Evaluation of breast cancer risk by using formal reasoning algorithm

We introduce an approach to risk estimation in breast cancer disease based on an intelligent method of Petri net. For the purpose of knowledge representation of risk estimation in breast cancer disease, a specified type of Petri net approach is explicitly introduced in this paper. A woman whose mother, sister or daughter had breast cancer has an increased risk. Having a male relative with breast cancer, can also increase your risk. In the proposed approach, an eight factors profile is first transformed into a mapping form and then the transformed data are mapped into the fuzzy inference system. Since the relations of an eight factors are represented by fuzzy model, the proposed method is robust to noisy and uncertain information. The compatibility of the system to existing models of gender, age, genetic status, menarche age, menopause age, first birth age, alcohol consumption and nutrition habit as factors have been identified in the model of breast cancer has been tested.