AIMC Topic: Multiple Sclerosis
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Computer Aided Diagnosis System for multiple sclerosis disease based on phase to amplitude coupling in covert visual attention.
Computer methods and programs in biomedicine
Nov 24, 2018
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
Nov 10, 2018
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
Nov 5, 2018
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
Oct 6, 2018
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
Oct 5, 2018
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
Jan 29, 2018
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)
Jan 9, 2018
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...
Determination of Seminal Concentration of Fingolimod and Fingolimod-Phosphate in Multiple Sclerosis Patients Receiving Chronic Treatment With Fingolimod.
Clinical pharmacology in drug development
Dec 19, 2017
The safety profile of fingolimod 0.5 mg, approved therapy for relapsing multiple sclerosis, is well established in clinical and real-world studies. As fingolimod is teratogenic in rats, it was considered important to assess the concentrations of fing...
Robotics in Biomedical and Healthcare Engineering.
Journal of healthcare engineering
Aug 28, 2017
Machine-Learned Data Structures of Lipid Marker Serum Concentrations in Multiple Sclerosis Patients Differ from Those in Healthy Subjects.
International journal of molecular sciences
Jun 7, 2017
Lipid metabolism has been suggested to be a major pathophysiological mechanism of multiple sclerosis (MS). With the increasing knowledge about lipid signaling, acquired data become increasingly complex making bioinformatics necessary in lipid researc...
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