Mohammad Saifur Rahman

Interpretable biomarker discovery from small-sample microarray datasets using XGBoost rank aggregation and SVM-RFECV

Motivation High-dimensional microarray datasets remain valuable for cancer biomarker discovery, but their small sample sizes make robust and interpretable feature selection challenging. Efficient workflows are needed to derive compact gene signatures while preserving biological interpretability. Results We developed a...