Kinetic monte-carlo simulation of breast cancer risk and tumor growth
Abstract
Breast Cancer is one of the most common cancers in the world today usually affecting women and in rare cases men. In this experiment we attempt to simulate the growth of a breast cancer tumor by employing a stochastic based algorithm. The probabilities for developing breast cancer are taken from the National Cancer Institute's Surveillance, Epidemiology and End Results (SEER) Program and Harvard Cancer Risk Index. We simulate three different situations of breast cancer risk namely: No Exposure, Alcohol Exposure and Radiation Exposure. Results have shown to follow experimental and clinical data.