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Present and future of the diagnostic work-up of multiple sclerosis: the imaging perspective
In recent years, the use of magnetic resonance imaging (MRI) for the diagnostic work-up of
multiple sclerosis (MS) has evolved considerably. The 2017 McDonald criteria show high …
multiple sclerosis (MS) has evolved considerably. The 2017 McDonald criteria show high …
[HTML][HTML] Role of artificial intelligence in MS clinical practice
Abstract Machine learning (ML) and its subset, deep learning (DL), are branches of artificial
intelligence (AI) showing promising findings in the medical field, especially when applied to …
intelligence (AI) showing promising findings in the medical field, especially when applied to …
[HTML][HTML] Optimal integration of machine learning for distinct classification and activity state determination in multiple sclerosis and neuromyelitis optica
The intricate neuroinflammatory diseases multiple sclerosis (MS) and neuromyelitis optica
(NMO) often present similar clinical symptoms, creating challenges in their precise detection …
(NMO) often present similar clinical symptoms, creating challenges in their precise detection …
Transfer-transfer model with MSNet: An automated accurate multiple sclerosis and myelitis detection system
Purpose Multiple sclerosis (MS) is a commonly seen neurodegenerative disorder, and early
diagnosis of MS is a crucial issue to promote patient health. Since MS diagnosis is a …
diagnosis of MS is a crucial issue to promote patient health. Since MS diagnosis is a …
Current and future role of MRI in the diagnosis and prognosis of multiple sclerosis
In the majority of cases, multiple sclerosis (MS) is characterized by reversible episodes of
neurological dysfunction, often followed by irreversible clinical disability. Accurate diagnostic …
neurological dysfunction, often followed by irreversible clinical disability. Accurate diagnostic …
Artificial intelligence for multiple sclerosis management using retinal images: Pearl, peaks, and pitfalls
Multiple sclerosis (MS) is a complex autoimmune disease characterized by inflammatory
processes, demyelination, neurodegeneration, and axonal damage within the central …
processes, demyelination, neurodegeneration, and axonal damage within the central …
Machine learning approaches in study of multiple sclerosis disease through magnetic resonance images
Multiple sclerosis (MS) is one of the most common autoimmune diseases which is commonly
diagnosed and monitored using magnetic resonance imaging (MRI) with a combination of …
diagnosed and monitored using magnetic resonance imaging (MRI) with a combination of …
Differentiation between multiple sclerosis and neuromyelitis optica spectrum disorder using a deep learning model
Multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD) are
autoimmune inflammatory disorders of the central nervous system (CNS) with similar …
autoimmune inflammatory disorders of the central nervous system (CNS) with similar …
[HTML][HTML] Clinical applications of deep learning in neuroinflammatory diseases: A sco** review
Background Deep learning (DL) is an artificial intelligence technology that has aroused
much excitement for predictive medicine due to its ability to process raw data modalities …
much excitement for predictive medicine due to its ability to process raw data modalities …
Neutrophil-mediated mechanisms of damage and in-vitro protective effect of colchicine in non-vascular Behçet's syndrome
Behçet's syndrome (BS) is a systemic vasculitis with several clinical manifestations.
Neutrophil hyperactivation mediates vascular BS pathogenesis, via both a massive reactive …
Neutrophil hyperactivation mediates vascular BS pathogenesis, via both a massive reactive …