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Group Lasso Regularized Deep Learning for Cancer Prognosis from Multi-Omics and Clinical Features
Accurate prognosis of patients with cancer is important for the stratification of patients, the optimization of treatment strategies, and the design of clinical trials. Both clinical features and molecular data can be used for this purpose, for instance, to predict the survival of patients censored...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
MDPI
2019
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6471789/ https://www.ncbi.nlm.nih.gov/pubmed/30901858 http://dx.doi.org/10.3390/genes10030240 |