Prostate Cancer Survival Prediction: Integrating Clinical Insights, Genomics and Machine Learning for Precision Care

Prostate cancer remains a significant global health challenge among men, necessitating robust survival prediction models to enhance clinical decision-making and improve patient outcomes. While traditional prognostic tools—such as Gleason scores, PSA levels and TNM staging—offer valuable insights, they have limitations in precision, scalability and adaptability across diverse patient populations.