Xiaoru Dong

Bootstrap-enhanced regularization addressing multicollinearity and skewness in high-dimensional immunophenotyping data

The Bootstrap-Enhanced Regularization Method (BERM) is a robust approach for variable selection and coefficient estimation in complex biomedical datasets, achieving the highest overall balanced accuracy while maintaining competitive coefficient estimation performance across a range of simulated sparsity, noise, and dimensionality scenarios.