Identifying multi-omics biomarkers for ovarian cancer survival estimation
An interpretable three-stage machine learning framework integrating mRNA, microRNA, DNA methylation, copy number variation, and protein expression data from The Cancer Genome Atlas that couples improved prognostic estimation with biological interpretability supporting multi-omics biomarker discovery in ovarian cancer.