AIMC Topic: Alzheimer Disease
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Frontiers for the Early Diagnosis of AD by Means of MRI Brain Imaging and Support Vector Machines.
Current Alzheimer research
Jan 1, 2016
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
Dec 1, 2015
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 ...
Magnetic Resonance Imaging
Multimodal Imaging
Least-Squares Analysis
Supervised Machine Learning
Alzheimer Disease
Positron-Emission Tomography
Disease Progression
Humans
Pattern Recognition, Automated
Diagnosis, Computer-Assisted
Aged
Cognitive Dysfunction
Aged, 80 and over
Databases, Factual
ROC Curve
Middle Aged
Brain
Prognosis
Characterization of complexity in the electroencephalograph activity of Alzheimer's disease based on fuzzy entropy.
Chaos (Woodbury, N.Y.)
Aug 1, 2015
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
Jan 1, 2015
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
Jan 1, 2015
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
Jan 1, 2015
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...
Applying Automated MR-Based Diagnostic Methods to the Memory Clinic: A Prospective Study.
Journal of Alzheimer's disease : JAD
Jan 1, 2015
Several studies have demonstrated that fully automated pattern recognition methods applied to structural magnetic resonance imaging (MRI) aid in the diagnosis of dementia, but these conclusions are based on highly preselected samples that significant...
Use of Robotic Pets in Providing Stimulation for Nursing Home Residents with Dementia.
Studies in health technology and informatics
Jan 1, 2015
Trial experiments utilized robotic pets to facilitate self-reliance in nursing home residents. A remote-control robot modeled clear and meaningful behaviors to elderly residents. Special attention was paid to its effects on mental and social domains....
[Technology yes, technology no?].
Krankenpflege. Soins infirmiers
Jan 1, 2015
Epistasis analysis using artificial intelligence.
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2015
Here we introduce artificial intelligence (AI) methodology for detecting and characterizing epistasis in genetic association studies. The ultimate goal of our AI strategy is to analyze genome-wide genetics data as a human would using sources of exper...
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