AIMC Topic: Multiple Sclerosis

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

Frontiers in immunology Feb 17, 2025
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 ...
Humans Artificial Intelligence Precision Medicine Multiple Sclerosis Patient Reported Outcome Measures Patient Participation
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Deep learning-based prediction of autoimmune diseases.

Scientific reports Feb 7, 2025
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 ...
Humans Neural Networks, Computer T-Lymphocytes Diabetes Mellitus, Type 1 Autoimmune Diseases Deep Learning Multiple Sclerosis ROC Curve Receptors, Antigen, T-Cell
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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 Jan 22, 2025
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...
Protein Interaction Maps Computational Biology Lipid Metabolism Genetic Markers Multiple Sclerosis Machine Learning Biomarkers Molecular Docking Simulation Humans Neural Networks, Computer
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AI-based assessment of longitudinal multiple sclerosis MRI: Strengths and weaknesses in clinical practice.

European journal of radiology Jan 18, 2025
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 ...
Female Reproducibility of Results Adult Artificial Intelligence Software Brain Longitudinal Studies Magnetic Resonance Imaging Multiple Sclerosis Sensitivity and Specificity Male Middle Aged Humans Image Interpretation, Computer-Assisted
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Differentiation between multiple sclerosis and neuromyelitis optic spectrum disorders with multilevel fMRI features: A machine learning analysis.

Scientific reports Jan 14, 2025
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...
Multiple Sclerosis Gray Matter Neuromyelitis Optica Adult Machine Learning Male Brain Middle Aged Female Support Vector Machine Humans Magnetic Resonance Imaging Diagnosis, Differential
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A density-based MS disease diagnosis model using the capuchin search algorithm and an ensemble of deep neural networks.

Scientific reports Dec 30, 2024
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...
Humans Neural Networks, Computer Magnetic Resonance Imaging Principal Component Analysis Multiple Sclerosis Algorithms Brain Image Processing, Computer-Assisted
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Enhancing classification of active and non-active lesions in multiple sclerosis: machine learning models and feature selection techniques.

BMC medical imaging Dec 20, 2024
INTRODUCTION: Gadolinium-based T1-weighted MRI sequence is the gold standard for the detection of active multiple sclerosis (MS) lesions. The performance of machine learning (ML) and deep learning (DL) models in the classification of active and non-a...
Male Deep Learning Magnetic Resonance Imaging Female Area Under Curve Adult Multiple Sclerosis Sensitivity and Specificity Humans Image Interpretation, Computer-Assisted Machine Learning
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Deep Learning techniques to detect and analysis of multiple sclerosis through MRI: A systematic literature review.

Computers in biology and medicine Dec 17, 2024
Deep learning (DL) techniques represent a rapidly advancing field within artificial intelligence, gaining significant prominence in the detection and analysis of various medical conditions through the analysis of medical data. This study presents a s...
Magnetic Resonance Imaging Multiple Sclerosis Image Interpretation, Computer-Assisted Humans Neural Networks, Computer Deep Learning
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A Context-Dependent CNN-Based Framework for Multiple Sclerosis Segmentation in MRI.

International journal of neural systems Dec 13, 2024
Despite several automated strategies for identification/segmentation of Multiple Sclerosis (MS) lesions in Magnetic Resonance Imaging (MRI) being developed, they consistently fall short when compared to the performance of human experts. This emphasiz...
Image Interpretation, Computer-Assisted Brain Magnetic Resonance Imaging Humans Multiple Sclerosis Neural Networks, Computer
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Structural-based uncertainty in deep learning across anatomical scales: Analysis in white matter lesion segmentation.

Computers in biology and medicine Nov 15, 2024
This paper explores uncertainty quantification (UQ) as an indicator of the trustworthiness of automated deep-learning (DL) tools in the context of white matter lesion (WML) segmentation from magnetic resonance imaging (MRI) scans of multiple sclerosi...
Magnetic Resonance Imaging Male Uncertainty Multiple Sclerosis Humans Deep Learning Female White Matter Image Processing, Computer-Assisted
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