AIMC Topic: Multiple Sclerosis
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New approaches to lesion assessment in multiple sclerosis.
Current opinion in neurology
Aug 1, 2025
PURPOSE OF REVIEW: To summarize recent advancements in artificial intelligence-driven lesion segmentation and novel neuroimaging modalities that enhance the identification and characterization of multiple sclerosis (MS) lesions, emphasizing their imp...
Segmentation with artificial intelligence and automated calculation of the corpus callosum index in multiple sclerosis.
Saudi medical journal
Jun 1, 2025
OBJECTIVES: To determine the corpus callosum index (CCI) differences between chronic phase multiple sclerosis (MS) patients and healthy individuals and to evaluate the corpus callosum segmentation in MS patients using artificial intelligence technolo...
Evolution of Cortical Lesions and Function-Specific Cognitive Decline in People With Multiple Sclerosis.
Neurology
Jun 1, 2025
BACKGROUND AND OBJECTIVES: Cortical lesions in multiple sclerosis (MS) severely affect cognition, but their longitudinal evolution and impact on specific cognitive functions remain understudied. This study investigates the evolution of function-speci...
Deep learning for multiple sclerosis lesion classification and stratification using MRI.
Computers in biology and medicine
Jun 1, 2025
BACKGROUND AND OBJECTIVE: Multiple sclerosis (MS) is a chronic neurological disease characterized by inflammation, demyelination, and neurodegeneration within the central nervous system. Conventional magnetic resonance imaging (MRI) techniques often ...
An Intelligent Model of Segmentation and Classification Using Enhanced Optimization-Based Attentive Mask RCNN and Recurrent MobileNet With LSTM for Multiple Sclerosis Types With Clinical Brain MRI.
NMR in biomedicine
Jun 1, 2025
In healthcare sector, magnetic resonance imaging (MRI) images are taken for multiple sclerosis (MS) assessment, classification, and management. However, interpreting an MRI scan requires an exceptional amount of skill because abnormalities on scans a...
Whole Brain 3D T1 Mapping in Multiple Sclerosis Using Standard Clinical Images Compared to MP2RAGE and MR Fingerprinting.
NMR in biomedicine
Jun 1, 2025
Quantitative T1 and T2 mapping is a useful tool to assess properties of healthy and diseased tissues. However, clinical diagnostic imaging remains dominated by relaxation-weighted imaging without direct collection of relaxation maps. Dedicated resear...
Predicting 5-Year EDSS in Multiple Sclerosis with LSTM Networks: A Deep Learning Approach to Disease Progression.
Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
Jun 1, 2025
BACKROUNDS: Multiple Sclerosis (MS) is a neurodegerative disease that is common worldwide, has no definitive cure yet, and negatively affects the individual's quality of life due to disease-related disability. Predicting disability in MS is difficult...
Performance of machine learning models for predicting high-severity symptoms in multiple sclerosis.
Scientific reports
May 25, 2025
Current care in multiple sclerosis (MS) primarily relies on infrequently obtained data such as magnetic resonance imaging, clinical laboratory tests or clinical history, resulting in subtle changes that may occur between visits being missed. Mobile t...
Towards Multiple Sclerosis Personalised Interventions Based on Real-World Predictive Analytics.
Studies in health technology and informatics
May 15, 2025
This study investigates the use of machine learning (ML) techniques to predict intervention response in patients with Multiple Sclerosis (PwMS) using real-world data from wearable devices. Data from 27 PwMS, monitored over two months were analyzed wi...
Advancing the Use of Longitudinal Electronic Health Records: Tutorial for Uncovering Real-World Evidence in Chronic Disease Outcomes.
Journal of medical Internet research
May 12, 2025
Managing chronic diseases requires ongoing monitoring of disease activity and therapeutic responses to optimize treatment plans. With the growing availability of disease-modifying therapies, it is crucial to investigate comparative effectiveness and ...
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