Optimizing the feature set for a Bayesian network for breast cancer diagnosis using genetic algorithm techniques

Xiao Hui Wang; Bin Zheng; Yuan-Hsiang Chang; Walter F. Good

doi:10.1117/12.348560

21 May 1999 Optimizing the feature set for a Bayesian network for breast cancer diagnosis using genetic algorithm techniques

Xiao Hui Wang, Bin Zheng, Yuan-Hsiang Chang, Walter F. Good

Author Affiliations +

Proceedings Volume 3661, Medical Imaging 1999: Image Processing; (1999) https://doi.org/10.1117/12.348560
Event: Medical Imaging '99, 1999, San Diego, CA, United States

Abstract

This study investigates the degree to which the performance of Bayesian belief networks (BBNs), for computer-assisted diagnosis of breast cancer, can be improved by optimizing their input feature sets using a genetic algorithm (GA). 421 cases (all women) were used in this study, of which 92 were positive for breast cancer. Each case contained both non-image information and image information derived from mammograms by radiologists. A GA was used to select an optimal subset of features, from a total of 21, to use as the basis for a BBN classifier. The figure-of-merit used in the GA's evaluation of feature subsets was A_z, the area under the ROC curve produced by the corresponding BBN classifier. For each feature subset evaluated by the GA, a BBN was developed to classify positive and negative cases. Overall performance of the BBNs was evaluated using a jackknife testing method to calculate A_z, for their respective ROC curves. The A_z value of the BBN incorporating all 21 features was 0.851 plus or minus 0.012. After a 93 generation search, the GA found an optimal feature set with four non-image and four mammographic features, which achieved an A_z value of 0.927 plus or minus 0.009. This study suggests that GAs are a viable means to optimize feature sets, and optimizing feature sets can result in significant performance improvements.

Citation Download Citation

Xiao Hui Wang, Bin Zheng, Yuan-Hsiang Chang, and Walter F. Good "Optimizing the feature set for a Bayesian network for breast cancer diagnosis using genetic algorithm techniques", Proc. SPIE 3661, Medical Imaging 1999: Image Processing, (21 May 1999); https://doi.org/10.1117/12.348560

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