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Cognitive Dysfunction

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A Deep Learning Approach to Neuroanatomical Characterisation of Alzheimer's Disease.

Studies in health technology and informatics
Alzheimer's disease (AD) is a neurological degenerative disorder that leads to progressive mental deterioration. This work introduces a computational approach to improve our understanding of the progression of AD. We use ensemble learning methods and...

Machine-learning Support to Individual Diagnosis of Mild Cognitive Impairment Using Multimodal MRI and Cognitive Assessments.

Alzheimer disease and associated disorders
BACKGROUND: Understanding whether the cognitive profile of a patient indicates mild cognitive impairment (MCI) or performance levels within normality is often a clinical challenge. The use of resting-state functional magnetic resonance imaging (RS-fM...

Label-aligned multi-task feature learning for multimodal classification of Alzheimer's disease and mild cognitive impairment.

Brain imaging and behavior
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...

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...

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...

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...

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 ...

Supervised Discriminative Group Sparse Representation for Mild Cognitive Impairment Diagnosis.

Neuroinformatics
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...