PATRICK EDWARD A. PhD MD FACEP; MOSKOWITZ, MYRON MD, FACR; MANSUKHANI, VINEET T. MS; GRUENSTEIN, ERIC I. PhDInvestigative Radiology: June 1991 Original Investigations: PDF Only Buy Abstract Patrick EA, Moskowitz M, Mansukhani VT, Gruenstein EI. Expert learning system network for diagnosis of breast calcifications. Invest Radiol 1991;26:534-539. Breast calcification diagnosis was studied by using clinical findings and computerized image processing of a mammogram in a network of trained expert learning systems (Outcome Advisor® [OA]). The system was tested with records not used for training and performance was compared with radiologists. The network was 72% accurate in classifying clusters of calcifications as malignant or benign over a set of test cases radiologists had considered “hard-to-diagnose calcifications,” and referred for biopsy. The radiologists had decided to conduct biopsy by selecting an equal number of positive and negative cases for the test group; thus the radiologists’ performance with respect to categories of benign versus malignant was constrained to be 50/50. Statistical analysis shows only a 2% probability that the observed accuracy of 72% was a chance performance in recognizing whether a cluster is benign or malignant. The feasibility of developing a network of OAs for diagnosing breast cancer integrating digital image processing of mammograms is promising. © Lippincott-Raven Publishers.