alzheimer's disease (ad) is the most prevalent neurodegenerative disorder. it is characterized by formation of amyloid plaques and neurofibrillary tangles in the brain, degeneration of the cholinergic neurons and neural cell death. this study was aimed to investigate the effect of a triazine derivative, c16h12cl2n3s, on learning in an alzheimer's rat model. animals were divided into seven group...

alzheimers disease (ad) is by far the most common cause of dementia. definite diagnosis of ad is based on pathological findings. nincds-adrda criteria, published more than 25 years ago, are commonly used for the clinical diagnosis of ad. however, considering serious shortcomings of these criteria, new criteria have been proposed. according to these new criteria, ad can be diagnosed in predement...

Alzheimer’s disease (AD) is a neurodegenerative disease and the most common cause of dementia worldwide. Apart from dominantly inherited mutations, age is the major risk factor and as life expectancy increases the prevalence for AD escalates dramatically. AD causes substantial problems for the affected persons and their families, and the society suffers economically. To date the available treat...

Cerebrospinal fluid (CSF) biomarkers may be used to identify and monitor pathological processes in the central nervous system. CSF biomarkers in Alzheimer’s disease (AD) include β-amyloid 42 (Aβ42), total-tau (T-tau) and phosphorylated-tau (P-tau), reflecting brain amyloid, axonal and tangle pathology, respectively. This dissertation aims at defining and validating CSF biomarkers for amyloid an...

BACKGROUND Health care planning and research would benefit from tools that enable researchers to project the future burden of Alzheimer's disease (AD) and evaluate the effect of potential interventions. METHODS We created a web-based application of the AD prevalence model developed by Brookmeyer et al (Am J Public Health 1998;88:1337-42; Alzheimers Dement 2007;3:186-91). The user defines the ...

Computer-aided early diagnosis of Alzheimers Disease (AD) and its prodromal form, Mild Cognitive Impairment (MCI), has been the subject of extensive research in recent years. Some recent studies have shown promising results in the AD and MCI determination using structural and functional Magnetic Resonance Imaging (sMRI, fMRI), Positron Emission Tomography (PET) and Diffusion Tensor Imaging (DTI...

Alzheimers disease is the most common form of dementia in adults aged 65 or older. While many neuro-imaging based biomarkers have been proposed over the years for detection of AD, these have mostly been hand-crafted and utilized domain-specific clinical knowledge. In this project, we are interested in automatically discovering such biomarkers (hidden cues) by using deep learning methods to clas...

Magnetic resonance imaging (MRI) allows to display brain structures with highest resolution. To fully exploit the potential of this imagining modality, data mining methods are required to reveal subtle differences in brain structure caused by disorders such as Mild Cognitive Impairment (MCI) and early stage Alzheimers disease (AD). In this paper, we propose a data mining framework which combine...

Alzheimers Disease (AD) is the most common neurodegenerative disorder associated with aging. Early diagnosis of AD is key to the development, assessment, and monitoring of new treatments for AD. Machine learning approaches are increasingly being applied on the diagnosis of AD from structural MRI. However, the high feature-dimension and imbalanced data learning problem is two major challenges in...