Müllerian ducts can form upper parts of normal female reproductive system and any failure in ductal fusion may result in to müllerian duct anomalies (MDA). We present a case of MDA and a uterus dysplasia with no evidence of cervical or upper vaginal tissue. This case showes the role of magnetic resonace imaging (MRI) on MDA diagnosis and urges the need for a unified reliable and practical classification more compatible with clinical practice.

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