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Expert System for Staging Breast Cancer

by Adenike Adegoke-Elijah, Adewale Adisa, Chidiebere Raphael
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 183 - Number 52
Year of Publication: 2022
Authors: Adenike Adegoke-Elijah, Adewale Adisa, Chidiebere Raphael

Adenike Adegoke-Elijah, Adewale Adisa, Chidiebere Raphael . Expert System for Staging Breast Cancer. International Journal of Computer Applications. 183, 52 ( Feb 2022), 34-39. DOI=10.5120/ijca2022921941

@article{ 10.5120/ijca2022921941,
author = { Adenike Adegoke-Elijah, Adewale Adisa, Chidiebere Raphael },
title = { Expert System for Staging Breast Cancer },
journal = { International Journal of Computer Applications },
issue_date = { Feb 2022 },
volume = { 183 },
number = { 52 },
month = { Feb },
year = { 2022 },
issn = { 0975-8887 },
pages = { 34-39 },
numpages = {9},
url = { },
doi = { 10.5120/ijca2022921941 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-07T01:19:45.697849+05:30
%A Adenike Adegoke-Elijah
%A Adewale Adisa
%A Chidiebere Raphael
%T Expert System for Staging Breast Cancer
%J International Journal of Computer Applications
%@ 0975-8887
%V 183
%N 52
%P 34-39
%D 2022
%I Foundation of Computer Science (FCS), NY, USA

The task of staging breast cancer is very essential in the management of the disease. This is because the stage of the disease determines the most appropriate treatment to be given to patients, and this consequently determines the rate of mortality due to the menace. Despite its importance, staging of breast cancer is cumbersome and requires experiential knowledge for it to be adequately done. New and inexperienced doctors therefore depend on consultant oncologists to carry out this task. This study therefore adopted a traditional rule-based approach to develop an expert system than could serve as a decision support system for inexperienced doctors in staging breast cancer. To achieve this aim, knowledge of the symptoms and the criteria for staging were elicited from the Association of American Cancer Society. The elicited knowledge was represented procedurally using IF-THEN rule. The Breast Cancer Staging System was later implemented using JAVA programming language, The developed system was evaluated for accuracy, reliability and usability using Mean Opinion Score; and the scores gotten were 4.12, 4.12 and 4.08 respectively. This study has therefore developed a computational tool that could reduce the bottlenecks in staging breast cancer and subsequently reduce mortality rate due to the disease.

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Index Terms

Computer Science
Information Sciences


Breast Cancer Breast Cancer Staging Expert System Rule-based system