Latest AI and machine learning research in alzheimer's disease for healthcare professionals.
We present a comparative split-half resampling analysis of various data driven feature selection and classification methods for the whole brain voxel-based classification analysis of anatomical magnetic resonance images. We compared support vector machines (SVMs), with or without filter based feature selection, several embedded feature selection methods and stability selection. While comparisons o...
INTRODUCTION: Down Syndrome (DS) adults experience accumulation of Alzheimer's disease (AD)-like amyloid plaques and tangles and a high incidence of dementia and could provide an enriched population to study AD-targeted treatments. However, to evaluate effects of therapeutic intervention, it is necessary to dissociate the contributions of DS and AD from overall phenotype. Imaging biomarkers offer ...
In the extremely aged society, rehabilitation staff will be required to provide ample rehabilitation training for more stroke patients and more aged p...
New technologies offer innovations to improve the care of the elderly with Alzheimer's or and other forms of dementia. Robots, endowed with features s...
The emergence of Alzheimer's Disease (AD) as a consequence of increasing aging population makes urgent the availability of methods for the early and a...
Alzheimer's disease (AD) is a chronic neurodegenerative disease of the central nervous system that has no cure and leads to death. One of the most pre...
The analysis of positron emission tomography (PET) scan image is challenging due to a high level of noise and a low resolution and also because differ...
β-secretase (BACE1) is an aspartyl protease, which is considered as a novel vital target in Alzheimer`s disease therapy. We collected a data set of 29...
The merging of the human world and the information technology world is advancing at a pace, even for those with dementia there are many useful smart '...
As the early stage of Alzheimer's disease (AD), mild cognitive impairment (MCI) has high chance to convert to AD. Effective prediction of such convers...
The current study aimed to explore (a) reactions of individuals with dementia to an interactive robotic cat and their relatives' and professional care...
In this paper, experimental neurophysiologic recording and statistical analysis are combined to investigate the nonlinear characteristic and the cogni...
Research on an early detection of Mild Cognitive Impairment (MCI), a prodromal stage of Alzheimer's Disease (AD), with resting-state functional Magnet...
Artificial intelligence (IA) is the subject of much research, but also many fantasies. It aims to reproduce human intelligence in its learning capacit...
Multivariate pattern analysis (MVPA) methods have become an important tool in neuroimaging, revealing complex associations and yielding powerful predi...
BACKGROUND: Neuroimaging techniques combined with computational neuroanatomy have been playing a role in the investigation of healthy aging and Alzhei...
BACKGROUND: Socially assistive robotics (SAR) has been a major field of investigation during the last decade and, as it develops, the groups the techn...
In the last twenty years most developed countries face dramatic demographic changes, and predominantly the rapid aging of their population. As the sha...
INTRODUCTION: Reducing the amount of testing required to accurately detect cognitive impairment is clinically relevant. The aim of this research was t...
Several studies have demonstrated that fully automated pattern recognition methods applied to structural magnetic resonance imaging (MRI) aid in the d...