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Multiple Sclerosis

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Discriminating sample groups with multi-way data.

Biostatistics (Oxford, England)
High-dimensional linear classifiers, such as distance weighted discrimination (DWD) and versions of the support vector machine (SVM), are commonly used in biomedical research to distinguish groups of subjects based on a large number of features. Howe...

Neuroplasticity-Based Technologies and Interventions for Restoring Motor Functions in Multiple Sclerosis.

Advances in experimental medicine and biology
Motor impairments are very common in multiple sclerosis (MS), leading to a reduced Quality of Life and active participation. In the past decades, new insights into the functional reorganization processes that occur after a brain injury have been intr...

Determining Multiple Sclerosis Phenotype from Electronic Medical Records.

Journal of managed care & specialty pharmacy
BACKGROUND: Multiple sclerosis (MS), a central nervous system disease in which nerve signals are disrupted by scarring and demyelination, is classified into phenotypes depending on the patterns of cognitive or physical impairment progression: relapsi...

Subject-Specific Sparse Dictionary Learning for Atlas-Based Brain MRI Segmentation.

IEEE journal of biomedical and health informatics
Quantitative measurements from segmentations of human brain magnetic resonance (MR) images provide important biomarkers for normal aging and disease progression. In this paper, we propose a patch-based tissue classification method from MR images that...

Brain tissue segmentation using fuzzy clustering techniques.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Medical image segmentation is an essential step for most consequent image analysis tasks. Medical images can be segmented manually, but the accuracy of image segmentation using the automated segmentation algorithms is more when compared w...

Patient-specific early classification of multivariate observations.

International journal of data mining and bioinformatics
Early classification of time series has been receiving a lot of attention recently. In this paper we present a model, which we call the Early Classification Model (ECM), that allows for early, accurate and patient-specific classification of multivari...

Multiple ANN Recognizers for Adaptive Recognition of the Speech of Dysarthric Patients in AAL Systems.

Studies in health technology and informatics
People suffering from neuromuscular disorders are one of the main target groups of speech-controlled Ambient Assisted Living systems. However, the speech of these patients is often distorted because of the dysarthric symptoms of the disease. The dysa...