AIMC Topic: Multiple Sclerosis
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A machine learning approach to determine the risk factors for fall in multiple sclerosis.
BMC medical informatics and decision making
Jul 30, 2024
BACKGROUND: Falls in multiple sclerosis can result in numerous problems, including injuries and functional loss. Therefore, determining the factors contributing to falls in people with Multiple Sclerosis (PwMS) is crucial. This study aims to investig...
Detection of diffusely abnormal white matter in multiple sclerosis on multiparametric brain MRI using semi-supervised deep learning.
Scientific reports
Jul 26, 2024
In addition to focal lesions, diffusely abnormal white matter (DAWM) is seen on brain MRI of multiple sclerosis (MS) patients and may represent early or distinct disease processes. The role of MRI-observed DAWM is understudied due to a lack of automa...
An analytical review on the use of artificial intelligence and machine learning in diagnosis, prediction, and risk factor analysis of multiple sclerosis.
Multiple sclerosis and related disorders
Jul 16, 2024
Medical research offers potential for disease prediction, like Multiple Sclerosis (MS). This neurological disorder damages nerve cell sheaths, with treatments focusing on symptom relief. Manual MS detection is time-consuming and error prone. Though M...
Explainable machine learning on baseline MRI predicts multiple sclerosis trajectory descriptors.
PloS one
Jul 16, 2024
Multiple sclerosis (MS) is a multifaceted neurological condition characterized by challenges in timely diagnosis and personalized patient management. The application of Artificial Intelligence (AI) to MS holds promises for early detection, accurate d...
Efficient segmentation of active and inactive plaques in FLAIR-images using DeepLabV3Plus SE with efficientnetb0 backbone in multiple sclerosis.
Scientific reports
Jul 15, 2024
This research paper introduces an efficient approach for the segmentation of active and inactive plaques within Fluid-attenuated inversion recovery (FLAIR) images, employing a convolutional neural network (CNN) model known as DeepLabV3Plus SE with th...
Artificial Intelligence and Multiple Sclerosis.
Current neurology and neuroscience reports
Jun 28, 2024
In this paper, we analyse the different advances in artificial intelligence (AI) approaches in multiple sclerosis (MS). AI applications in MS range across investigation of disease pathogenesis, diagnosis, treatment, and prognosis. A subset of AI, Mac...
Evaluation of machine learning-based classification of clinical impairment and prediction of clinical worsening in multiple sclerosis.
Journal of neurology
Jun 23, 2024
BACKGROUND: Robust predictive models of clinical impairment and worsening in multiple sclerosis (MS) are needed to identify patients at risk and optimize treatment strategies.
Time-Dependent Deep Learning Prediction of Multiple Sclerosis Disability.
Journal of imaging informatics in medicine
Jun 13, 2024
The majority of deep learning models in medical image analysis concentrate on single snapshot timepoint circumstances, such as the identification of current pathology on a given image or volume. This is often in contrast to the diagnostic methodology...
Using machine learning algorithms to detect fear of falling in people with multiple sclerosis in standardized gait analysis.
Multiple sclerosis and related disorders
Jun 10, 2024
INTRODUCTION: Multiple sclerosis (MS) is the most common chronic inflammatory disease of the central nervous system. The progressive impairment of gait is one of the most important pathognomic symptoms which are associated with falls and fear of fall...
Testing Dynamic Balance in People with Multiple Sclerosis: A Correlational Study between Standard Posturography and Robotic-Assistive Device.
Sensors (Basel, Switzerland)
May 23, 2024
BACKGROUND: Robotic devices are known to provide pivotal parameters to assess motor functions in Multiple Sclerosis (MS) as dynamic balance. However, there is still a lack of validation studies comparing innovative technologies with standard solution...
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