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...

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Detalles Bibliográficos
Autores principales: Roder, Joanna, Oliveira, Carlos, Net, Lelia, Tsypin, Maxim, Linstid, Benjamin, Roder, Heinrich
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Methodology Article
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

Internet

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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