AIMC Topic: Multiple Sclerosis

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Artificial intelligence in the diagnosis of multiple sclerosis: A systematic review.

Multiple sclerosis and related disorders Feb 7, 2022
BACKGROUND: In recent years Artificial intelligence (AI) techniques are rapidly evolving into clinical practices such as diagnosis and prognosis processes, assess treatment effectiveness, and monitoring of diseases. The previous studies showed intere...
Artificial Intelligence Magnetic Resonance Imaging Multiple Sclerosis Humans
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Determination of CSF GFAP, CCN5, and vWF Levels Enhances the Diagnostic Accuracy of Clinically Defined MS From Non-MS Patients With CSF Oligoclonal Bands.

Frontiers in immunology Feb 4, 2022
BACKGROUND: Inclusion of cerebrospinal fluid (CSF) oligoclonal IgG bands (OCGB) in the revised McDonald criteria increases the sensitivity of diagnosis when dissemination in time (DIT) cannot be proven. While OCGB negative patients are unlikely to de...
Multiple Sclerosis Oligoclonal Bands Glial Fibrillary Acidic Protein Central Nervous System Diseases Humans Biomarkers
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A Deep Learning Approach to Predicting Disease Progression in Multiple Sclerosis Using Magnetic Resonance Imaging.

Investigative radiology Jan 31, 2022
OBJECTIVES: Magnetic resonance imaging (MRI) is an important tool for diagnosis and monitoring of disease course in multiple sclerosis (MS). However, its prognostic value for predicting disease worsening is still being debated. The aim of this study ...
Humans Artificial Intelligence Disease Progression Multiple Sclerosis Deep Learning Magnetic Resonance Imaging
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Automatic deep learning multicontrast corpus callosum segmentation in multiple sclerosis.

Journal of neuroimaging : official journal of the American Society of Neuroimaging Jan 26, 2022
BACKGROUND AND PURPOSE: Corpus callosum (CC) atrophy is predictive of future disability in multiple sclerosis (MS). However, current segmentation methods are either labor- or computationally intensive. We therefore developed an automated deep learnin...
Magnetic Resonance Imaging Multiple Sclerosis Atrophy Deep Learning Image Processing, Computer-Assisted Corpus Callosum Female Humans Reproducibility of Results Male Adult Middle Aged
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Deep Learning and the OPERA Trials for Multiple Sclerosis.

Radiology Dec 14, 2021
Multiple Sclerosis Multiple Sclerosis, Relapsing-Remitting Deep Learning Antibodies, Monoclonal, Humanized Humans
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Joint MRI T1 Unenhancing and Contrast-enhancing Multiple Sclerosis Lesion Segmentation with Deep Learning in OPERA Trials.

Radiology Dec 14, 2021
Background Deep learning-based segmentation could facilitate rapid and reproducible T1 lesion load assessments, which is crucial for disease management in multiple sclerosis (MS). T1 unenhancing and contrast-enhancing lesions in MS are those that enh...
Contrast Media Magnetic Resonance Imaging Immunologic Factors Deep Learning Antibodies, Monoclonal, Humanized Multiple Sclerosis Datasets as Topic Adult Male Female Humans Retrospective Studies
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DeepLesionBrain: Towards a broader deep-learning generalization for multiple sclerosis lesion segmentation.

Medical image analysis Nov 27, 2021
Recently, segmentation methods based on Convolutional Neural Networks (CNNs) showed promising performance in automatic Multiple Sclerosis (MS) lesions segmentation. These techniques have even outperformed human experts in controlled evaluation condit...
Brain Deep Learning Multiple Sclerosis Humans Neural Networks, Computer Image Processing, Computer-Assisted
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Effects of Robot-Assisted Gait Training in Patients With Multiple Sclerosis: A Single-Blinded Randomized Controlled Study.

American journal of physical medicine & rehabilitation Oct 21, 2021
OBJECTIVE: This study aims to evaluate and compare the effects of conventional and robot-assisted gait training (RAGT) programs on fatigue, mood, and quality of life in patients with multiple sclerosis who have fatigue.
Fatigue Gait Disorders, Neurologic Exercise Therapy Multiple Sclerosis Robotics Gait Humans Quality of Life
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Opportunities for Understanding MS Mechanisms and Progression With MRI Using Large-Scale Data Sharing and Artificial Intelligence.

Neurology Oct 4, 2021
Patients with multiple sclerosis (MS) have heterogeneous clinical presentations, symptoms, and progression over time, making MS difficult to assess and comprehend in vivo. The combination of large-scale data sharing and artificial intelligence create...
Artificial Intelligence Algorithms Humans Information Dissemination Magnetic Resonance Imaging Multiple Sclerosis
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MTANS: Multi-Scale Mean Teacher Combined Adversarial Network with Shape-Aware Embedding for Semi-Supervised Brain Lesion Segmentation.

NeuroImage Sep 8, 2021
The annotation of brain lesion images is a key step in clinical diagnosis and treatment of a wide spectrum of brain diseases. In recent years, segmentation methods based on deep learning have gained unprecedented popularity, leveraging a large amount...
Deep Learning Research Design Datasets as Topic Magnetic Resonance Imaging Brain Humans Stroke Brain Neoplasms Students Multiple Sclerosis
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