Alzheimer's Disease

Effects of a Humanoid Companion Robot on Dementia Symptoms and Caregiver Distress for Residents in Long-Term Care.

OBJECTIVES: To test the effects of deploying a humanoid companion robot (Kabochan) in comparison with usual care for long-term care facilities' residents with dementia.

Alzheimer's Disease stage identification using deep learning models.

OBJECTIVE: The aim of this research is to identify the stage of Alzheimer's Disease (AD) patients through the use of mobility data and deep learning models. This process facilitates the monitoring of the disease and allows actions to be taken in order to provide the optimal treatment and the prevention of complications.

Robot companion cats for people at home with dementia: A qualitative case study on companotics.

The use of robot companion pets for people in care homes has been extensively studied. The results are largely positive and suggest that they are valu...

Diagnosis of Alzheimer's disease using laser-induced breakdown spectroscopy and machine learning.

Alzheimer's disease (AD) is a progressive incurable neurodegenerative disease and a major health problem in aging population. We show that the combine...

Home-Based Cognitively Assistive Robots: Maximizing Cognitive Functioning and Maintaining Independence in Older Adults Without Dementia.

Promoting health and prolonging independence in the home is a priority for older adults, caregivers, clinicians, and society at large. Rapidly develop...

Fully bayesian longitudinal unsupervised learning for the assessment and visualization of AD heterogeneity and progression.

Tau pathology and brain atrophy are the closest correlate of cognitive decline in Alzheimer's disease (AD). Understanding heterogeneity and longitudin...

Using diffusion tensor imaging to detect cortical changes in fronto-temporal dementia subtypes.

Fronto-temporal dementia (FTD) is a common type of presenile dementia, characterized by a heterogeneous clinical presentation that includes three main...

Effects of the Level of Interactivity of a Social Robot and the Response of the Augmented Reality Display in Contextual Interactions of People with Dementia.

The well-being of people with dementia (PWD) living in long-term care facilities is hindered due to disengagement and social isolation. Animal-like so...

Selective Neuronal Vulnerability in Alzheimer's Disease: A Network-Based Analysis.

A major obstacle to treating Alzheimer's disease (AD) is our lack of understanding of the molecular mechanisms underlying selective neuronal vulnerabi...

Speech Quality Feature Analysis for Classification of Depression and Dementia Patients.

Loss of cognitive ability is commonly associated with dementia, a broad category of progressive brain diseases. However, major depressive disorder may...

Effects of non-facilitated meaningful activities for people with dementia in long-term care facilities: A systematic review.

This systematic review sought to evaluate the effectiveness of non-facilitated meaningful activities for older people with dementia in long-term care ...

Insight into potent leads for alzheimer's disease by using several artificial intelligence algorithms.

Several proteins including S-nitrosoglutathione reductase (GSNOR), complement Factor D, complement 3b (C3b) and Protein Kinase R-like Endoplasmic Reti...

Generalization of deep learning models for ultra-low-count amyloid PET/MRI using transfer learning.

PURPOSE: We aimed to evaluate the performance of deep learning-based generalization of ultra-low-count amyloid PET/MRI enhancement when applied to stu...

FastSurfer - A fast and accurate deep learning based neuroimaging pipeline.

Traditional neuroimage analysis pipelines involve computationally intensive, time-consuming optimization steps, and thus, do not scale well to large c...

MRI Segmentation and Classification of Human Brain Using Deep Learning for Diagnosis of Alzheimer's Disease: A Survey.

Many neurological diseases and delineating pathological regions have been analyzed, and the anatomical structure of the brain researched with the aid ...

Application of Deep Learning to Predict Standardized Uptake Value Ratio and Amyloid Status on F-Florbetapir PET Using ADNI Data.

BACKGROUND AND PURPOSE: Cortical amyloid quantification on PET by using the standardized uptake value ratio is valuable for research studies and clini...

An Efficient Combination among sMRI, CSF, Cognitive Score, and 4 Biomarkers for Classification of AD and MCI Using Extreme Learning Machine.

Alzheimer's disease (AD) is the most common cause of dementia and a progressive neurodegenerative condition, characterized by a decline in cognitive f...

AD-NET: Age-adjust neural network for improved MCI to AD conversion prediction.

The prediction of Mild Cognitive Impairment (MCI) patients who are at higher risk converting to Alzheimer's Disease (AD) is critical for effective int...

Neuro4Neuro: A neural network approach for neural tract segmentation using large-scale population-based diffusion imaging.

Subtle changes in white matter (WM) microstructure have been associated with normal aging and neurodegeneration. To study these associations in more d...

Evidence that the Kennedy and polyamine pathways are dysregulated in human brain in cases of dementia with Lewy bodies.

Disruptions of brain metabolism are considered integral to the pathogenesis of dementia, but thus far little is known of how dementia with Lewy bodies...