Neurology

Dementia

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

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An experimental framework for conjoint measures of olfaction, navigation, and motion as pre-clinical biomarkers of Alzheimer's disease.

Elucidating Alzheimer's disease (AD) prodromal symptoms can resolve the outstanding challenge of ear...

Classifying Alzheimer's Disease Using a Finite Basis Physics Neural Network.

The disease amyloid plaques, neurofibrillary tangles, synaptic dysfunction, and neuronal death gradu...

Association between Alzheimer's disease pathologic products and age and a pathologic product-based diagnostic model for Alzheimer's disease.

BACKGROUND: Alzheimer's disease (AD) has a major negative impact on people's quality of life, life, ...

Cholinesterase Inhibitory Activity of Paeoniflorin: Molecular Dynamics Simulation, and In Vitro Mechanistic Investigation.

Alzheimer's disease (AD), a neurological disorder, is one of the major reasons for memory loss in th...

MHAGuideNet: a 3D pre-trained guidance model for Alzheimer's Disease diagnosis using 2D multi-planar sMRI images.

BACKGROUND: Alzheimer's Disease is a neurodegenerative condition leading to irreversible and progres...

Deep learning-based patient stratification for prognostic enrichment of clinical dementia trials.

Dementia probably due to Alzheimer's disease is a progressive condition that manifests in cognitive ...

DCA-Enhanced Alzheimer's detection with shearlet and deep learning integration.

Alzheimer's dementia (AD) is a neurodegenerative disorder that affects the central nervous system, c...

Multimodal Alzheimer's disease classification through ensemble deep random vector functional link neural network.

Alzheimer's disease (AD) is a condition with a complex pathogenesis, sometimes hereditary, character...

A machine learning approach for identifying anatomical biomarkers of early mild cognitive impairment.

BACKGROUND: Alzheimer's Disease (AD) poses a major challenge as a neurodegenerative disorder, and ea...

Random survival forest model for early prediction of Alzheimer's disease conversion in early and late Mild cognitive impairment stages.

With a clinical trial failure rate of 99.6% for Alzheimer's Disease (AD), early diagnosis is critica...

Time-Frequency functional connectivity alterations in Alzheimer's disease and frontotemporal dementia: An EEG analysis using machine learning.

OBJECTIVE: Alzheimer's disease (AD) and frontotemporal dementia (FTD) are prevalent neurodegenerativ...

Synthetic data analysis for early detection of Alzheimer progression through machine learning algorithms.

Alzheimer's disease (AD) is a serious neurodegenerative disorder that causes incurable and irreversi...

Early detection of Alzheimer's disease in structural and functional MRI.

OBJECTIVES: To implement state-of-the-art deep learning architectures such as Deep-Residual-U-Net an...

Early Detection of Dementia in Populations With Type 2 Diabetes: Predictive Analytics Using Machine Learning Approach.

BACKGROUND: The possible association between diabetes mellitus and dementia has raised concerns, giv...

Natural compounds for Alzheimer's prevention and treatment: Integrating SELFormer-based computational screening with experimental validation.

BACKGROUND: This study aimed to develop and apply a novel computational pipeline combining SELFormer...

Neurodegeneration: 2024 update.

This review highlights a collection of both diverse and highly impactful studies published in the pr...

Machine learning based algorithms for virtual early detection and screening of neurodegenerative and neurocognitive disorders: a systematic-review.

BACKGROUND AND AIM: Neurodegenerative disorders (e.g., Alzheimer's, Parkinson's) lead to neuronal lo...

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