AIMC Topic: Multiple Sclerosis

Clear Filters Showing 81 to 90 of 239 articles

Do people with multiple sclerosis perceive upper limb improvements from robotic-mediated therapy? A mixed methods study.

Multiple sclerosis and related disorders Sep 6, 2022
BACKGROUND: Robot-mediated training is increasingly considered as a rehabilitation intervention targeting upper limb disability. However, experiences of such an intervention have been rarely explored in the multiple sclerosis population. This mixed m...
Humans Treatment Outcome Activities of Daily Living Multiple Sclerosis Upper Extremity Robotics Exercise Therapy
View on PubMed DOI

Validation of a Denoising Method Using Deep Learning-Based Reconstruction to Quantify Multiple Sclerosis Lesion Load on Fast FLAIR Imaging.

AJNR. American journal of neuroradiology Jul 28, 2022
BACKGROUND AND PURPOSE: Accurate quantification of WM lesion load is essential for the care of patients with multiple sclerosis. We tested whether the combination of accelerated 3D-FLAIR and denoising using deep learning-based reconstruction could pr...
Multiple Sclerosis Image Interpretation, Computer-Assisted Humans Deep Learning Magnetic Resonance Imaging
View on PubMed DOI

Transformer-Based Deep-Learning Algorithm for Discriminating Demyelinating Diseases of the Central Nervous System With Neuroimaging.

Frontiers in immunology Jun 14, 2022
BACKGROUND: Differential diagnosis of demyelinating diseases of the central nervous system is a challenging task that is prone to errors and inconsistent reading, requiring expertise and additional examination approaches. Advancements in deep-learnin...
Aquaporin 4 Humans Neuromyelitis Optica Spinal Cord Deep Learning Neuroimaging Multiple Sclerosis
View on PubMed DOI

Role of artificial intelligence in MS clinical practice.

NeuroImage. Clinical May 28, 2022
Machine learning (ML) and its subset, deep learning (DL), are branches of artificial intelligence (AI) showing promising findings in the medical field, especially when applied to imaging data. Given the substantial role of MRI in the diagnosis and ma...
Machine Learning Algorithms Reproducibility of Results Deep Learning Humans Artificial Intelligence Multicenter Studies as Topic Multiple Sclerosis
View on PubMed DOI

Multiple sclerosis cortical lesion detection with deep learning at ultra-high-field MRI.

NMR in biomedicine Mar 31, 2022
Manually segmenting multiple sclerosis (MS) cortical lesions (CLs) is extremely time consuming, and past studies have shown only moderate inter-rater reliability. To accelerate this task, we developed a deep-learning-based framework (CLAIMS: Cortical...
Multiple Sclerosis Deep Learning Magnetic Resonance Imaging Humans Reproducibility of Results
View on PubMed DOI

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...
Magnetic Resonance Imaging Multiple Sclerosis Humans Artificial Intelligence
View on PubMed DOI

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 Glial Fibrillary Acidic Protein Humans Oligoclonal Bands Central Nervous System Diseases Biomarkers
View on PubMed DOI

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 ...
Disease Progression Deep Learning Humans Magnetic Resonance Imaging Multiple Sclerosis Artificial Intelligence
View on PubMed DOI

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...
Atrophy Corpus Callosum Magnetic Resonance Imaging Multiple Sclerosis Male Middle Aged Deep Learning Image Processing, Computer-Assisted Reproducibility of Results Adult Humans Female
View on PubMed DOI

Deep Learning and the OPERA Trials for Multiple Sclerosis.

Radiology Dec 14, 2021
Multiple Sclerosis, Relapsing-Remitting Antibodies, Monoclonal, Humanized Multiple Sclerosis Humans Deep Learning
View on PubMed DOI
Popular Topics
Recent Journals