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Standard machine learning approaches outperform deep representation learning on phenotype prediction from transcriptomics data
BACKGROUND: The ability to confidently predict health outcomes from gene expression would catalyze a revolution in molecular diagnostics. Yet, the goal of developing actionable, robust, and reproducible predictive signatures of phenotypes such as clinical outcome has not been attained in almost any...
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| Publicat a: | BMC Bioinformatics |
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| Autors principals: | , , , , , , , , , , , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
BioMed Central
2020
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7085143/ https://ncbi.nlm.nih.gov/pubmed/32197580 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12859-020-3427-8 |
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