AIMC Topic: Brain Mapping
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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
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...
Recursive feature elimination for biomarker discovery in resting-state functional connectivity.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Aug 1, 2016
Biomarker discovery involves finding correlations between features and clinical symptoms to aid clinical decision. This task is especially difficult in resting state functional magnetic resonance imaging (rs-fMRI) data due to low SNR, high-dimensiona...
Measuring the agreement between brain connectivity networks.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Aug 1, 2016
Investigating the level of similarity between two brain networks, resulting from measures of effective connectivity in the brain, can be of interest from many respects. In this study, we propose and test the idea to borrow measures of association use...
A connectionist modeling study of the neural mechanisms underlying pain's ability to reorient attention.
Cognitive, affective & behavioral neuroscience
Aug 1, 2016
Connectionist modeling was used to investigate the brain mechanisms responsible for pain's ability to shift attention away from another stimulus modality and toward itself. Different connectionist model architectures were used to simulate the differe...
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...
Supervised learning technique for the automated identification of white matter hyperintensities in traumatic brain injury.
Brain injury
Jan 1, 2016
BACKGROUND: White matter hyperintensities (WMHs) are foci of abnormal signal intensity in white matter regions seen with magnetic resonance imaging (MRI). WMHs are associated with normal ageing and have shown prognostic value in neurological conditio...
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...
Best facilitated cortical activation during different stepping, treadmill, and robot-assisted walking training paradigms and speeds: A functional near-infrared spectroscopy neuroimaging study.
NeuroRehabilitation
Jan 1, 2016
BACKGROUND: Robot-assisted and treadmill-gait training are promising neurorehabilitation techniques, with advantages over conventional gait training, but the neural substrates underpinning locomotor control remain unknown particularly during differen...
Supervised Discriminative Group Sparse Representation for Mild Cognitive Impairment Diagnosis.
Neuroinformatics
Jul 1, 2015
Research on an early detection of Mild Cognitive Impairment (MCI), a prodromal stage of Alzheimer's Disease (AD), with resting-state functional Magnetic Resonance Imaging (rs-fMRI) has been of great interest for the last decade. Witnessed by recent s...
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