04:00
2026-07-10
arxiv.org
machine-learning
SHIFT: Survival Prediction from Incomplete and Heterogeneous Genomic Data
Researchers propose SHIFT, a missingness-aware survival model that predicts from incomplete genomic data without test-time imputation, using masked self-attention and variable-rate feature masking. Evโฆ