Neurology

Dementia

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

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Evaluating the reliability of neurocognitive biomarkers of neurodegenerative diseases across countries: A machine learning approach.

Accurate early diagnosis of neurodegenerative diseases represents a growing challenge for current cl...

Combining entity co-occurrence with specialized word embeddings to measure entity relation in Alzheimer's disease.

BACKGROUND: Extracting useful information from biomedical literature plays an important role in the ...

Machine Learning to Detect Alzheimer's Disease from Circulating Non-coding RNAs.

Blood-borne small non-coding (sncRNAs) are among the prominent candidates for blood-based diagnostic...

Discriminative margin-sensitive autoencoder for collective multi-view disease analysis.

Medical prediction is always collectively determined based on bioimages collected from different sou...

How people with dementia perceive a therapeutic robot called PARO in relation to their pain and mood: A qualitative study.

BACKGROUND: Interacting with social robots, such as the robotic seal PARO, has been shown to improve...

Deep learning to detect Alzheimer's disease from neuroimaging: A systematic literature review.

Alzheimer's Disease (AD) is one of the leading causes of death in developed countries. From a resear...

Synthetic review of financial capacity in cognitive disorders: Foundations, interventions, and innovations.

PURPOSE OF REVIEW: Financial capacity (FC) is a complex, multi-dimensional construct that changes ov...

Cognitive signature of brain FDG PET based on deep learning: domain transfer from Alzheimer's disease to Parkinson's disease.

PURPOSE: Although functional brain imaging has been used for the early and objective assessment of c...

Quantitative susceptibility mapping based hybrid feature extraction for diagnosis of Parkinson's disease.

Parkinson's disease is the second most common neurodegenerative disease in the elderly after Alzheim...

A distributed multitask multimodal approach for the prediction of Alzheimer's disease in a longitudinal study.

Predicting the progression of Alzheimer's Disease (AD) has been held back for decades due to the lac...

Single-slice Alzheimer's disease classification and disease regional analysis with Supervised Switching Autoencoders.

BACKGROUND: Alzheimer's disease (AD) is a difficult to diagnose pathology of the brain that progress...

A comparison of machine learning classifiers for dementia with Lewy bodies using miRNA expression data.

BACKGROUND: Dementia with Lewy bodies (DLB) is the second most common subtype of neurodegenerative d...

Computational modeling of the effects of EEG volume conduction on functional connectivity metrics. Application to Alzheimer's disease continuum.

OBJECTIVE: The aim of this study was to evaluate the effect of electroencephalographic (EEG) volume ...

MCADNNet: Recognizing Stages of Cognitive Impairment through Efficient Convolutional fMRI and MRI Neural Network Topology Models.

Mild cognitive impairment (MCI) represents the intermediate stage between normal cerebral aging and ...

Review of outcome measures in PARO robot intervention studies for dementia care.

The aim of this study was to describe interventions for PARO, as well as the outcomes evaluated and ...

Hippocampal segmentation for brains with extensive atrophy using three-dimensional convolutional neural networks.

Hippocampal volumetry is a critical biomarker of aging and dementia, and it is widely used as a pred...

Person transfer assist systems: a literature review.

OBJECTIVE: Novel developments in the robotics field have produced systems that can support person wh...

Using path signatures to predict a diagnosis of Alzheimer's disease.

The path signature is a means of feature generation that can encode nonlinear interactions in data i...

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