hEFS uses subsampling and multi-model voting with Pareto front selection to produce fewer, more stable prognostic biomarkers from pancreatic cancer multi-omics data while matching CoxLasso discrimination performance.
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Optimizing Prognostic Biomarker Discovery in Pancreatic Cancer Through Hybrid Ensemble Feature Selection and Multi-Omics Data
hEFS uses subsampling and multi-model voting with Pareto front selection to produce fewer, more stable prognostic biomarkers from pancreatic cancer multi-omics data while matching CoxLasso discrimination performance.