Latest AI and machine learning research in dementia for healthcare professionals.
Deep learning is a promising tool that uses nonlinear transformations to extract features from high-dimensional data. Deep learning is challenging in genome-wide association studies (GWAS) with high-dimensional genomic data. Here we propose a novel three-step approach (SWAT-CNN) for identification of genetic variants using deep learning to identify phenotype-related single nucleotide polymorphisms...
Mild cognitive impairment (MCI) is often considered the precursor of Alzheimer's disease. However, MCI is associated with substantially variable progression rates, which are not well understood. Attempts to identify the mechanisms that underlie MCI progression have often focused on the hippocampus but have mostly overlooked its intricate structure and subdivisions. Here, we utilized deep learning ...
Alzheimer disease (AD) is a neurodegenerative disorder characterized pathologically by the presence of neurofibrillary tangles and amyloid beta (Aβ) p...
Dementia and other related diseases are becoming increasingly diagnosed and are placing a serious strain on the healthcare system. Robotic technology ...
BACKGROUND: Mild cognitive impairment (MCI), which is common in older adults, is a risk factor for dementia. Rapidly growing health care demand associ...
BACKGROUND: In assessing the levels of clinical impairment in dementia, a summary index of neuropsychological batteries has been widely used in descri...
BACKGROUND: Makeup greatly impacts normal social lives but can also be a non-pharmacological form of therapy for dementia.
BACKGROUND: Alzheimer's disease (AD) is a neurodegenerative condition driven by multifactorial etiology. Mild cognitive impairment (MCI) is a transiti...
MicroRNAs constitute small non-coding RNAs that play a pivotal role in regulating the translation and degradation of mRNA and have been associated wit...
BACKGROUND: Recent studies reported that vascular cognitive impairment in the elderly caused by arteriosclerosis plays an important role in cognitive ...
BACKGROUND: Recent development in neuroimaging and genetic testing technologies have made it possible to measure pathological features associated with...
An expected surge of dementia patients in Japan indicates a pressing need to establish countermeasures. As described herein, by developing an educatio...
Alzheimer's disease (AD) is a progressive neurodegenerative brain disorder characterized by memory loss and cognitive decline. Early detection and acc...
Alzheimer's disease (AD) is a leading cause of dementia, and the current diagnostic methods of AD, such as positron emission tomography imaging, have ...
Biomarkers are one of the primary medical signs to facilitate the early detection of Alzheimer's disease. The small beta-amyloid (Aβ) peptide is an im...
Detecting low cognitive scores at an early stage is important for delaying the progress of dementia. Investigations of early-stage detection have empl...
The majority of studies for automatic epileptic seizure (ictal) detection are based on electroencephalogram (EEG) data, but electrocardiogram (ECG) pr...
Data-driven deep learning has been considered a promising method for building powerful models for medical data, which often requires a large amount of...
Mild Cognitive Impairment (MCI) is the stage between the declining of normal brain function and the more serious decline of dementia. Alzheimer's dise...
Alzheimer's disease (AD) is a progressive brain disorder that causes memory and functional impairments. The advances in machine learning and publicly ...