Expert learning system network for diagnosis of breast calcifications.

Abstract:

: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 radiologist. 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.

journal_name

Invest Radiol

journal_title

Investigative radiology

authors

Patrick EA,Moskowitz M,Mansukhani VT,Gruenstein EI

doi

10.1097/00004424-199106000-00004

subject

Has Abstract

pub_date

1991-06-01 00:00:00

pages

534-9

issue

6

eissn

0020-9996

issn

1536-0210

journal_volume

26

pub_type

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