Alzheimer's Disease

Neuroprotective and Therapeutic Effects of Tocovid and Twendee-X on Aβ Oligomer-Induced Damage in the SH-SY5Y Cell Line.

BACKGROUND: Alzheimer's disease (AD) is the most frequent cause of dementia among the elderly. The accumulation of amyloid beta (Aβ) and its downstream pathological events such as oxidative stress play central roles in AD. Recent studies revealed that Aβ oligomer (AβO)-induced strong neurotoxicity in SH-SY5Y cells via the induction of oxidative stress.

Cognitive Impairment of Patient With Neurological Cerebrovascular Disease Using the Artificial Intelligence Technology Guided by MRI.

This study was to explore the application of MRI based on artificial intelligence technology combined with neuropsychological assessment to the cognitive impairment of patients with neurological cerebrovascular diseases. A total of 176 patients were divided into a control group, a vascular cognitive impairment non-dementia (VCIND) group, a vascular dementia (VD) group, and an Alzheimer's disease (...

Improving Alzheimer's Disease Detection for Speech Based on Feature Purification Network.

Alzheimer's disease (AD) is a neurodegenerative disease involving the decline of cognitive ability with illness progresses. At present, the diagnosis ...

Machine learning detects altered spatial navigation features in outdoor behaviour of Alzheimer's disease patients.

Impairment of navigation is one of the earliest symptoms of Alzheimer's disease (AD), but to date studies have involved proxy tests of navigation rath...

Segmentation of pancreatic ductal adenocarcinoma (PDAC) and surrounding vessels in CT images using deep convolutional neural networks and texture descriptors.

Fully automated and volumetric segmentation of critical tumors may play a crucial role in diagnosis and surgical planning. One of the most challenging...

Deep learning identifies brain structures that predict cognition and explain heterogeneity in cognitive aging.

Specific brain structures (gray matter regions and white matter tracts) play a dominant role in determining cognitive decline and explain the heteroge...

Predictive classification of Alzheimer's disease using brain imaging and genetic data.

For now, Alzheimer's disease (AD) is incurable. But if it can be diagnosed early, the correct treatment can be used to delay the disease. Most of the ...

Blockchain-Based Deep Learning to Process IoT Data Acquisition in Cognitive Data.

Remote health monitoring can help prevent disease at the earlier stages. The Internet of Things (IoT) concepts have recently advanced, enabling omnipr...

Evaluation of Neuro Images for the Diagnosis of Alzheimer's Disease Using Deep Learning Neural Network.

Alzheimer's Disease (AD) is a progressive, neurodegenerative brain disease and is an incurable ailment. No drug exists for AD, but its progression can...

Inferring protein expression changes from mRNA in Alzheimer's dementia using deep neural networks.

Identifying the molecular systems and proteins that modify the progression of Alzheimer's disease and related dementias (ADRD) is central to drug targ...

GuiltyTargets: Prioritization of Novel Therapeutic Targets With Network Representation Learning.

The majority of clinical trials fail due to low efficacy of investigated drugs, often resulting from a poor choice of target protein. Existing computa...

Genetic Algorithms for Optimized Diagnosis of Alzheimer's Disease and Frontotemporal Dementia Using Fluorodeoxyglucose Positron Emission Tomography Imaging.

Genetic algorithms have a proven capability to explore a large space of solutions, and deal with very large numbers of input features. We hypothesized...

Propagating Uncertainty Across Cascaded Medical Imaging Tasks for Improved Deep Learning Inference.

Although deep networks have been shown to perform very well on a variety of medical imaging tasks, inference in the presence of pathology presents sev...

Investigating Simultaneity for Deep Learning-Enhanced Actual Ultra-Low-Dose Amyloid PET/MR Imaging.

BACKGROUND AND PURPOSE: Diagnostic-quality amyloid PET images can be created with deep learning using actual ultra-low-dose PET images and simultaneou...

Machine Learning-Assisted Pattern Recognition of Amyloid Beta Aggregates with Fluorescent Conjugated Polymers and Graphite Oxide Electrostatic Complexes.

Five fluorescent positively charged poly(-aryleneethynylene) (-) were designed to construct electrostatic complexes - with negatively charged graphene...

Intelligent assistive technology devices for persons with dementia: A scoping review.

Assistive technology (AT) with context-aware computing and artificial intelligence capabilities can be applied to address cognitive and communication ...

DOTA: Deep Learning Optimal Transport Approach to Advance Drug Repositioning for Alzheimer's Disease.

Alzheimer's disease (AD) is the leading cause of age-related dementia, affecting over 5 million people in the United States and incurring a substantia...

An Exploration: Alzheimer's Disease Classification Based on Convolutional Neural Network.

Alzheimer's disease (AD) is the most generally known neurodegenerative disorder, leading to a steady deterioration in cognitive ability. Deep learning...

Comparing two artificial intelligence software packages for normative brain volumetry in memory clinic imaging.

PURPOSE: To compare two artificial intelligence software packages performing normative brain volumetry and explore whether they could differently impa...

Application of artificial intelligence in brain molecular imaging.

Initial development of artificial Intelligence (AI) and machine learning (ML) dates back to the mid-twentieth century. A growing awareness of the pote...