AIMC Topic: Multiple Sclerosis

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White Matter Lesion Segmentation for Multiple Sclerosis Patients implementing deep learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The aim of this work is to address the problem of White Matter Lesion (WML) segmentation employing Magnetic Resonance Imaging (MRI) images from Multiple Sclerosis (MS) patients through the application of deep learning. A U-net based architecture cont...

[What worries people with multiple sclerosis in Russia? Semantic analysis of patient messages using artificial intelligence tools].

Zhurnal nevrologii i psikhiatrii imeni S.S. Korsakova
OBJECTIVE: To study the needs of patients suffering from multiple sclerosis (MS) in Russia.

Identification of viral-mediated pathogenic mechanisms in neurodegenerative diseases using network-based approaches.

Briefings in bioinformatics
During the course of a viral infection, virus-host protein-protein interactions (PPIs) play a critical role in allowing viruses to replicate and survive within the host. These interspecies molecular interactions can lead to viral-mediated perturbatio...

SGANRDA: semi-supervised generative adversarial networks for predicting circRNA-disease associations.

Briefings in bioinformatics
Emerging research shows that circular RNA (circRNA) plays a crucial role in the diagnosis, occurrence and prognosis of complex human diseases. Compared with traditional biological experiments, the computational method of fusing multi-source biologica...

Deep Learning on Conventional Magnetic Resonance Imaging Improves the Diagnosis of Multiple Sclerosis Mimics.

Investigative radiology
OBJECTIVES: The aims of this study were to present a deep learning approach for the automated classification of multiple sclerosis and its mimics and compare model performance with that of 2 expert neuroradiologists.

Deep-Learning Generated Synthetic Double Inversion Recovery Images Improve Multiple Sclerosis Lesion Detection.

Investigative radiology
OBJECTIVES: The aim of the study was to implement a deep-learning tool to produce synthetic double inversion recovery (synthDIR) images and compare their diagnostic performance to conventional sequences in patients with multiple sclerosis (MS).

Factors affecting the usability of an assistive soft robotic glove after stroke or multiple sclerosis.

Journal of rehabilitation medicine
OBJECTIVE: To explore the usability and effects of an assistive soft robotic glove in the home setting after stroke or multiple sclerosis.

MRI-based prediction of conversion from clinically isolated syndrome to clinically definite multiple sclerosis using SVM and lesion geometry.

Brain imaging and behavior
Neuroanatomical pattern classification using support vector machines (SVMs) has shown promising results in classifying Multiple Sclerosis (MS) patients based on individual structural magnetic resonance images (MRI). To determine whether pattern class...

Beyond therapists: Technology-aided physical MS rehabilitation delivery.

Multiple sclerosis (Houndmills, Basingstoke, England)
In the last decade, rehabilitation technology has been developed, investigated, and entered specialized clinical settings. In this chapter, we first discuss the potential of rehabilitation technology to support the achievement of key factors in motor...