Cancermath employs a variety of mathematical tools, including differential equations, probabilistic models, and machine learning algorithms. These tools help in modeling the growth dynamics of tumors, predicting the progression of the disease, and optimizing treatment protocols. For instance, differential equations can model how cancer cells proliferate and interact with their environment, while probabilistic models can assess the likelihood of cancer recurrence.
