AIMC Topic: Demyelinating Diseases

Clear Filters Showing 1 to 6 of 6 articles

Machine learning-driven diagnosis of multiple sclerosis from whole blood transcriptomics.

Brain, behavior, and immunity Aug 2, 2024
Multiple sclerosis (MS) is a neurological disorder characterized by immune dysregulation. It begins with a first clinical manifestation, a clinically isolated syndrome (CIS), which evolves to definite MS in case of further clinical and/or neuroradiol...
Female Adult Male Machine Learning Algorithms Transcriptome Multiple Sclerosis Demyelinating Diseases Middle Aged Gene Expression Profiling Humans
View on PubMed DOI

Predicting the conversion from clinically isolated syndrome to multiple sclerosis: An explainable machine learning approach.

Multiple sclerosis and related disorders Apr 9, 2024
INTRODUCTION: Predicting the conversion of clinically isolated syndrome (CIS) to clinically definite multiple sclerosis (CDMS) is critical to personalizing treatment planning and benefits for patients. The aim of this study is to develop an explainab...
Humans Machine Learning Female Follow-Up Studies Magnetic Resonance Imaging Middle Aged Demyelinating Diseases Disease Progression Multiple Sclerosis Adult Mexico Male
View on PubMed DOI

Machine learning based white matter models with permeability: An experimental study in cuprizone treated in-vivo mouse model of axonal demyelination.

NeuroImage Oct 6, 2020
The intra-axonal water exchange time (τ), a parameter associated with axonal permeability, could be an important biomarker for understanding and treating demyelinating pathologies such as Multiple Sclerosis. Diffusion-Weighted MRI (DW-MRI) is sensiti...
Demyelinating Diseases Diffusion Magnetic Resonance Imaging Corpus Callosum Monte Carlo Method White Matter Monoamine Oxidase Inhibitors Cuprizone Mice Disease Models, Animal Axons Microscopy, Electron Permeability Computer Simulation Animals Image Processing, Computer-Assisted Machine Learning
View on PubMed DOI

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

European journal of neurology Mar 1, 2019
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 ...
Demyelinating Diseases Machine Learning Magnetic Resonance Imaging Male Brain Humans Bayes Theorem Middle Aged Gray Matter Female White Matter Image Processing, Computer-Assisted Multiple Sclerosis Adult
View on PubMed DOI

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 ...
Multiple Sclerosis Demyelinating Diseases Cohort Studies Humans Middle Aged Female Magnetic Resonance Imaging Disease Progression Machine Learning Adult Predictive Value of Tests Prospective Studies Male
View on PubMed DOI

Predicting outcome in clinically isolated syndrome using machine learning.

NeuroImage. Clinical Dec 4, 2014
We aim to determine if machine learning techniques, such as support vector machines (SVMs), can predict the occurrence of a second clinical attack, which leads to the diagnosis of clinically-definite Multiple Sclerosis (CDMS) in patients with a clini...
Image Interpretation, Computer-Assisted Sensitivity and Specificity Female Demyelinating Diseases Male Humans Young Adult Middle Aged Disease Progression Magnetic Resonance Imaging Retrospective Studies Adult Support Vector Machine Multiple Sclerosis
View on PubMed DOI
Popular Topics
Recent Journals