Dementia

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 developing robotics technology provides a platform for interventions, with the fields of physically and socially assistive robots expanding in recent years. However, less attention has been paid to using robots to enhance the cognitive health of older adult...

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 longitudinal progression of atrophy during the disease course will play a key role in understanding AD pathogenesis. We propose a framework for longitudinal clustering that simultaneously: 1) incorporates whole brain data, 2) leverages unequal visits per indiv...

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...

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 ...

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...

Grab-AD: Generalizability and reproducibility of altered brain activity and diagnostic classification in Alzheimer's Disease.

Alzheimer's disease (AD) is associated with disruptions in brain activity and networks. However, there is substantial inconsistency among studies that...

Deep learning based mild cognitive impairment diagnosis using structure MR images.

Mild cognitive impairment (MCI) is an early sign of Alzheimer's disease (AD) which is the fourth leading disease mostly found in the aged population. ...

The reliability of a deep learning model in clinical out-of-distribution MRI data: A multicohort study.

Deep learning (DL) methods have in recent years yielded impressive results in medical imaging, with the potential to function as clinical aid to radio...

Validation of machine learning models to detect amyloid pathologies across institutions.

Semi-quantitative scoring schemes like the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) are the most commonly used method in Alz...

Designing weighted correlation kernels in convolutional neural networks for functional connectivity based brain disease diagnosis.

Functional connectivity networks (FCNs) based on functional magnetic resonance imaging (fMRI) have been widely applied to analyzing and diagnosing bra...

Gait-Based Machine Learning for Classifying Patients with Different Types of Mild Cognitive Impairment.

Mild cognitive impairment (MCI) may be caused by Alzheimer's disease, Parkinson's disease (PD), cerebrovascular accident, nutritional or metabolic dis...

AI approach of cycle-consistent generative adversarial networks to synthesize PET images to train computer-aided diagnosis algorithm for dementia.

OBJECTIVE: An artificial intelligence (AI)-based algorithm typically requires a considerable amount of training data; however, few training images are...