A Clinically and Biologically Based Subclassification of the Idiopathic Inflammatory Myopathies Usin...
A Clinically and Biologically Based Subclassification of the Idiopathic Inflammatory Myopathies Using Machine Learning
About this item
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Publisher
United States: John Wiley & Sons, Inc
Journal title
Language
English
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Publisher
United States: John Wiley & Sons, Inc
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Scope and Contents
Contents
Objective
Published predictive models of disease outcomes in idiopathic inflammatory myopathies (IIMs) are sparse and of limited accuracy due to disease heterogeneity. Computational methods may address this heterogeneity by partitioning patients based on clinical and biological phenotype.
Methods
To identify new patient groups, we applied...
Alternative Titles
Full title
A Clinically and Biologically Based Subclassification of the Idiopathic Inflammatory Myopathies Using Machine Learning
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TN_cdi_doaj_primary_oai_doaj_org_article_9d92f243072c471780161d15beb82080
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_9d92f243072c471780161d15beb82080
Other Identifiers
ISSN
2578-5745
E-ISSN
2578-5745
DOI
10.1002/acr2.11115
