AIMC Topic: Multiple Sclerosis

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AI in Radiology: Where are we today in Multiple Sclerosis Imaging?

RoFo : Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin Jul 8, 2020
BACKGROUND:  MR imaging is an essential component in managing patients with Multiple sclerosis (MS). This holds true for the initial diagnosis as well as for assessing the clinical course of MS. In recent years, a growing number of computer tools wer...
Humans Image Processing, Computer-Assisted Magnetic Resonance Imaging Multiple Sclerosis Cost of Illness Artificial Intelligence Algorithms Prognosis
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Artificial intelligence to predict clinical disability in patients with multiple sclerosis using FLAIR MRI.

Diagnostic and interventional imaging Jul 7, 2020
PURPOSE: The purpose of this study was to create an algorithm that combines multiple machine-learning techniques to predict the expanded disability status scale (EDSS) score of patients with multiple sclerosis at two years solely based on age, sex an...
Predictive Value of Tests Multiple Sclerosis Artificial Intelligence Brain Magnetic Resonance Imaging Humans Neural Networks, Computer
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Multiple sclerosis cortical and WM lesion segmentation at 3T MRI: a deep learning method based on FLAIR and MP2RAGE.

NeuroImage. Clinical Jun 30, 2020
The presence of cortical lesions in multiple sclerosis patients has emerged as an important biomarker of the disease. They appear in the earliest stages of the illness and have been shown to correlate with the severity of clinical symptoms. However, ...
Magnetic Resonance Imaging Humans Multiple Sclerosis Deep Learning White Matter Contrast Media
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Functional recovery in multiple sclerosis patients undergoing rehabilitation programs is associated with plasma levels of hemostasis inhibitors.

Multiple sclerosis and related disorders Jun 20, 2020
BACKGROUND: Increasing evidence for contribution of hemostasis components in multiple sclerosis (MS) has been reported. Hemostasis protein inhibitors display key regulatory roles, extending to regulation of innate immune response and inflammation, an...
Gait Humans Exercise Therapy Robotics Multiple Sclerosis Hemostasis Walking
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Machine Learning and Multiparametric Brain MRI to Differentiate Hereditary Diffuse Leukodystrophy with Spheroids from Multiple Sclerosis.

Journal of neuroimaging : official journal of the American Society of Neuroimaging May 26, 2020
BACKGROUND AND PURPOSE: Hereditary diffuse leukoencephalopathy with spheroids (HDLS) and multiple sclerosis (MS) are demyelinating and neurodegenerative disorders that can be hard to distinguish clinically and radiologically. HDLS is a rare disorder ...
Male Female Middle Aged Humans Diagnosis, Differential Aged Magnetic Resonance Imaging Leukoencephalopathies Machine Learning Multiple Sclerosis Adult Brain
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Deep learning segmentation of gadolinium-enhancing lesions in multiple sclerosis.

Multiple sclerosis (Houndmills, Basingstoke, England) May 22, 2020
OBJECTIVE: The aim of this study is to assess the performance of deep learning convolutional neural networks (CNNs) in segmenting gadolinium-enhancing lesions using a large cohort of multiple sclerosis (MS) patients.
Humans Neural Networks, Computer Deep Learning Magnetic Resonance Imaging Multiple Sclerosis Gadolinium
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A self-administered, artificial intelligence (AI) platform for cognitive assessment in multiple sclerosis (MS).

BMC neurology May 18, 2020
BACKGROUND: Cognitive impairment is common in patients with multiple sclerosis (MS). Accurate and repeatable measures of cognition have the potential to be used as markers of disease activity.
Neuropsychological Tests Male Middle Aged Case-Control Studies Adolescent Reproducibility of Results Humans Cognitive Dysfunction Young Adult Multiple Sclerosis Adult Artificial Intelligence Learning Female
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A new lower limb portable exoskeleton for gait assistance in neurological patients: a proof of concept study.

Journal of neuroengineering and rehabilitation May 6, 2020
BACKGROUND: Few portable exoskeletons following the assist-as-needed concept have been developed for patients with neurological disorders. Thus, the main objectives of this proof-of-concept study were 1) to explore the safety and feasibility of an ex...
Female Adult Cross-Sectional Studies Humans Algorithms Multiple Sclerosis Proof of Concept Study Exoskeleton Device Male Middle Aged Robotics Physical Therapy Modalities Stroke Rehabilitation Gait Disorders, Neurologic
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Deep learning with diffusion basis spectrum imaging for classification of multiple sclerosis lesions.

Annals of clinical and translational neurology Apr 18, 2020
OBJECTIVE: Multiple sclerosis (MS) lesions are heterogeneous with regard to inflammation, demyelination, axonal injury, and neuronal loss. We previously developed a diffusion basis spectrum imaging (DBSI) technique to better address MS lesion heterog...
Gray Matter Humans White Matter Female Diffusion Tensor Imaging Diffusion Magnetic Resonance Imaging Aged Middle Aged Adult Deep Learning Sensitivity and Specificity Multiple Sclerosis Male
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Machine learning analysis of motor evoked potential time series to predict disability progression in multiple sclerosis.

BMC neurology Mar 21, 2020
BACKGROUND: Evoked potentials (EPs) are a measure of the conductivity of the central nervous system. They are used to monitor disease progression of multiple sclerosis patients. Previous studies only extracted a few variables from the EPs, which are ...
Datasets as Topic Belgium Female Evoked Potentials, Motor Male Logistic Models Disease Progression Disability Evaluation Multiple Sclerosis Humans Machine Learning
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