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Machine learning approaches to predict lupus disease activity from gene expression data
The integration of gene expression data to predict systemic lupus erythematosus (SLE) disease activity is a significant challenge because of the high degree of heterogeneity among patients and study cohorts, especially those collected on different microarray platforms. Here we deployed machine learn...
Enregistré dans:
| Publié dans: | Sci Rep |
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| Auteurs principaux: | , , , , , , , , , |
| Format: | Artigo |
| Langue: | Inglês |
| Publié: |
Nature Publishing Group UK
2019
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| Sujets: | |
| Accès en ligne: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6610624/ https://ncbi.nlm.nih.gov/pubmed/31270349 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41598-019-45989-0 |
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