Neurology

Dementia

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

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A brief method for preparation of gintonin-enriched fraction from ginseng.

BACKGROUND: Ginseng has been used as a tonic for invigoration of the human body. In a previous repor...

Deep sparse multi-task learning for feature selection in Alzheimer's disease diagnosis.

Recently, neuroimaging-based Alzheimer's disease (AD) or mild cognitive impairment (MCI) diagnosis h...

Feature Selection Based on the SVM Weight Vector for Classification of Dementia.

Computer-aided diagnosis of dementia using a support vector machine (SVM) can be improved with featu...

A Robust Deep Model for Improved Classification of AD/MCI Patients.

Accurate classification of Alzheimer's disease (AD) and its prodromal stage, mild cognitive impairme...

Boosting diagnosis accuracy of Alzheimer's disease using high dimensional recognition of longitudinal brain atrophy patterns.

OBJECTIVE: Boosting accuracy in automatically discriminating patients with Alzheimer's disease (AD) ...

Identification of a small set of plasma signalling proteins using neural network for prediction of Alzheimer's disease.

MOTIVATION: Alzheimer's disease (AD) is a dementia that gets worse with time resulting in loss of me...

Lokomat training in vascular dementia: motor improvement and beyond!

Vascular dementia (VaD) is a general term describing problems with reasoning, planning, judgment, me...

Multimodal analysis of functional and structural disconnection in Alzheimer's disease using multiple kernel SVM.

Alzheimer's disease (AD) patients exhibit alterations in the functional connectivity between spatial...

Diabetes knowledge in young adults: associations with hemoglobin A1C.

The purpose of this study was to quantify associations between hemoglobin A1C (A1C) and diabetes kno...

Autonomous unobtrusive detection of mild cognitive impairment in older adults.

The current diagnosis process of dementia is resulting in a high percentage of cases with delayed de...

Machine learning framework for early MRI-based Alzheimer's conversion prediction in MCI subjects.

Mild cognitive impairment (MCI) is a transitional stage between age-related cognitive decline and Al...

Predictive Models Based on Support Vector Machines: Whole-Brain versus Regional Analysis of Structural MRI in the Alzheimer's Disease.

Decision-making systems trained on structural magnetic resonance imaging data of subjects affected b...

Manifold regularized multitask feature learning for multimodality disease classification.

Multimodality based methods have shown great advantages in classification of Alzheimer's disease (AD...

Latent feature representation with stacked auto-encoder for AD/MCI diagnosis.

Recently, there have been great interests for computer-aided diagnosis of Alzheimer's disease (AD) a...

Creating a place for caregivers in personal health: the iHealthSpace copilot program and diabetes care.

BACKGROUND: As America's baby boom generation reaches retirement, the number of elders, and, in turn...

Multimodal attention fusion deep self-reconstruction presentation model for Alzheimer's disease diagnosis and biomarker identification.

The unknown pathogenic mechanisms of Alzheimer's disease (AD) make treatment challenging. Neuroimagi...

Emerging blood biomarkers in Alzheimer's disease: a proteomic perspective.

Early detection of Alzheimer's disease (AD) remains a formidable clinical challenge, but emerging bl...

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