A Hybrid PINN-DE Framework for Data-Driven Parameter Estimation of Tumor-Immune Dynamics in Bladder Cancer
This study proposes a hybrid framework combining Differential Evolution and Physics-Informed Neural Networks to accurately estimate parameters in tumor-immune ODE models for bladder cancer, enabling robust, data-driven personalization of treatment strategies despite sparse and noisy clinical data.