Introduction of a New Diagnostic Method for Breast Cancer Based on Fine Needle Aspiration (FNA) Test Data and Combining Intelligent Systems

摘要: Accurate Diagnosis of Breast Cancer is prime importance. Fine Needle Aspiration test or "FNA", which has been used for several years in Europe, a simple, inexpensive, noninvasive and accurate technique detecting breast cancer. Expending the suitable features results most important diagnostic problem early stages In this study, we introduced new algorithm that can detect cancer based on combining artificial intelligent system (FNA). Methods: We studied Features Wisconsin Data Base contained about 569 FNA samples (212 patient (malignant) 357 healthy (benign)). research, combined Artificial Intelligence Approaches, such as Evolutionary Algorithm (EA) with Genetic (GA), also Exact Classifier Systems (here by Fuzzy C-Means (FCM)) to separate malignant from benign samples. Furthermore, examined Neural Networks (NN) identify model structure. This research proposed an diagnosis Results: According (WDBC) data base, 62.75% were benign, 37.25% malignant. After applying algorithm, achieved high detection accuracy "96.579%" 205 patients who diagnosed having It was found method had 93% sensitivity, 73% specialty, 65% positive predictive value, 95% negative respectively. If done experts, (FNA) be reliable replacement open biopsy palpable masses. Evaluation during aspiration decrease insufficient first line women masses, at least deprived regions, may increase health standards clinical supervision patients. Conclusion: Such smart, economical, non-invasive, rapid useful comprehensive treatment Another advantage possibility diagnosing abnormalities.