Cox versus Random Survival Forest for prostate Cancer mortality prediction: a retrospective competing risks analysis of 14,294 Patients

Abstract

Machine learning survival models are increasingly applied to prostate cancer risk stratification, yet rigorous comparisons with traditional approaches accounting for competing mortality remain limited. We hypothesized that Random Survival Forest would demonstrate superior discrimination compared to Cox proportional hazards modelling.

The paper