Present and future of the diagnostic work-up of multiple sclerosis: the imaging perspective

M Filippi, P Preziosa, DL Arnold, F Barkhof… - Journal of …, 2023‏ - Springer
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 …

[HTML][HTML] Role of artificial intelligence in MS clinical practice

R Bonacchi, M Filippi, MA Rocca - NeuroImage: Clinical, 2022‏ - Elsevier
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 …

[HTML][HTML] Optimal integration of machine learning for distinct classification and activity state determination in multiple sclerosis and neuromyelitis optica

M Gharaibeh, W Abedalaziz, NA Alawad, H Gharaibeh… - Technologies, 2023‏ - mdpi.com
The intricate neuroinflammatory diseases multiple sclerosis (MS) and neuromyelitis optica
(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

S Tatli, G Macin, I Tasci, B Tasci, PD Barua… - Expert Systems with …, 2024‏ - Elsevier
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 …

Current and future role of MRI in the diagnosis and prognosis of multiple sclerosis

MA Rocca, P Preziosa, F Barkhof… - The Lancet Regional …, 2024‏ - thelancet.com
In the majority of cases, multiple sclerosis (MS) is characterized by reversible episodes of
neurological dysfunction, often followed by irreversible clinical disability. Accurate diagnostic …

Artificial intelligence for multiple sclerosis management using retinal images: Pearl, peaks, and pitfalls

S Farabi Maleki, M Yousefi, S Afshar… - Seminars in …, 2024‏ - Taylor & Francis
Multiple sclerosis (MS) is a complex autoimmune disease characterized by inflammatory
processes, demyelination, neurodegeneration, and axonal damage within the central …

Machine learning approaches in study of multiple sclerosis disease through magnetic resonance images

F Moazami, A Lefevre-Utile, C Papaloukas… - Frontiers in …, 2021‏ - frontiersin.org
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 …

Differentiation between multiple sclerosis and neuromyelitis optica spectrum disorder using a deep learning model

JM Seok, W Cho, YH Chung, H Ju, ST Kim, JK Seong… - Scientific reports, 2023‏ - nature.com
Multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD) are
autoimmune inflammatory disorders of the central nervous system (CNS) with similar …

[HTML][HTML] Clinical applications of deep learning in neuroinflammatory diseases: A sco** review

S Demuth, J Paris, I Faddeenkov, J De Sèze… - Revue …, 2024‏ - Elsevier
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 …

Neutrophil-mediated mechanisms of damage and in-vitro protective effect of colchicine in non-vascular Behçet's syndrome

A Bettiol, M Becatti, E Silvestri… - Clinical & …, 2021‏ - academic.oup.com
Behçet's syndrome (BS) is a systemic vasculitis with several clinical manifestations.
Neutrophil hyperactivation mediates vascular BS pathogenesis, via both a massive reactive …