AIRCC's International Journal of Computer Science and Information Technology

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Breast cancer is known as one of the most common cancers to afflict the female population. Computer assisted diagnosis can be helpful for doctors in detection and diagnosing of potential abnormalities. Several techniques can be useful for accomplishing this task. This paper outlines an approach for recognizing breast cancer diagnosis using neuro-fuzzy inference technique namely ANFIS (Adaptative Neuro-Fuzzy Inference System). Wisconsin breast cancer diagnosis (WBCD)database developed at University of California, Irvine (UCI) is used to evaluate this method. Results show that the best performances are obtained by our model compared to others cited in literatur (an accuracy of 98, 25 %).

Keywords

Artificial Neural Networks, Breast Cancer, Fuzzy Logic, Neuro-Fuzzy, Computer Assisted Diagnostic WBCD, Artificial Intelligence.
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