Xuelin Huang

SuperSurv provides a unified R package for building, evaluating, and interpreting ensemble survival models with right-censored data, using SHAP values and IPCW Brier risk for weighting.

MELODY quantifies total mediation effects in logistic regression for high-dimensional mediators and binary outcomes, outperforming traditional methods in non-rare disease scenarios.

MASH identifies high-dimensional mediators in survival analysis, showing cigarette smoking mediates 51.1% of coronary heart disease risk via five metabolites.

CASi is a framework for analyzing multi-timepoint scRNA-seq data, enabling cell annotation, novel cell type detection, population evolution visualization, and temporal differential gene identification.

This paper introduces a method for imputing censored survival data to improve machine learning analysis in biomedical research.

This paper applies machine learning to response-adaptive randomization in clinical trials, showing improved treatment assignment and response rates.