A case-based reasoning system using feature scaling for computer aided breast cancer diagnosis

In this paper a CBR system for mammography CAD that uses feature s caling to improve the systems classification performance is proposed. The CBR system was evaluated on the public DDSM mammography database. We use ROC analysis and leaving-one-out sampling to show that the feature weighting approach results in improved ROC performance.