AI Medical Compendium Topic:
Alzheimer Disease

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Application of advanced machine learning methods on resting-state fMRI network for identification of mild cognitive impairment and Alzheimer's disease.

Brain imaging and behavior
The study of brain networks by resting-state functional magnetic resonance imaging (rs-fMRI) is a promising method for identifying patients with dementia from healthy controls (HC). Using graph theory, different aspects of the brain network can be ef...

[Effects of extractionfrom raspberry on hippocampus proteomics of mice suffered from ovariectomized-induced AD].

Zhongguo Zhong yao za zhi = Zhongguo zhongyao zazhi = China journal of Chinese materia medica
This paper was aimed to investigate the impact of the extraction from raspberry on the Alzheimer disease model protein expression. According to weight, the ovariectomized mice were randomly divided into shame operation group, model group, estrogen po...

Comparison of Feature Selection Techniques in Machine Learning for Anatomical Brain MRI in Dementia.

Neuroinformatics
We present a comparative split-half resampling analysis of various data driven feature selection and classification methods for the whole brain voxel-based classification analysis of anatomical magnetic resonance images. We compared support vector ma...

[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...