preliminary [F]FDG PET study.

OBJECTIVES: In this study, we propose an interpretable deep learning radiomics (IDLR) model based on...

A modified deep learning method for Alzheimer's disease detection based on the facial submicroscopic features in mice.

Alzheimer's disease (AD) is a chronic disease among people aged 65 and older. As the aging populatio...

Hierarchical Graph Convolutional Network Built by Multiscale Atlases for Brain Disorder Diagnosis Using Functional Connectivity.

Functional connectivity network (FCN) data from functional magnetic resonance imaging (fMRI) is incr...

Utilizing graph neural networks for adverse health detection and personalized decision making in sensor-based remote monitoring for dementia care.

BACKGROUND: Sensor-based remote health monitoring is increasingly used to detect adverse health in p...

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