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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Detalles Bibliográficos
Autores principales: Mohaiminul Islam, Md., Huang, Shujun, Ajwad, Rasif, Chi, Chen, Wang, Yang, Hu, Pingzhao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Research Network of Computational and Structural Biotechnology 2020
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7473884/
https://www.ncbi.nlm.nih.gov/pubmed/32952934
http://dx.doi.org/10.1016/j.csbj.2020.08.005

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7473884/
https://www.ncbi.nlm.nih.gov/pubmed/32952934
http://dx.doi.org/10.1016/j.csbj.2020.08.005

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