Application of a GRNN oracle to the intelligent combination of several breast cancer benign/malignant predictive paradigms

Walker H. Land, Timothy Masters, Clayton T. Morrison, Joseph Y. Lo

Research output: Contribution to conferencePaper

Abstract

The General Regression Neural Network (GRNN) is well known to be an extremely effective prediction model in a wide variety of problems. It has been recently established that in many prediction problems, the results obtained by intelligently combining the outputs of several different prediction models are generally superior to the results obtained by using any one of the models. An overseer model that combines predictions from other independently trained prediction models is often called an oracle. This paper describes how the GRNN is modified to serve as a powerful oracle for combining decisions from four different breast cancer benign/malignant prediction models using mammogram data. In all experiments conducted, the oracle consistently provided superior benign/malignant classification discrimination as measured by the receiver operator characteristic curve Az index values.

Original languageEnglish (US)
Pages803-808
Number of pages6
StatePublished - Dec 1 1999
Externally publishedYes
EventProceedings of the 1999 Artificial Neural Networks in Engineering Conference (ANNIE '99) - St. Louis, MO, USA
Duration: Nov 7 1999Nov 10 1999

Other

OtherProceedings of the 1999 Artificial Neural Networks in Engineering Conference (ANNIE '99)
CitySt. Louis, MO, USA
Period11/7/9911/10/99

ASJC Scopus subject areas

  • Software

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  • Cite this

    Land, W. H., Masters, T., Morrison, C. T., & Lo, J. Y. (1999). Application of a GRNN oracle to the intelligent combination of several breast cancer benign/malignant predictive paradigms. 803-808. Paper presented at Proceedings of the 1999 Artificial Neural Networks in Engineering Conference (ANNIE '99), St. Louis, MO, USA, .