Title

Consistent and complete data and “expert” mining in medicine

Authors

Boris Kovalerchuk, Central Washington UniversityFollow
Evgenii Vityaev, Russian Academy of Sciences
James F. Ruiz, Baton Rouge Women's Hospital

Document Type

Article

Department or Administrative Unit

Computer Science

Publication Date

2001

Abstract

The ultimate purpose of many medical data mining systems is to create formalized knowledge for a computer-aided diagnostic system, which can in turn, provide a second diagnostic opinion. Such systems should be consistent and complete as much as possible. The system is consistent if it is free of contradictions (between rules in a computer-aided diagnostic system, rules used by an experienced medical expert and a database of pathologically confirmed cases). The system is complete if it is able to cover (classify) all (or largest possible number of) combinations of the used attributes. A method for discovering a consistent and complete set of diagnostic rules is presented in this chapter. Advantages of the method are shown for development of a breast cancer computer-aided diagnostic system.

Comments

This book chapter was originally published in Medical Data Mining and Knowledge Discovery. The book from the publisher can be found here.

Due to copyright restrictions, this article is not available for free download from ScholarWorks @ CWU.

Recommended Citation

B. Kovalerchuck, E. Vitaev, & J. F. Ruiz, "Consistent and complete data and 'expert' mining in medicine," in Medical Data Mining and Knowledge Discovery, Springer, 2001.

Rights

© Physica-Verlag Heidelberg