Predictive model for PSA persistence after radical prostatectomy using machine learning algorithms

The Random Forest algorithm performed excellently in this study and can be used to construct a predictive model for PSA persistence. By incorporating clinical data from the Asian region and exploring the risk factors for PSA persistence, this study contributes to the existing research and aids clinicians in assessing the risk of PSA persistence occurrence, enabling timely treatment planning and improving patient prognosis.