AIMC Topic: Alzheimer Disease

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[Robotics and improvement of the quality of geriatric care].

Soins. Gerontologie
New technologies offer innovations to improve the care of the elderly with Alzheimer's or and other forms of dementia. Robots, endowed with features such as monitoring of physiological parameters, cognitive training or occupational therapy, have appe...

Discrimination of Active and Weakly Active Human BACE1 Inhibitors Using Self-Organizing Map and Support Vector Machine.

Combinatorial chemistry & high throughput screening
β-secretase (BACE1) is an aspartyl protease, which is considered as a novel vital target in Alzheimer`s disease therapy. We collected a data set of 294 BACE1 inhibitors, and built six classification models to discriminate active and weakly active inh...

Alzheimer's Disease Brain Areas: The Machine Learning Support for Blind Localization.

Current Alzheimer research
The analysis of positron emission tomography (PET) scan image is challenging due to a high level of noise and a low resolution and also because differences between healthy and demented are very subtle. High dimensional classification methods based on...

Fuzzy Computer-Aided Alzheimer's Disease Diagnosis Based on MRI Data.

Current Alzheimer research
Alzheimer's disease (AD) is a chronic neurodegenerative disease of the central nervous system that has no cure and leads to death. One of the most prevalent tools for AD diagnosis is magnetic resonance imaging (MRI), because of its capability to visu...

Frontiers for the Early Diagnosis of AD by Means of MRI Brain Imaging and Support Vector Machines.

Current Alzheimer research
The emergence of Alzheimer's Disease (AD) as a consequence of increasing aging population makes urgent the availability of methods for the early and accurate diagnosis. Magnetic Resonance Imaging (MRI) could be used as in vivo, non invasive tool to i...

Multimodal manifold-regularized transfer learning for MCI conversion prediction.

Brain imaging and behavior
As the early stage of Alzheimer's disease (AD), mild cognitive impairment (MCI) has high chance to convert to AD. Effective prediction of such conversion from MCI to AD is of great importance for early diagnosis of AD and also for evaluating AD risk ...

Characterization of complexity in the electroencephalograph activity of Alzheimer's disease based on fuzzy entropy.

Chaos (Woodbury, N.Y.)
In this paper, experimental neurophysiologic recording and statistical analysis are combined to investigate the nonlinear characteristic and the cognitive function of the brain. Fuzzy approximate entropy and fuzzy sample entropy are applied to charac...

Robust supervised segmentation of neuropathology whole-slide microscopy images.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Alzheimer's disease is characterized by brain pathological aggregates such as Aβ plaques and neurofibrillary tangles which trigger neuroinflammation and participate to neuronal loss. Quantification of these pathological markers on histological sectio...

Semi-supervised manifold learning with affinity regularization for Alzheimer's disease identification using positron emission tomography imaging.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Dementia, Alzheimer's disease (AD) in particular is a global problem and big threat to the aging population. An image based computer-aided dementia diagnosis method is needed to providing doctors help during medical image examination. Many machine le...

Identification of Conversion from Normal Elderly Cognition to Alzheimer's Disease using Multimodal Support Vector Machine.

Journal of Alzheimer's disease : JAD
Alzheimer's disease (AD) is one of the most serious progressive neurodegenerative diseases among the elderly, therefore the identification of conversion to AD at the earlier stage has become a crucial issue. In this study, we applied multimodal suppo...