Neurology

Dementia

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

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Robot-induced hallucinations in Parkinson's disease depend on altered sensorimotor processing in fronto-temporal network.

Hallucinations in Parkinson's disease (PD) are disturbing and frequent non-motor symptoms and consti...

[A Preliminary Study of Applying Geometric Deep Learning in Brain Morphometry for Diagnosis of Alzheimer's Disease].

OBJECTIVE: A predictive model of Alzheimer's disease (AD) was established based on brain surface mes...

Converting disease maps into heavyweight ontologies: general methodology and application to Alzheimer's disease.

Omics technologies offer great promises for improving our understanding of diseases. The integration...

In Vivo Assay of Cortical Microcircuitry in Frontotemporal Dementia: A Platform for Experimental Medicine Studies.

The analysis of neural circuits can provide crucial insights into the mechanisms of neurodegeneratio...

Prediction of Alzheimer's disease-specific phospholipase c gamma-1 SNV by deep learning-based approach for high-throughput screening.

Exon splicing triggered by unpredicted genetic mutation can cause translational variations in neurod...

DS-GCNs: Connectome Classification using Dynamic Spectral Graph Convolution Networks with Assistant Task Training.

Functional connectivity (FC) matrices measure the regional interactions in the brain and have been w...

An Optimized Decision Tree with Genetic Algorithm Rule-Based Approach to Reveal the Brain's Changes During Alzheimer's Disease Dementia.

BACKGROUND: It is desirable to achieve acceptable accuracy for computer aided diagnosis system (CADS...

A Role for Prior Knowledge in Statistical Classification of the Transition from Mild Cognitive Impairment to Alzheimer's Disease.

BACKGROUND: The transition from mild cognitive impairment (MCI) to dementia is of great interest to ...

An Artificial Intelligence-Assisted Method for Dementia Detection Using Images from the Clock Drawing Test.

BACKGROUND: Widespread dementia detection could increase clinical trial candidates and enable approp...

Identification of Blood-Based Glycolysis Gene Associated with Alzheimer's Disease by Integrated Bioinformatics Analysis.

BACKGROUND: Alzheimer's disease (AD) is one of many common neurodegenerative diseases without ideal ...

Short-Term Memory Binding Distinguishing Amnestic Mild Cognitive Impairment from Healthy Aging: A Machine Learning Study.

BACKGROUND: Amnestic mild cognitive impairment (aMCI) is the most common preclinical stage of Alzhei...

Screening for Early-Stage Alzheimer's Disease Using Optimized Feature Sets and Machine Learning.

BACKGROUND: Detecting early-stage Alzheimer's disease in clinical practice is difficult due to a lac...

A Review of Automated Techniques for Assisting the Early Detection of Alzheimer's Disease with a Focus on EEG.

In this paper, we review state-of-the-art approaches that apply signal processing (SP) and machine l...

Deep Learning and Risk Score Classification of Mild Cognitive Impairment and Alzheimer's Disease.

BACKGROUND: Many neurocognitive and neuropsychological tests are used to classify early mild cogniti...

Sex Differences of Brain Functional Topography Revealed in Normal Aging and Alzheimer's Disease Cohort.

We applied graph theory analysis on resting-state functional magnetic resonance imaging data to eval...

Quantitative Assessment of Resting-State for Mild Cognitive Impairment Detection: A Functional Near-Infrared Spectroscopy and Deep Learning Approach.

BACKGROUND: Mild cognitive impairment (MCI) is considered a prodromal stage of Alzheimer's disease. ...

Machine Learning for the Prediction of Amyloid Positivity in Amnestic Mild Cognitive Impairment.

BACKGROUND: Amyloid-β (Aβ) evaluation in amnestic mild cognitive impairment (aMCI) patients is impor...

Recursive Support Vector Machine Biomarker Selection for Alzheimer's Disease.

BACKGROUND: There is a need for more reliable diagnostic tools for the early detection of Alzheimer'...

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