A Clinically and Biologically Based Subclassification of the Idiopathic Inflammatory Myopathies Using Machine Learning

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:...

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Detalles Bibliográficos
Autores principales: Eng, Simon W. M., Olazagasti, Jeannette M., Goldenberg, Anna, Crowson, Cynthia S., Oddis, Chester V., Niewold, Timothy B., Yeung, Rae S. M., Reed, Ann M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Original Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7077789/
https://www.ncbi.nlm.nih.gov/pubmed/32039563
http://dx.doi.org/10.1002/acr2.11115

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7077789/
https://www.ncbi.nlm.nih.gov/pubmed/32039563
http://dx.doi.org/10.1002/acr2.11115

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