Structured Transfer Learning for Survival Risk Stratification in Data-Sparse Clinical Cohorts
数据稀疏临床队列生存风险分层的结构化迁移学习
Background: Survival prediction models are often less reliable in clinical groups with limited sample sizes or few outcome events. Target-only models may be unstable, whereas models from larger cohorts may transfer poorly when risk-factor effects differ across populations. We evaluated whether structured transfer learning can improve survival risk stratification in data-sparse cohorts while allowing cohort-specific adaptation. Methods: We developed the COhort-shared…