AIMC Topic: Multiple Sclerosis
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A Vision-Based Framework for Predicting Multiple Sclerosis and Parkinson's Disease Gait Dysfunctions-A Deep Learning Approach.
IEEE journal of biomedical and health informatics
Jan 4, 2023
This study examined the effectiveness of a vision-based framework for multiple sclerosis (MS) and Parkinson's disease (PD) gait dysfunction prediction. We collected gait video data from multi-view digital cameras during self-paced walking from MS, PD...
A dense residual U-net for multiple sclerosis lesions segmentation from multi-sequence 3D MR images.
International journal of medical informatics
Dec 21, 2022
Multiple Sclerosis (MS) is an autoimmune disease that causes brain and spinal cord lesions, which magnetic resonance imaging (MRI) can detect and characterize. Recently, deep learning methods have achieved remarkable results in the automated segmenta...
Minimizing the effect of white matter lesions on deep learning based tissue segmentation for brain volumetry.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Dec 13, 2022
Automated methods for segmentation-based brain volumetry may be confounded by the presence of white matter (WM) lesions, which introduce abnormal intensities that can alter the classification of not only neighboring but also distant brain tissue. The...
Feasibility and Safety of a Powered Exoskeleton for Balance Training for People Living with Multiple Sclerosis: A Single-Group Preliminary Study (Rapper III).
Journal of rehabilitation medicine
Dec 9, 2022
OBJECTIVE: To evaluate the feasibility, usability, safety, and potential health benefits of using an exoskeleton device for rehabilitation of people living with multiple sclerosis.
3-Dimensional Immunostaining and Automated Deep-Learning Based Analysis of Nerve Degeneration.
International journal of molecular sciences
Nov 26, 2022
Multiple sclerosis (MS) is an autoimmune and neurodegenerative disease driven by inflammation and demyelination in the brain, spinal cord, and optic nerve. Optic neuritis, characterized by inflammation and demyelination of the optic nerve, is a sympt...
Diagnostic performance of artificial intelligence in multiple sclerosis: a systematic review and meta-analysis.
Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
Oct 27, 2022
BACKGROUND: The expansion of the availability of advanced imaging methods needs more time, expertise, and resources which is in contrast to the primary goal of the imaging techniques. To overcome most of these difficulties, artificial intelligence (A...
Prior optic neuritis detection on peripapillary ring scans using deep learning.
Annals of clinical and translational neurology
Oct 25, 2022
BACKGROUND: The diagnosis of multiple sclerosis (MS) requires demyelinating events that are disseminated in time and space. Peripapillary retinal nerve fiber layer (pRNFL) thickness as measured by optical coherence tomography (OCT) distinguishes eyes...
Multiple Sclerosis Diagnosis Using Machine Learning and Deep Learning: Challenges and Opportunities.
Sensors (Basel, Switzerland)
Oct 16, 2022
Multiple Sclerosis (MS) is a disease that impacts the central nervous system (CNS), which can lead to brain, spinal cord, and optic nerve problems. A total of 2.8 million are estimated to suffer from MS. Globally, a new case of MS is reported every f...
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 ...
Evaluation of Disability Progression in Multiple Sclerosis via Magnetic-Resonance-Based Deep Learning Techniques.
International journal of molecular sciences
Sep 13, 2022
Short-term disability progression was predicted from a baseline evaluation in patients with multiple sclerosis (MS) using their three-dimensional T1-weighted (3DT1) magnetic resonance images (MRI). One-hundred-and-eighty-one subjects diagnosed with M...
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