Why Use Random Survival Forests in Cancer Research?
Cancer progression and treatment outcomes are inherently complex and influenced by a multitude of factors. RSFs provide a robust, non-parametric approach to handle this complexity. They can:
Handle high-dimensional data, making them suitable for genomic or proteomic studies. Accommodate censoring, where the event of interest has not occurred for some subjects during the study period. Identify important variables that contribute to survival, aiding in the discovery of potential biomarkers.
