In cancer treatment, Bayesian models are employed to predict how patients will respond to different therapies. By incorporating prior clinical trial data and individual patient characteristics, these models can help in personalizing treatment plans. For example, Bayesian models can forecast the efficacy of chemotherapy or immunotherapy regimes, allowing oncologists to tailor treatments that maximize efficacy while minimizing side effects.
