On the Investigation of the Dynamical Mechanisms of Neuroblastoma by Stochastic Neural Networks

This study develops a mathematical neuroblastoma model (NBLM) to analyze interactions between cancer cells, tumor-suppressor cells, immune-suppressor cells, and oncolytic viruses. The system is solved using stochastic neural networks with Bayesian Regularization (BRA-SNNs) trained on Runge-Kutta generated datasets, and evaluated using Absolute Error and Mean Square Error metrics.

Journal of Computational and Applied Mathematics