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An integrative deep learning framework for classifying molecular subtypes of breast cancer
Classification of breast cancer subtypes using multi-omics profiles is a difficult problem since the data sets are high-dimensional and highly correlated. Deep neural network (DNN) learning has demonstrated advantages over traditional methods as it does not require any hand-crafted features, but rat...
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| Pubblicato in: | Comput Struct Biotechnol J |
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| Autori principali: | , , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Research Network of Computational and Structural Biotechnology
2020
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7473884/ https://ncbi.nlm.nih.gov/pubmed/32952934 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.csbj.2020.08.005 |
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