3 papers
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.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.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…