Interpretable deep neural network for cancer survival analysis by integrating genomic and clinical data

BACKGROUND: Understanding the complex biological mechanisms of cancer patient survival using genomic and clinical data is vital, not only to develop new treatments for patients, but also to improve survival prediction. However, highly nonlinear and high-dimension, low-sample size (HDLSS) data cause...

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Detalles Bibliográficos
Autores principales: Hao, Jie, Kim, Youngsoon, Mallavarapu, Tejaswini, Oh, Jung Hun, Kang, Mingon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6927105/
https://www.ncbi.nlm.nih.gov/pubmed/31865908
http://dx.doi.org/10.1186/s12920-019-0624-2

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6927105/
https://www.ncbi.nlm.nih.gov/pubmed/31865908
http://dx.doi.org/10.1186/s12920-019-0624-2

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