Research of Lung Cancer Screening Algorithm Based on RBF Neural Network

In this paper, a radial basis neural network (RBFN) for lung cancer screening algorithm is presented. Because of the learning characteristics of the radial basis neural network (RBFN), it has been selected to train the samples, which are the lung cancer examples, and then extracts the internal relations between the pathogenic factors and inducing lung cancer, and eventually it generates empirical function and forecasts the new samples. Advantage of this algorithm is that during the RBFN construction process, training function adopts the linear least square method (LLS) and the gradient descent hybrid learning algorithm, to optimize the training process and the screening results.