Applying knowledge engineering and representation methods to improve support vector machine and multivariate probabilistic neural network CAD performance

Walker H. Land Jr.; Frances Anderson; Tom Smith; Stephen Fahlbusch; Robert Choma; Lut Wong

doi:10.1117/12.593683

29 April 2005 Applying knowledge engineering and representation methods to improve support vector machine and multivariate probabilistic neural network CAD performance

Walker H. Land Jr., Frances Anderson, Tom Smith, Stephen Fahlbusch, Robert Choma, Lut Wong

Author Affiliations +

Proceedings Volume 5747, Medical Imaging 2005: Image Processing; (2005) https://doi.org/10.1117/12.593683
Event: Medical Imaging, 2005, San Diego, California, United States

Abstract

Achieving consistent and correct database cases is crucial to the correct evaluation of any computer-assisted diagnostic (CAD) paradigm. This paper describes the application of artificial intelligence (AI), knowledge engineering (KE) and knowledge representation (KR) to a data set of ≈2500 cases from six separate hospitals, with the objective of removing/reducing inconsistent outlier data. Several support vector machine (SVM) kernels were used to measure diagnostic performance of the original and a “cleaned” data set. Specifically, KE and ER principles were applied to the two data sets which were re-examined with respect to the environment and agents. One data set was found to contain 25 non-characterizable sets. The other data set contained 180 non-characterizable sets. CAD system performance was measured with both the original and “cleaned” data sets using two SVM kernels as well as a multivariate probabilistic neural network (PNN). Results demonstrated: (i) a 10% average improvement in overall Az and (ii) approximately a 50% average improvement in partial Az.

Citation Download Citation

Walker H. Land Jr., Frances Anderson, Tom Smith, Stephen Fahlbusch, Robert Choma, and Lut Wong "Applying knowledge engineering and representation methods to improve support vector machine and multivariate probabilistic neural network CAD performance", Proc. SPIE 5747, Medical Imaging 2005: Image Processing, (29 April 2005); https://doi.org/10.1117/12.593683

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