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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...
Autores principales: | Kegerreis, Brian, Catalina, Michelle D., Bachali, Prathyusha, Geraci, Nicholas S., Labonte, Adam C., Zeng, Chen, Stearrett, Nathaniel, Crandall, Keith A., Lipsky, Peter E., Grammer, Amrie C. |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6610624/ https://www.ncbi.nlm.nih.gov/pubmed/31270349 http://dx.doi.org/10.1038/s41598-019-45989-0 |
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