AIMC Topic: Alzheimer Disease

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Multiscale deep neural network based analysis of FDG-PET images for the early diagnosis of Alzheimer's disease.

Medical image analysis
Alzheimer's disease (AD) is one of the most common neurodegenerative diseases with a commonly seen prodromal mild cognitive impairment (MCI) phase where memory loss is the main complaint progressively worsening with behavior issues and poor self-care...

Higher Serum Endocan Level Is Associated with Alzheimer Disease.

Dementia and geriatric cognitive disorders
BACKGROUND: The novel molecule endocan, which is released by endothelium and is regulated by proangiogenic and proinflammatory cytokines, may have a role in the pathophysiology of Alzheimer disease (AD). The aim of this study was to evaluate the rela...

Use of multimodality imaging and artificial intelligence for diagnosis and prognosis of early stages of Alzheimer's disease.

Translational research : the journal of laboratory and clinical medicine
Alzheimer's disease (AD) is a major neurodegenerative disease and the most common cause of dementia. Currently, no treatment exists to slow down or stop the progression of AD. There is converging belief that disease-modifying treatments should focus ...

Revealing Alzheimer's disease genes spectrum in the whole-genome by machine learning.

BMC neurology
BACKGROUND: Alzheimer's disease (AD) is an important, progressive neurodegenerative disease, with a complex genetic architecture. A key goal of biomedical research is to seek out disease risk genes, and to elucidate the function of these risk genes i...

A wrapped multi-label classifier for the automatic diagnosis and prognosis of Alzheimer's disease.

Journal of neuroscience methods
BACKGROUND: AD is the most frequent neurodegenerative disease, severely impacting our society. Early diagnosis and prognosis are challenging tasks in the management of AD patients.

Alzheimer's disease diagnostics by a 3D deeply supervised adaptable convolutional network.

Frontiers in bioscience (Landmark edition)
Early diagnosis is playing an important role in preventing progress of the Alzheimer's disease (AD). This paper proposes to improve the prediction of AD with a deep 3D Convolutional Neural Network (3D-CNN), which can show generic features capturing A...

Deep learning reveals Alzheimer's disease onset in MCI subjects: Results from an international challenge.

Journal of neuroscience methods
BACKGROUND: Early diagnosis of Alzheimer's disease (AD) and its onset in subjects affected by mild cognitive impairment (MCI) based on structural MRI features is one of the most important open issues in neuroimaging. Accordingly, a scientific challen...

Neural Network Modeling of AChE Inhibition by New Carbazole-Bearing Oxazolones.

Interdisciplinary sciences, computational life sciences
Acetylcholine esterase (AChE) is one of the targeted enzymes in the therapy of important neurodegenerative diseases such as Alzheimer's disease. Many studies on carbazole- and oxazolone-based compounds have been conducted in the last decade due to th...