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<front>
<journal-meta>
<journal-id journal-id-type="publisher">global-journal-of-computer-science-and-technology-g-interdisciplinary</journal-id>
<journal-title-group>
<journal-title>Global Journal of Computer Science and Technology - G: Interdisciplinary</journal-title>
</journal-title-group>
<issn publication-format="print">0975-4350</issn>
<issn publication-format="electronic">0975-4172</issn>
<publisher><publisher-name>Global Journals Publishing Group Incorporated</publisher-name></publisher>
<self-uri xlink:href="https://globaljournals.org/journal-seo-export/jats/89028.xml" />
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<article-meta>
<article-id pub-id-type="publisher-id">89028</article-id>
<title-group>
<article-title>Colon Cancer Prediction based on Artificial Neural Network</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author"><name><surname>Sabuj</surname><given-names>1. Md. Asaduzzaman</given-names></name><xref ref-type="aff" rid="aff1" />
</contrib>
</contrib-group>
<aff id="aff1">BANGLADESH, Chittagong University of Engineering and Technology</aff>
<pub-date publication-format="electronic" date-type="pub" iso-8601-date="2013-01-15">
<day>15</day>
<month>01</month>
<year>2013</year>
</pub-date>
<volume>13</volume>
<issue>G3</issue>
<fpage>23</fpage>
<lpage>27</lpage>
<abstract><p>Artificial neural networks (ANNs) consists of computational neurons or processing elements are linear mathematical model which abstract away the complex biological model and its aim is good, human like predictive ability. Artificial intelligence tries to simulate some properties of biological neural networks. In this study on the basis of previous dataset the in symptoms data are applied to a supervised back propagation artificial neural network learning process to find out the predictive outcome which is better than logistic regression (LR) process. As in most cases ANN is an adaptive system that changes its structure on the basis of internal and external information, the predictive result is more accurate than any other processes.</p></abstract>
<kwd-group kwd-group-type="author-generated">
<kwd>artificial neural network</kwd>
<kwd>back propagation</kwd>
<kwd>colon cancer</kwd>
<kwd>supervised learning</kwd>
<kwd>prediction.</kwd>
</kwd-group>
<self-uri content-type="pdf" xlink:href="https://globaljournals.org/GJCST_Volume13/4-Colon-Cancer-Prediction.pdf" />
<self-uri content-type="html" xlink:href="https://globaljournals.org/scholarly-articles/colon-cancer-prediction-based-on-artificial-neural-network/" />
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<title>Full Text</title>
<p>Artificial neural networks (ANNs) consists of computational neurons or processing elements are linear mathematical model which abstract away the complex biological model and its aim is good, human like predictive ability. Artificial intelligence tries to simulate some properties of biological neural networks. In this study on the basis of previous dataset the in symptoms data are applied to a supervised back propagation artificial neural network learning process to find out the predictive outcome which is better than logistic regression (LR) process. As in most cases ANN is an adaptive system that changes its structure on the basis of internal and external information, the predictive result is more accurate than any other processes.</p>
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</body>
</article>