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A Deep Neural Network Model using Random Forest to Extract Feature Representation for Gene Expression Data Classification
In predictive model development, gene expression data is associated with the unique challenge that the number of samples (n) is much smaller than the amount of features (p). This “n ≪ p” property has prevented classification of gene expression data from deep learning techniques, which have been prov...
| Autores principales: | , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
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Nature Publishing Group UK
2018
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6220289/ https://www.ncbi.nlm.nih.gov/pubmed/30405137 http://dx.doi.org/10.1038/s41598-018-34833-6 |