This chapter summarises the applications of neural networks to urologic oncology. An artificial neural network (ANN) is a complex computer system that is designed to replicate human decision making by modelling the human neuron. Most of the work in neural networks in urologic oncology is in the area of diagnosis and treatment outcomes in prostate cancer. R. E. Hurst and colleagues used a neural network applied to an image analysis system to identify bladder cells expressing the tumour antigen p300. For detection of prostate cancer, the sensitivity was 81% and specificity 92%. For predicting benign prostatic hyperplasia the sensitivity was 63%. R. N. Naguib et al. reported the use of a neural network to predict prognosis and outcome in prostate cancer using conventional input variables. For the ANN expert, using a custom network, the overall accuracy was 92%, sensitivity of 88%, specificity of 96%.