Fig. 2
Machine learning analysis. We presented several steps for model development. We randomly split the data into training and testing datasets and used the Cox proportional hazards model and ML survival models including random survival forest, survival trees, survival support vector machine, extra survival trees, and gradient boosting to predict prostate cancer