GPDBN: deep bilinear network integrating both genomic data and pathological images for breast cancer prognosis prediction

MOTIVATION: Breast cancer is a very heterogeneous disease and there is an urgent need to design computational methods that can accurately predict the prognosis of breast cancer for appropriate therapeutic regime. Recently, deep learning-based methods have achieved great success in prognosis predicti...

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Detalles Bibliográficos
Autores principales: Wang, Zhiqin, Li, Ruiqing, Wang, Minghui, Li, Ao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2021
Materias:
Original Papers
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8479662/
https://www.ncbi.nlm.nih.gov/pubmed/33734318
http://dx.doi.org/10.1093/bioinformatics/btab185

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8479662/
https://www.ncbi.nlm.nih.gov/pubmed/33734318
http://dx.doi.org/10.1093/bioinformatics/btab185

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