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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:...
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. |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2020
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Materias: | |
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 |
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