AIMC Topic: Multiple Sclerosis

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Monitoring multiple sclerosis: digital and fluid phase biomarkers.

Current opinion in neurology
PURPOSE OF REVIEW: Monitoring of disease activity and treatment response in multiple sclerosis (MS) currently relies on the integration of qualitative clinical and radiological data that is of limited predictive value. An array of quantitative digita...

Machine Learning Methods for Classifying Multiple Sclerosis and Alzheimer's Disease Using Genomic Data.

International journal of molecular sciences
Complex diseases pose challenges in prediction due to their multifactorial and polygenic nature. This study employed machine learning (ML) to analyze genomic data from the UK Biobank, aiming to predict the genomic predisposition to complex diseases l...

Artificial intelligence versus neurologists: A comparative study on multiple sclerosis expertise.

Clinical neurology and neurosurgery
INTRODUCTION: Multiple sclerosis (MS) is an autoimmune neurodegenerative disease affecting the central nervous system. MS diagnosis is complex, requiring magnetic resonance imaging and cerebrospinal fluid analysis due to the lack of definitive biomar...

Artificial intelligence and science of patient input: a perspective from people with multiple sclerosis.

Frontiers in immunology
Artificial intelligence (AI) can play a vital role in achieving a shift towards predictive, preventive, and personalized medicine, provided we are guided by the science with and of patient input. Patient-reported outcome measures (PROMs) represent a ...

Deep learning-based prediction of autoimmune diseases.

Scientific reports
Autoimmune Diseases are a complex group of diseases caused by the immune system mistakenly attacking body tissues. Their etiology involves multiple factors such as genetics, environmental factors, and abnormalities in immune cells, making prediction ...

Advancing Optical Coherence Tomography Diagnostic Capabilities: Machine Learning Approaches to Detect Autoimmune Inflammatory Diseases.

Journal of neuro-ophthalmology : the official journal of the North American Neuro-Ophthalmology Society
BACKGROUND: In many parts of the world including India, the prevalence of autoimmune inflammatory diseases such as neuromyelitis optica spectrum disorders (NMOSD), myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD), and multiple ...

Identification of lipid metabolism-related gene markers and construction of a diagnostic model for multiple sclerosis: An integrated analysis by bioinformatics and machine learning.

Analytical biochemistry
BACKGROUND: Multiple sclerosis (MS) is an autoimmune inflammatory disorder that causes neurological disability. Dysregulated lipid metabolism contributes to the pathogenesis of MS. This study aimed to identify lipid metabolism-related gene markers an...

AI-based assessment of longitudinal multiple sclerosis MRI: Strengths and weaknesses in clinical practice.

European journal of radiology
OBJECTIVES: In Multiple Sclerosis (MS) cerebral MRI is essential for disease and treatment monitoring. For this purpose, software solutions are available to support the radiologist with image interpretation and reporting of follow up imaging. Aim of ...

Differentiation between multiple sclerosis and neuromyelitis optic spectrum disorders with multilevel fMRI features: A machine learning analysis.

Scientific reports
The conventional statistical approach for analyzing resting state functional MRI (rs-fMRI) data struggles to accurately distinguish between patients with multiple sclerosis (MS) and those with neuromyelitis optic spectrum disorders (NMOSD), highlight...

A density-based MS disease diagnosis model using the capuchin search algorithm and an ensemble of deep neural networks.

Scientific reports
Multiple sclerosis (MS) is a severe brain disease that permanently destroys brain cells, impacting vision, balance, muscle control, and daily activity. This research employs a weighted combination of deep neural networks and optimization techniques f...