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International Journal of Nonlinear Sciences and Numerical Simulation

Editor-in-Chief: Birnir, Björn

Editorial Board: Armbruster, Dieter / Bessaih, Hakima / Chou, Tom / Grauer, Rainer / Marzocchella, Antonio / Rangarajan, Govindan / Trivisa, Konstantina / Weikard, Rudi

8 Issues per year


IMPACT FACTOR 2017: 1.162

CiteScore 2017: 1.41

SCImago Journal Rank (SJR) 2017: 0.382
Source Normalized Impact per Paper (SNIP) 2017: 0.636

Mathematical Citation Quotient (MCQ) 2017: 0.12

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2191-0294
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Volume 19, Issue 6

Issues

An Automated Computer System Based on Genetic Algorithm and Fuzzy Systems for Lung Cancer Diagnosis

Abir Alharbi
Published Online: 2018-07-19 | DOI: https://doi.org/10.1515/ijnsns-2017-0048

Abstract

An automated system for the diagnosis of lung cancer is proposed in this paper, the system is designed by combining two major methodologies, namely the fuzzy base systems and the evolutionary genetic algorithms (GAs), to be employed on lung cancer data to assist physicians in the early detection of lung cancers, and hence obtain an early automated diagnosis complementary to that by physicians. Our hybrid algorithm, the genetic-fuzzy algorithm, has produced optimized diagnosis systems that attain high classification performance, in fact, our best six rule system obtained a 97.5 % accuracy, with simple and well interpretive rules, with 93 % degree of confidence, and without the need for dimensionality reduction. The results on real data indicate that the proposed system is very effective in the diagnosis of lung cancer and can be used for clinical applications.

Keywords: fuzzy systems; genetic algorithms; optimization methods; lung cancer; computer-aided diagnosis (CAD)

JEL Classification: 68T01; 68T20; 03B52; 65Y10

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About the article

Received: 2017-02-16

Accepted: 2018-07-07

Published Online: 2018-07-19

Published in Print: 2018-09-25


Citation Information: International Journal of Nonlinear Sciences and Numerical Simulation, Volume 19, Issue 6, Pages 583–594, ISSN (Online) 2191-0294, ISSN (Print) 1565-1339, DOI: https://doi.org/10.1515/ijnsns-2017-0048.

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