Fig. 1
From: Predicting time-to-first cancer diagnosis across multiple cancer types
Model development and evaluation workflow: This figure outlines the workflow for predicting time-to-first cancer diagnosis using PLCO data. After preprocessing (exclusion criteria, missForest imputation, and feature standardization), three models—Cox proportional hazards, survival decision tree, and random survival forest—were trained on PLCO data and then evaluated on UKBB participants. Key outputs include a coefficient heatmap from the Cox proportional hazards model, a time-dependent AUC curve comparing performance, and a table summarizing C-index values across cancer types, highlighting the Cox model’s superior accuracy.
