Neural network design for optimization of the partial area under the receiver operating characteristic curve

A new backpropagation training algorithm was developed for the maximization of the area under the receiver operating characteristic (ROC) curve between two user-specified true-positive fraction thresholds. The algorithm was used to design a neural network classifier with high specificity at the high-sensitivity region of the ROC curve, which is of particular interest for computer-aided diagnosis applications. The effectiveness of the algorithm was demonstrated with a simulation study