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A Machine Learning Classifier for Assigning Individual Patients with Systemic Sclerosis to Intrinsic Molecular Subsets
OBJECTIVE: High-throughput gene expression profiling of tissue samples from patients with systemic sclerosis (SSc) has identified four “intrinsic” gene expression subsets: inflammatory, fibroproliferative, normal-like, and limited. Prior methods required agglomerative clustering of many samples. In...
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| Udgivet i: | Arthritis Rheumatol |
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| Main Authors: | , , , , , , |
| Format: | Artigo |
| Sprog: | Inglês |
| Udgivet: |
2019
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| Fag: | |
| Online adgang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6764877/ https://ncbi.nlm.nih.gov/pubmed/30920766 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/art.40898 |
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