Modeling of breast cancer risk using Bayesian networks

Breast cancer is the most common cancer in women at different stages of life affects about 10 percent of them. This Cancer is the second cause of death in women and the most common cause of death among women 45-55 years old. So the find a model to predict the likelihood of breast cancer based on patient past history and other risk factors is helpful. The purpose of this study was Building a Bayesian network model to calculate the risk of breast cancer. This research is developmental. Model and the conditional probability table that obtained from the Clementine 12.0. Breast cancer detection accuracy evaluate and results showed that the accuracy of the model was 96.22 percent. key words-- Breast cancer, Bayesian networks, Modeling.