Yong-Jhu Sun, Shou-Yu Wang, Yvette Tsai, Wenxi Wei, Hui-Chen Chang
Registered nurses' perceptions and experience of working in aged care: A qualitative approach
Nursing open
identifying cancer risk groups multiomics attracted researchers quest find biomarkers diverse riskrelated omics stratifying patients cancer risk groups using genomics essential clinicians preprevention treatment improve survival time patients identify appropriate therapy strategies study proposes multiomics framework extract features various omics simultaneously framework employs autoencoders learn nonlinear representation data applies tensor analysis feature learning clustering method used stratify patients multiple cancer risk groups several omics included experiments namely methylation somatic copynumber variation scnv micro rna mirna rna sequencing rnaseq two cancer types including glioma breast invasive carcinoma tcga dataset results study promising evidenced survival analysis classification models outperformed stateoftheart patients significantly pvalue005 divided risk groups using extracted latent variables fused multiomics data pipeline open source help researchers clinicians identify patients risk groups using genomics