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A Breast Cancer Diagnosis System using Hybrid Case-based Approach

by Dina A. Sharaf-el Deen, Ibrahim F. Moawad, M. E. Khalifa
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 72 - Number 23
Year of Publication: 2013
Authors: Dina A. Sharaf-el Deen, Ibrahim F. Moawad, M. E. Khalifa
10.5120/12681-9450

Dina A. Sharaf-el Deen, Ibrahim F. Moawad, M. E. Khalifa . A Breast Cancer Diagnosis System using Hybrid Case-based Approach. International Journal of Computer Applications. 72, 23 ( June 2013), 14-20. DOI=10.5120/12681-9450

@article{ 10.5120/12681-9450,
author = { Dina A. Sharaf-el Deen, Ibrahim F. Moawad, M. E. Khalifa },
title = { A Breast Cancer Diagnosis System using Hybrid Case-based Approach },
journal = { International Journal of Computer Applications },
issue_date = { June 2013 },
volume = { 72 },
number = { 23 },
month = { June },
year = { 2013 },
issn = { 0975-8887 },
pages = { 14-20 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume72/number23/12681-9450/ },
doi = { 10.5120/12681-9450 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:38:51.019766+05:30
%A Dina A. Sharaf-el Deen
%A Ibrahim F. Moawad
%A M. E. Khalifa
%T A Breast Cancer Diagnosis System using Hybrid Case-based Approach
%J International Journal of Computer Applications
%@ 0975-8887
%V 72
%N 23
%P 14-20
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Nowadays, mammography is recognized as the most effective technique for breast cancer diagnosis. Case-Based Reasoning (CBR) is one of the important techniques used to diagnose the breast cancer disease. The retrieval-only CBR systems do not provide an acceptable accuracy in critical domains such as medical. In this paper, a new breast cancer diagnosis system using hybrid case-based approach is presented to improve the accuracy of the retrieval-only CBR systems. The approach integrates case-based reasoning and rule-based reasoning, and applies the adaptation process automatically by exploiting adaptation rules. Both adaptation rules and reasoning rules are generated automatically from the case-base. After solving a new case, the case-base is expanded, and both adaptation and reasoning rules are updated automatically. To evaluate the proposed approach, a prototype was implemented and experimented to diagnose the breast cancerdisease. The final results showed that the proposed approach increases the diagnosing accuracy comparing with the retrieval-only CBR systems, and provides a reliable accuracy comparing to the current breast cancer diagnosis systems.

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Index Terms

Computer Science
Information Sciences

Keywords

Case-based reasoning (CBR) Rule-based reasoning (RBR) Adaptation rules Breast cancer diagnosis Mammography

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