Breast cancer diagnosis using genetic algorithm for training feed forward back propagation

Biological system such as neural networks and genetic algorithms are adapted to improve the doctors experience for diagnosis of illnesses. This work is introduced an approach for diagnosing breast cancer via classifying a well-known WBCD dataset based on a hybrid neurogenetic system. The suggested approach showed a good behavior and excellent classification accuracy through the implementation of several trials using different number of test samples. The accuracy of system has been reached to 100% in the best trial and it is exceeding 97% in other experiments.