5 papers
Calibrated Transfer Learning for Survival Prediction and Treatment Inference
Shuoyang Wang, Wanyu Zhang, Lingli Yang +1
Historical survival data can improve prediction in a cohort with few events, but prognostic differences can make borrowing harmful. To borrow while adapting, we propose calibrated…
Direct Learning of Treatment-Benefit Rankings for Restricted Mean Survival Time in Randomized Trials with Censoring
Lingli Yang, Bingxia Wang, Tian Chen +2
In precision medicine, treatment decisions often depend more on identifying which patients are most likely to benefit from treatment than on accurately estimating benefit for every…
Adaptive Sampling of Costly Outcomes in Randomized Clinical Trials
Shuoyang Wang, Wanyu Zhang, Lingli Yang +1
In some randomized trials the primary outcome is costly or slow to measure, while auxiliary variables that predict it are available for everyone. The outcome can then be measured i…
Worst-Case Win Ratios Under Partially Specified Outcome Hierarchies
Kexuan Li, Xue Fan, Lingli Yang
Win statistics require a prespecified outcome hierarchy. Clinical teams sometimes agree only on the highest priority outcome, leaving the order of lower priority outcomes unresolve…
Detection of LUAD-Associated Genes Using Wasserstein Distance in Multi-Omics Feature Selection
Shaofei Zhao, Siming Huang, Kexuan Li +3
Lung adenocarcinoma (LUAD) is characterized by substantial genetic heterogeneity, posing challenges in identifying reliable biomarkers for improved diagnosis and treatment. Tumor M…