Abstract:Ovarian cancer is a complex disease with poor outcome affecting women worldwide. The lack of successful therapeutic options for ovarian cancer patients results in the strong need to identify new biomarkers for patient selection. The development of outcome predictors based on gene expression is important not only for patient stratification but also to recognize categories of patients that are more likely to respond to particular therapies. In this paper, we proposed a new deep learning survival model trained on… Show more
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