Recent advances in the development of new biomarker tests, which physicians use for the early detection of cancer, have the potential to improve patient survival by catching cancer at an early stage. Q-learning methods were used to develop optimal screening policies, in terms of patient outcomes, for new prostate cancer biomarker tests. Numerical results based on a large clinical dataset will be used to draw insights about optimal screening policies.
