Dementia

Higher Serum Endocan Level Is Associated with Alzheimer Disease.

BACKGROUND: The novel molecule endocan, which is released by endothelium and is regulated by proangiogenic and proinflammatory cytokines, may have a role in the pathophysiology of Alzheimer disease (AD). The aim of this study was to evaluate the relationship between serum endocan levels and AD.

Effect of a robotic seal on the motor activity and sleep patterns of older people with dementia, as measured by wearable technology: A cluster-randomised controlled trial.

OBJECTIVES: The robotic seal, PARO, has been used as an alternative to animal-assisted therapies with residents with dementia in long-term care, yet understanding of its efficacy is limited by a paucity of research. We explored the effects of PARO on motor activity and sleep patterns, as measured by a wearable triaxial accelerometer.

Use of multimodality imaging and artificial intelligence for diagnosis and prognosis of early stages of Alzheimer's disease.

Alzheimer's disease (AD) is a major neurodegenerative disease and the most common cause of dementia. Currently, no treatment exists to slow down or st...

Revealing Alzheimer's disease genes spectrum in the whole-genome by machine learning.

BACKGROUND: Alzheimer's disease (AD) is an important, progressive neurodegenerative disease, with a complex genetic architecture. A key goal of biomed...

The Cost-Effectiveness of Using PARO, a Therapeutic Robotic Seal, to Reduce Agitation and Medication Use in Dementia: Findings from a Cluster-Randomized Controlled Trial.

OBJECTIVES: To examine the within-trial costs and cost-effectiveness of using PARO, compared with a plush toy and usual care, for reducing agitation a...

Alzheimer's disease diagnostics by a 3D deeply supervised adaptable convolutional network.

Early diagnosis is playing an important role in preventing progress of the Alzheimer's disease (AD). This paper proposes to improve the prediction of ...

Using a therapeutic companion robot for dementia symptoms in long-term care: reflections from a cluster-RCT.

OBJECTIVES: We undertook a cluster-randomised controlled trial exploring the effect of a therapeutic companion robot (PARO) compared to a look-alike p...

Deep learning reveals Alzheimer's disease onset in MCI subjects: Results from an international challenge.

BACKGROUND: Early diagnosis of Alzheimer's disease (AD) and its onset in subjects affected by mild cognitive impairment (MCI) based on structural MRI ...

Robots and people with dementia: Unintended consequences and moral hazard.

The use of social robots in elder care is entering the mainstream as robots become more sophisticated and populations age. While there are many potent...

Random forest feature selection, fusion and ensemble strategy: Combining multiple morphological MRI measures to discriminate among healhy elderly, MCI, cMCI and alzheimer's disease patients: From the alzheimer's disease neuroimaging initiative (ADNI) database.

BACKGROUND: In the era of computer-assisted diagnostic tools for various brain diseases, Alzheimer's disease (AD) covers a large percentage of neuroim...

Ensemble of random forests One vs. Rest classifiers for MCI and AD prediction using ANOVA cortical and subcortical feature selection and partial least squares.

BACKGROUND: Alzheimer's disease (AD) is the most common cause of dementia in the elderly and affects approximately 30 million individuals worldwide. M...

"I Treat Him as a Normal Patient": Unveiling the Normalization Coping Strategy Among Formal Caregivers of Persons With Dementia and Its Implications for Person-Centered Care.

INTRODUCTION: Currently, 47 million people have dementia, worldwide, often requiring paid care by formal caregivers. Research regarding family caregiv...

Advanced patient transfer assist device with intuitive interaction control.

This research aims to improve patient transfers by developing a new type of advanced robotic assist device. It has multiple actuated degrees of freedo...

Early Diagnosis of Alzheimer's Disease Based on Resting-State Brain Networks and Deep Learning.

Computerized healthcare has undergone rapid development thanks to the advances in medical imaging and machine learning technologies. Especially, recen...

Looking for Alzheimer's Disease morphometric signatures using machine learning techniques.

BACKGROUND: We present our results in the International challenge for automated prediction of MCI from MRI data. We evaluate the performance of MRI-ba...

Ensemble based on static classifier selection for automated diagnosis of Mild Cognitive Impairment.

BACKGROUND: Alzheimer's disease (AD) is the most common cause of neurodegenerative dementia in the elderly population. Scientific research is very act...

Comparative molecular docking studies of lupeol and lupenone isolated from Pueraria lobata that inhibits BACE1: Probable remedies for Alzheimer's disease.

OBJECTIVE: To discover lead lupane triterpenoid's potential isolated from Pueraria lobata roots against β-site amyloid precursor protein cleaving enzy...

Nonlinearity-aware based dimensionality reduction and over-sampling for AD/MCI classification from MRI measures.

Alzheimer's disease (AD) has been not only a substantial financial burden to the health care system but also an emotional burden to patients and their...

Alzheimer's disease and driving: review of the literature and consensus guideline from Belgian dementia experts and the Belgian road safety institute endorsed by the Belgian Medical Association.

Alzheimer's disease (AD) is a highly prevalent condition and its prevalence is expected to further increase due to the aging of the general population...

Support vector machine-based classification of neuroimages in Alzheimer's disease: direct comparison of FDG-PET, rCBF-SPECT and MRI data acquired from the same individuals.

OBJECTIVE: To conduct the first support vector machine (SVM)-based study comparing the diagnostic accuracy of T1-weighted magnetic resonance imaging (...