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Artificial intelligence applied to MRI data to tackle key challenges in multiple sclerosis

Collorone, Sara; Coll, Llucia; Lorenzi, Marco; Lladó, Xavier; Sastre-Garriga, Jaume; Tintoré, Mar; Montalban, Xavier; ... Tur, Carmen; + view all (2024) Artificial intelligence applied to MRI data to tackle key challenges in multiple sclerosis. Multiple Sclerosis Journal , 30 (7) 767 - 784. 10.1177/13524585241249422. Green open access

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Abstract

Artificial intelligence (AI) is the branch of science aiming at creating algorithms able to carry out tasks that typically require human intelligence. In medicine, there has been a tremendous increase in AI applications thanks to increasingly powerful computers and the emergence of big data repositories. Multiple sclerosis (MS) is a chronic autoimmune condition affecting the central nervous system with a complex pathogenesis, a challenging diagnostic process strongly relying on magnetic resonance imaging (MRI) and a high and largely unexplained variability across patients. Therefore, AI applications in MS have the great potential of helping us better support the diagnosis, find markers for prognosis to eventually design more powerful randomised clinical trials and improve patient management in clinical practice and eventually understand the mechanisms of the disease. This topical review aims to summarise the recent advances in AI applied to MRI data in MS to illustrate its achievements, limitations and future directions.

Type: Article
Title: Artificial intelligence applied to MRI data to tackle key challenges in multiple sclerosis
Location: England
Open access status: An open access version is available from UCL Discovery
DOI: 10.1177/13524585241249422
Publisher version: http://dx.doi.org/10.1177/13524585241249422
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Multiple sclerosis; MRI; artificial intelligence; deep learning; progressive; convolutional neural networks
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Neuroinflammation
URI: https://discovery.ucl.ac.uk/id/eprint/10193600
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