A kernel approach for ensemble decision combinations with two-view mammography applications

Abstract

An ensemble decision combination method was derived with kernel methods. An ensemble comprised of six Artificial Neural Networks (ANNs) was used to make benign?malignant predictions for breast lesions. The combination processing was evaluated for both single-view and two-view mammograms. The single-view combination showed marked improvements over the performance of each individual ANN, and the two-view combination showed marked improvements over the single-view combination performance. The work provides preliminary validation of the ensemble combination mechanism using an important clinically relevant data set.