Latest AI and machine learning research in alzheimer's disease for healthcare professionals.
Accurate identification and understanding informative feature is important for early Alzheimer's disease (AD) prognosis and diagnosis. In this paper, we propose a novel discriminative sparse learning method with relational regularization to jointly predict the clinical score and classify AD disease stages using multimodal features. Specifically, we apply a discriminative learning technique to expa...
BACKGROUND: The manual diagnosis of neurodegenerative disorders such as Alzheimer's disease (AD) and related Dementias has been a challenge. Currently, these disorders are diagnosed using specific clinical diagnostic criteria and neuropsychological examinations. The use of several Machine Learning algorithms to build automated diagnostic models using low-level linguistic features resulting from ve...
Currently, an estimated 36 million people worldwide are affected by Alzheimer's disease or related dementias. In the absence of a cure, non-pharmacolo...
Cardiovascular disease (CVD) remains a leading cause of mortality and morbidity worldwide. Numerous therapies are currently under investigation to imp...
A 2-year-old girl, previously healthy, was brought to the emergency department because of significant cramping abdominal pain with recurrent hematoche...
BACKGROUND: This study specifically focused on anatomical MRI characterization of the low shear stress-induced atherosclerotic plaque in mice. We used...
BACKGROUND: A variety of neurodegenerative diseases (NDs) have been associated with deregulated caspase activation that leads to neuronal death. Caspa...
Impaired endothelial nitric oxide synthase (eNOS)/nitric oxide (NO) pathway induces atherogenesis. The present study examined whether icariin improves...
Rey's Auditory Verbal Learning Test (RAVLT) is a powerful neuropsychological tool for testing episodic memory, which is widely used for the cognitive ...
The use of wearable devices to study gait and postural control is a growing field on neurodegenerative disorders such as Alzheimer's disease (AD). In ...
OBJECTIVES: Social robots such as Paro, a therapeutic companion robot, have recently been introduced into dementia care as a means to reduce behaviour...
INTRODUCTION: Blood protein analysis of total tau (t-tau) may be a practical screening biomarker for chronic traumatic encephalopathy (CTE), a neurode...
This paper presents a brain T1-weighted structural magnetic resonance imaging (MRI) biomarker that combines several individual MRI biomarkers (cortica...
BACKGROUND: Alzheimer's disease (AD) is a complex progressive neurodegenerative disorder commonly characterized by short term memory loss. Presently n...
Effectively utilizing incomplete multi-modality data for diagnosis of Alzheimer's disease (AD) is still an area of active research. Several multi-view...
The diagnosis of Alzheimer's disease (AD) from neuroimaging data at the pre-clinical stage has been intensively investigated because of the immense so...
BACKGROUND: Robots have the potential to both enable older adults with dementia to perform daily activities with greater independence, and provide sup...
Fluorescence represents one of the most powerful tools for the detection and structural characterization of the pathogenic protein aggregates, amyloid...
AIM: The aim of this study was to investigate effects of robot-assisted group activity with Paro on quality of life in older people with dementia.
Longitudinal designs are widely used in medical studies as a means of observing within-subject changes over time in groups of subjects, thereby aiming...