AIMC Topic: Multiple Sclerosis
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Differentiation between multiple sclerosis and neuromyelitis optica spectrum disorder using a deep learning model.
Scientific reports
Jul 19, 2023
Multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD) are autoimmune inflammatory disorders of the central nervous system (CNS) with similar characteristics. The differential diagnosis between MS and NMOSD is critical for initiat...
Artificial intelligence and multiple sclerosis: ChatGPT model.
Multiple sclerosis and related disorders
Jun 20, 2023
The macular retinal ganglion cell layer as a biomarker for diagnosis and prognosis in multiple sclerosis: A deep learning approach.
Acta ophthalmologica
Jun 10, 2023
PURPOSE: The macular ganglion cell layer (mGCL) is a strong potential biomarker of axonal degeneration in multiple sclerosis (MS). For this reason, this study aims to develop a computer-aided method to facilitate diagnosis and prognosis in MS.
Boosting multiple sclerosis lesion segmentation through attention mechanism.
Computers in biology and medicine
May 10, 2023
Magnetic resonance imaging is a fundamental tool to reach a diagnosis of multiple sclerosis and monitoring its progression. Although several attempts have been made to segment multiple sclerosis lesions using artificial intelligence, fully automated ...
Deep learning-based PET/MR radiomics for the classification of annualized relapse rate in multiple sclerosis.
Multiple sclerosis and related disorders
May 9, 2023
Background Annualized Relapse Rate (ARR) is one of the most important indicators of disease progression in patients with Multiple Sclerosis (MS). However, imaging markers that can effectively predict ARR are currently unavailable. In this study, we d...
Effect of Robot-Assisted Gait Training on Multiple Sclerosis: A Systematic Review and Meta-analysis of Randomized Controlled Trials.
Neurorehabilitation and neural repair
Apr 20, 2023
BACKGROUND: In recent meta-analyses, robot-assisted gait training for patients with multiple sclerosis (MS) have yielded limited clinical benefits compared with conventional overground gait training.
Thin-slice Two-dimensional T2-weighted Imaging with Deep Learning-based Reconstruction: Improved Lesion Detection in the Brain of Patients with Multiple Sclerosis.
Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine
Mar 16, 2023
PURPOSE: Brain MRI with high spatial resolution allows for a more detailed delineation of multiple sclerosis (MS) lesions. The recently developed deep learning-based reconstruction (DLR) technique enables image denoising with sharp edges and reduced ...
Deciphering multiple sclerosis disability with deep learning attention maps on clinical MRI.
NeuroImage. Clinical
Mar 15, 2023
The application of convolutional neural networks (CNNs) to MRI data has emerged as a promising approach to achieving unprecedented levels of accuracy when predicting the course of neurological conditions, including multiple sclerosis, by means of ext...
A 3-DoF robotic platform for the rehabilitation and assessment of reaction time and balance skills of MS patients.
PloS one
Feb 24, 2023
The central nervous system (CNS) exploits anticipatory (APAs) and compensatory (CPAs) postural adjustments to maintain the balance. The postural adjustments comprising stability of the center of mass (CoM) and the pressure distribution of the body in...
Reliability, validity and clinical usability of a robotic assessment of finger proprioception in persons with multiple sclerosis.
Multiple sclerosis and related disorders
Jan 14, 2023
BACKGROUND: Multiple sclerosis often leads to proprioceptive impairments of the hand. However, it is challenging to objectively assess such deficits using clinical methods, thereby also impeding accurate tracking of disease progression and hence the ...
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