3 papers
stat.ME2026
Evaluating Treatment Effects using Group Testing with Retesting of Positive Groups
Aye Aye Maung, Qi Zheng
Group testing is an established, highly cost-effective strategy for population-level disease surveillance that identifies positive individuals by pooling biological specimens. Orig…
stat.ME2026
Separating Spatial and Clinical Risk with Node-Splitting SVM Survival Trees
Drew Lazar, Aye Aye Maung
Recovering geographic variation in survival requires separating spatial risk from patients' clinical characteristics, a problem complicated by prognostic covariates that are themse…
stat.ME2025
Node Splitting SVMs for Survival Trees Based on an L2-Regularized Dipole Splitting Criteria
Aye Aye Maung, Drew Lazar, Qi Zheng
This paper proposes a novel, node-splitting support vector machine (SVM) for creating survival trees. This approach is capable of non-linearly partitioning survival data which incl…