AIMC Topic: Multiple Sclerosis, Relapsing-Remitting
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Relevance of choroid plexus volumes in multiple sclerosis.
Fluids and barriers of the CNS
May 8, 2025
BACKGROUND: The choroid plexus (ChP) plays a pivotal role in inflammatory processes that occur in multiple sclerosis (MS). The enlargement of the ChP in relapsing-remitting multiple sclerosis (RRMS) is considered to be an indication of disease activi...
Enhanced choroid plexus segmentation with 3D UX-Net and its association with disease progression in multiple sclerosis.
Multiple sclerosis and related disorders
Jun 28, 2024
BACKGROUND: The choroid plexus (CP) is suggested to be closely associated with the neuroinflammation of multiple sclerosis (MS). Segmentation based on deep learning (DL) could facilitate rapid and reproducible volume assessment of the CP, which is cr...
Machine Learning Analysis Using RNA Sequencing to Distinguish Neuromyelitis Optica from Multiple Sclerosis and Identify Therapeutic Candidates.
The Journal of molecular diagnostics : JMD
Mar 22, 2024
This study aims to identify RNA biomarkers distinguishing neuromyelitis optica (NMO) from relapsing-remitting multiple sclerosis (RRMS) and explore potential therapeutic applications leveraging machine learning (ML). An ensemble approach was develope...
Interpretable and Intuitive Machine Learning Approaches for Predicting Disability Progression in Relapsing-Remitting Multiple Sclerosis Based on Clinical and Gray Matter Atrophy Indicators.
Academic radiology
Feb 29, 2024
RATIONALE AND OBJECTIVES: To investigate whether clinical and gray matter (GM) atrophy indicators can predict disability in relapsing-remitting multiple sclerosis (RRMS) and to enhance the interpretability and intuitiveness of a predictive machine le...
Diagnosis of multiple sclerosis using optical coherence tomography supported by explainable artificial intelligence.
Eye (London, England)
Jan 31, 2024
BACKGROUND/OBJECTIVES: Study of retinal structure based on optical coherence tomography (OCT) data can facilitate early diagnosis of relapsing-remitting multiple sclerosis (RRMS). Although artificial intelligence can provide highly reliable diagnoses...
Estimating individual treatment effect on disability progression in multiple sclerosis using deep learning.
Nature communications
Sep 26, 2022
Disability progression in multiple sclerosis remains resistant to treatment. The absence of a suitable biomarker to allow for phase 2 clinical trials presents a high barrier for drug development. We propose to enable short proof-of-concept trials by ...
Deep Learning and the OPERA Trials for Multiple Sclerosis.
Radiology
Dec 14, 2021
Interpretable deep learning as a means for decrypting disease signature in multiple sclerosis.
Journal of neural engineering
Jul 19, 2021
The mechanisms driving multiple sclerosis (MS) are still largely unknown, calling for new methods allowing to detect and characterize tissue degeneration since the early stages of the disease. Our aim is to decrypt the microstructural signatures of t...
Differentiation between multiple sclerosis and neuromyelitis optica spectrum disorders by multiparametric quantitative MRI using convolutional neural network.
Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
Mar 11, 2021
Multiple sclerosis and neuromyelitis optica spectrum disorders are both neuroinflammatory diseases and have overlapping clinical manifestations. We developed a convolutional neural network model that differentiates between the two based on magnetic r...
Prediction of disease progression and outcomes in multiple sclerosis with machine learning.
Scientific reports
Dec 3, 2020
Multiple Sclerosis is a chronic inflammatory disease, affecting the Central Nervous System and leading to irreversible neurological damage, such as long term functional impairment and disability. It has no cure and the symptoms vary widely, depending...
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