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A dropout-regularized classifier development approach optimized for precision medicine test discovery from omics data
BACKGROUND: Modern genomic and proteomic profiling methods produce large amounts of data from tissue and blood-based samples that are of potential utility for improving patient care. However, the design of precision medicine tests for unmet clinical needs from this information in the small cohorts a...
Autores principales: | Roder, Joanna, Oliveira, Carlos, Net, Lelia, Tsypin, Maxim, Linstid, Benjamin, Roder, Heinrich |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6567499/ https://www.ncbi.nlm.nih.gov/pubmed/31196002 http://dx.doi.org/10.1186/s12859-019-2922-2 |
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