An artificial neural network approach for detecting skin cancer

Numerous computational intelligence (CI) techniques have emerged motivated for solving many real world problems by real biological systems, namely, artificial neural networks (NNs) [13-22] , evolutional computation, simulated annealing and swarm intelligence, which were enthused by biological nervous systems, natural selection, the principle of thermodynamics and insect behavior, respectively. The method used is training and testing phases with classification of Multilayer Perceptron (MLP) neural network. 2.Research Method In this section, the system design for skin cancer detection program using artificial neural network (ANN) with input data in the form of color image dermatoscopic is presented. 5) Feature extraction based on texture by using first-order characteristic extraction method. 6) Image classification with Artificial Neural Networks. 7) The final result of diagnose type of melanoma skin cancer and non-melanoma. 3.Results and Discussion Gray scaling is a technique used to change color image i.e. RGB into grey level (from black to white) with this modification then matrix to compose the image that previous 3 matrix will change to just 1 matrix [10]. [14] Chiroma H, Abdulkareem S, Herawan T. Evolutionary Neural Network model for West Texas Intermediate crude oil price prediction.