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The decision process for selecting the best-suited follow-up treatment for suspected breast cancer cases are strongly dependent upon the correct diagnosis and assessment of the breast cancer risk. This study will develop an expert system with soft computing methods by using Fuzzy logic and Bayesian network. This system has five input variables and one output variable (risk status). The output variable is a value from 1 to 4; representing low risk status, intermediate risk status ,high risk status and very high risk. This study will help to diagnosis and monitor breast cancer at home.

Breast Cancer Monitoring and Tracking System using Soft Computing and Expert System for Healthcare Support