AIMC Topic: Alzheimer Disease
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Machine Learning Applied to Alzheimer Disease.
Radiology
Dec 1, 2016
Imaging and machine learning techniques for diagnosis of Alzheimer's disease.
Reviews in the neurosciences
Dec 1, 2016
Alzheimer's disease (AD) is a common health problem in elderly people. There has been considerable research toward the diagnosis and early detection of this disease in the past decade. The sensitivity of biomarkers and the accuracy of the detection t...
Label-aligned multi-task feature learning for multimodal classification of Alzheimer's disease and mild cognitive impairment.
Brain imaging and behavior
Dec 1, 2016
Multimodal classification methods using different modalities of imaging and non-imaging data have recently shown great advantages over traditional single-modality-based ones for diagnosis and prognosis of Alzheimer's disease (AD), as well as its prod...
Aged
Disease Progression
Cognitive Dysfunction
ROC Curve
Databases, Factual
Brain
Prognosis
Image Interpretation, Computer-Assisted
Pattern Recognition, Automated
Fluorodeoxyglucose F18
Neuroimaging
Multimodal Imaging
Radiopharmaceuticals
Alzheimer Disease
Positron-Emission Tomography
Humans
Machine Learning
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
Sep 1, 2016
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
Aug 1, 2016
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
Jul 1, 2016
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
Jan 1, 2016
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
Jan 1, 2016
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
Jan 1, 2016
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
Jan 1, 2016
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...
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