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Automatic Detection of Multiple Sclerosis Using Genomic Expression
This study leverages microarray data together with statistical and machine learning techniques to investigate the best set of biomarkers in...
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A Binning Approach for Predicting Long-Term Prognosis in Multiple Sclerosis
Multiple sclerosis is a complex disease with a highly heterogeneous disease course. Early treatment of multiple sclerosis patients could delay or...
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A machine learning approach for multiple sclerosis diagnosis through Detecron Architecture
Multiple sclerosis is a prevalent inflammatory disease affecting the central nervous system, leading to demyelination. Neuroradiology relies on...
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Deep Survival Analysis in Multiple Sclerosis
Multiple Sclerosis (MS) is the most frequent non-traumatic debilitating neurological disease. It is usually diagnosed based on clinical observations...
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Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries 8th International Workshop, BrainLes 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Revised Selected Papers, Part II
This two volume-set LNCS 13769 and LNCS 14092 constitutes the refereed proceedings of the 8th International MICCAI Brainlesion Workshop, BrainLes...
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Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries 8th International Workshop, BrainLes 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Revised Selected Papers, Part I
This book constitutes the refereed proceedings of the 8th International MICCAI Brainlesion Workshop, BrainLes 2022, as well as the Brain Tumor...
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The Viewpoint of Informal Carers of People with Multiple Sclerosis in Digital Health Research: A Sco** Review
Multiple sclerosis (MS) is a common neurological disease that can impact not only individuals diagnosed with the condition but also their informal...
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Unsupervised Brain MRI Anomaly Detection for Multiple Sclerosis Classification
Supervised deep learning has been widely applied in medical imaging to detect multiple sclerosis. However, it is difficult to have perfectly...
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Machine learning in the identification of phenotypes of multiple sclerosis patients
Multiple sclerosis (MS) is a complex disease affecting the central nervous system, mainly in young adults. Even though there is no cure for this...
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Deep learning and classic machine learning models in the automatic diagnosis of multiple sclerosis using retinal vessels
This study aims to automatically detect multiple sclerosis (MS) in terms of the changes in retinal vessels using Scanning laser ophthalmoscopy (SLO)...
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Visual Modeling of Multiple Sclerosis Patient Pathways: The Healthcare Workers’ Perspectives
Multiple Sclerosis (MS) necessitates tailored care along intricate pathways throughout a patient's lifetime. Visualizing these pathways enhances the...
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DeepCONN: patch-wise deep convolutional neural networks for the segmentation of multiple sclerosis brain lesions
Segmentation is a critical process for examining Multiple Sclerosis (MS) brain lesions for diagnosis, follow-up, and prognosis of the disease. The...
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EEG-based mental workload estimation of multiple sclerosis patients
The amount of mental capacity required by individuals to complete any task is defined as mental workload. It is important to determine the...
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Ant Colony Optimization with BrainSeg3D Protocol for Multiple Sclerosis Lesion Detection
Magnetic resonance imaging (MRI) has quickly established itself as the reference imaging tool for the management of patients suffering from multiple...
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Detection of Features Regions of Syndrome in Multiple Sclerosis on MRI
In this paper regions of multiple sclerosis on radiological images are detected by model of convolutional neural network. The specific image...
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CoactSeg: Learning from Heterogeneous Data for New Multiple Sclerosis Lesion Segmentation
New lesion segmentation is essential to estimate the disease progression and therapeutic effects during multiple sclerosis (MS) clinical treatments....
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A Comparative Study of Explainable AI models in the Assessment of Multiple Sclerosis
Multiple Sclerosis (MS) is characterized by complex and heterogeneous nature and as a result, there’s currently no cure. Medications can help control...
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MRI contrast enhancement using singular value decomposition and brightness preserving dynamic fuzzy histogram equalization applied to multiple sclerosis patients
Multiple sclerosis (MS) is a neurological disease affecting the brain and spinal cord, which leads to several troubles such as numbness, memory...
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Machine Learning to Diagnose Neurodegenerative Multiple Sclerosis Disease
Multiple sclerosis (MS) is a progressive neurodegenerative disease with a wide range of symptoms, making it difficult to diagnose and monitor....
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Temporally Adjustable Longitudinal Fluid-Attenuated Inversion Recovery MRI Estimation / Synthesis for Multiple Sclerosis
Multiple Sclerosis (MS) is a chronic progressive neurological disease characterized by the development of lesions in the white matter of the brain....