A rough set based data model for breast cancer mammographic mass diagnostics

College

Gokongwei College of Engineering

Department/Unit

Electronics And Communications Engg

Document Type

Article

Source Title

International Journal of Biomedical Engineering and Technology

Volume

18

Issue

4

First Page

359

Last Page

369

Publication Date

1-1-2015

Abstract

Breast cancer is the principal cause of cancer deaths among women, and early diagnosis is critical to its survival. Mammography is the recommended diagnostic procedure for ages 40 years and older. However, the low precision rate of mammographic result leads to needless biopsies. Thus, in this paper, we present the application of rough set theory in the development of a data model to aid in physician's recommendation for biopsy. In particular, we will utilise the data obtained at the Institute of Radiology of the University Erlangen-Nuremberg between 2003 and 2006. The results showed that the rough set approach successfully reduced the dimensionality of the aforementioned data set by approximately 47%, and the outcome rules were validated using empirical testing at 100%. Copyright © 2015 Inderscience Enterprises Ltd.

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Digitial Object Identifier (DOI)

10.1504/IJBET.2015.071010

Disciplines

Biomedical Engineering and Bioengineering

Keywords

Biomedical engineering; Breast—Cancer—Diagnosis; Rough sets; Decision support systems

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