Artificial neural networks in urology: Update 2000

Artificial neural networks (ANNs) are widely available and have been demons trated to be superior to standard empirical methods of detecting, staging a nd monitoring prostate cancer. These algorithms have been statistically val idated in diverse, well-characterized patient groups and are now being eval uated for clinical use worldwide. New variables based on demographic data, tissue and serum markers show promise for improving our ability to predict disease extent and outcome and may be integrated in future ANN models. This review focuses on recently developed neural networks for detecting, stagin g and monitoring prostate cancer.