Neurology

Dementia

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

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Artificial intelligence and leukocyte epigenomics: Evaluation and prediction of late-onset Alzheimer's disease.

We evaluated the utility of leucocyte epigenomic-biomarkers for Alzheimer's Disease (AD) detection a...

Recent Advances in Imaging of Preclinical, Sporadic, and Autosomal Dominant Alzheimer's Disease.

Observing Alzheimer's disease (AD) pathological changes in vivo with neuroimaging provides invaluabl...

Detecting cerebral microbleeds via deep learning with features enhancement by reusing ground truth.

BACKGROUND AND OBJECTIVES: Cerebral microbleeds (CMBs) are cerebral small vascular diseases and are ...

Prediction of tau accumulation in prodromal Alzheimer's disease using an ensemble machine learning approach.

We developed machine learning (ML) algorithms to predict abnormal tau accumulation among patients wi...

Deep learning based neuronal soma detection and counting for Alzheimer's disease analysis.

BACKGROUND AND OBJECTIVE: Alzheimer's Disease (AD) is associated with neuronal damage and decrease. ...

Machine Learning and Novel Biomarkers for the Diagnosis of Alzheimer's Disease.

BACKGROUND: Alzheimer's disease (AD) is a complex and severe neurodegenerative disease that still la...

The sTREM2 Concentrations in the Blood: A Marker of Neurodegeneration?

Microglia performs a variety of functions during brain development designed to maintain brain homeos...

Privacy-Preserving Deep Speaker Separation for Smartphone-Based Passive Speech Assessment.

Smartphones can be used to passively assess and monitor patients' speech impairments caused by ailm...

Alzheimer's disease detection using depthwise separable convolutional neural networks.

To diagnose Alzheimer's disease (AD), neuroimaging methods such as magnetic resonance imaging have b...

Plasma d-glutamate levels for detecting mild cognitive impairment and Alzheimer's disease: Machine learning approaches.

BACKGROUND: d-glutamate, which is involved in N-methyl-d-aspartate receptor modulation, may be assoc...

Machine learning identifies candidates for drug repurposing in Alzheimer's disease.

Clinical trials of novel therapeutics for Alzheimer's Disease (AD) have consumed a large amount of t...

A 3D densely connected convolution neural network with connection-wise attention mechanism for Alzheimer's disease classification.

PURPOSE: Alzheimer's disease (AD) is a progressive and irreversible neurodegenerative disease. In re...

A Low-Cost Three-Dimensional DenseNet Neural Network for Alzheimer's Disease Early Discovery.

Alzheimer's disease is the most prevalent dementia among the elderly population. Early detection is ...

A Correlation Analysis between SNPs and ROIs of Alzheimer's Disease Based on Deep Learning.

. At present, the research methods for image genetics of Alzheimer's disease based on machine learni...

Deep learning-based T1-enhanced selection of linear attenuation coefficients (DL-TESLA) for PET/MR attenuation correction in dementia neuroimaging.

PURPOSE: The accuracy of existing PET/MR attenuation correction (AC) has been limited by a lack of c...

Barriers and facilitators to the implementation of social robots for older adults and people with dementia: a scoping review protocol.

BACKGROUND: Psychosocial health issues such as depression and social isolation are an important caus...

An anatomical knowledge-based MRI deep learning pipeline for white matter hyperintensity quantification associated with cognitive impairment.

Recent studies have confirmed that white matter hyperintensities (WMHs) accumulated in strategic bra...

A multilayer multimodal detection and prediction model based on explainable artificial intelligence for Alzheimer's disease.

Alzheimer's disease (AD) is the most common type of dementia. Its diagnosis and progression detectio...

Screening of Alzheimer's disease by facial complexion using artificial intelligence.

Despite the increasing incidence and high morbidity associated with dementia, a simple, non-invasive...

Brain Asymmetry Detection and Machine Learning Classification for Diagnosis of Early Dementia.

Early identification of degenerative processes in the human brain is considered essential for provid...

Cognitive and MRI trajectories for prediction of Alzheimer's disease.

The concept of Mild Cognitive Impairment (MCI) is used to describe the early stages of Alzheimer's d...

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