Back to Search Start Over

Identifying multiple sclerosis subtypes using unsupervised machine learning and MRI data

Authors :
Arman Eshaghi
Alexandra L. Young
Peter A. Wijeratne
Ferran Prados
Douglas L. Arnold
Sridar Narayanan
Charles R. G. Guttmann
Frederik Barkhof
Daniel C. Alexander
Alan J. Thompson
Declan Chard
Olga Ciccarelli
Source :
Nature Communications, Vol 12, Iss 1, Pp 1-12 (2021)
Publication Year :
2021
Publisher :
Nature Portfolio, 2021.

Abstract

Multiple sclerosis is a heterogeneous progressive disease. Here, the authors use an unsupervised machine learning algorithm to determine multiple sclerosis subtypes, progression, and response to potential therapeutic treatments based on neuroimaging data.

Subjects

Subjects :
Science

Details

Language :
English
ISSN :
20411723
Volume :
12
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Nature Communications
Publication Type :
Academic Journal
Accession number :
edsdoj.b925ea625e9146fc8c9474dea8ca687b
Document Type :
article
Full Text :
https://doi.org/10.1038/s41467-021-22265-2