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Multiple Sclerosis

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Over-ground walking or robot-assisted gait training in people with .multiple sclerosis: does the effect depend on baseline walking speed and disease related disabilities? A systematic review and meta-regression.

BMC neurology
BACKGROUND: It was suggested that robot-assisted gait training (RAGT) should not be routinely provided to disabled patients in place of conventional over-ground walking training (CGT). There exist several randomised controlled trials reporting on RAG...

Classification of radiologically isolated syndrome and clinically isolated syndrome with machine-learning techniques.

European journal of neurology
BACKGROUND AND PURPOSE: The unanticipated detection by magnetic resonance imaging (MRI) in the brain of asymptomatic subjects of white matter lesions suggestive of multiple sclerosis (MS) has been named radiologically isolated syndrome (RIS). As the ...

One-shot domain adaptation in multiple sclerosis lesion segmentation using convolutional neural networks.

NeuroImage. Clinical
In recent years, several convolutional neural network (CNN) methods have been proposed for the automated white matter lesion segmentation of multiple sclerosis (MS) patient images, due to their superior performance compared with those of other state-...

Computer Aided Diagnosis System for multiple sclerosis disease based on phase to amplitude coupling in covert visual attention.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Computer Aided Diagnosis (CAD) techniques have widely been used in research to detect the neurological abnormalities and improve the consistency of diagnosis and treatment in medicine. In this study, a new CAD system based o...

Planar conformity of movements in 3D reaching tasks for persons with Multiple Sclerosis.

Human movement science
Robotic rehabilitation of the upper limb has been proved beneficial for people with Multiple Sclerosis (MS). In order to provide task-specific therapy for MS, given its complex impairing nature, it is desired to take advantage of the robots' ability ...

Predicting conversion from clinically isolated syndrome to multiple sclerosis-An imaging-based machine learning approach.

NeuroImage. Clinical
Magnetic resonance imaging (MRI) scans play a pivotal role in the evaluation of patients presenting with a clinically isolated syndrome (CIS), as these may depict brain lesions suggestive of an inflammatory cause. We hypothesized that it is possible ...

Automatic segmentation of the spinal cord and intramedullary multiple sclerosis lesions with convolutional neural networks.

NeuroImage
The spinal cord is frequently affected by atrophy and/or lesions in multiple sclerosis (MS) patients. Segmentation of the spinal cord and lesions from MRI data provides measures of damage, which are key criteria for the diagnosis, prognosis, and long...

Machine-learning based lipid mediator serum concentration patterns allow identification of multiple sclerosis patients with high accuracy.

Scientific reports
Based on increasing evidence suggesting that MS pathology involves alterations in bioactive lipid metabolism, the present analysis was aimed at generating a complex serum lipid-biomarker. Using unsupervised machine-learning, implemented as emergent s...

Machine Learning EEG to Predict Cognitive Functioning and Processing Speed Over a 2-Year Period in Multiple Sclerosis Patients and Controls.

Brain topography
Event-related potentials (ERPs) show promise to be objective indicators of cognitive functioning. The aim of the study was to examine if ERPs recorded during an oddball task would predict cognitive functioning and information processing speed in Mult...

Harnessing electronic medical records to advance research on multiple sclerosis.

Multiple sclerosis (Houndmills, Basingstoke, England)
BACKGROUND: Electronic medical records (EMR) data are increasingly used in research, but no studies have yet evaluated similarity between EMR and research-quality data and between characteristics of an EMR multiple sclerosis (MS) population and known...