<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>1405-5546</journal-id>
<journal-title><![CDATA[Computación y Sistemas]]></journal-title>
<abbrev-journal-title><![CDATA[Comp. y Sist.]]></abbrev-journal-title>
<issn>1405-5546</issn>
<publisher>
<publisher-name><![CDATA[Instituto Politécnico Nacional, Centro de Investigación en Computación]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S1405-55462024000402221</article-id>
<article-id pub-id-type="doi">10.13053/cys-28-4-5296</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[Breast Cancer Classification through Mixture of Bivariate Normal Using EM Algorithm]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Martínez-Guzmán]]></surname>
<given-names><![CDATA[Gerardo]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Cerón-Garnica]]></surname>
<given-names><![CDATA[Carmen]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Fernández-Pérez]]></surname>
<given-names><![CDATA[Jorge Alejandro]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Villegas-Cerón]]></surname>
<given-names><![CDATA[Gerardo]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Benemérita Universidad Autónoma de Puebla Facultad de Ciencias de la Computación ]]></institution>
<addr-line><![CDATA[Puebla ]]></addr-line>
<country>Mexico</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Benemérita Universidad Autónoma de Puebla Instituto de Ciencias ]]></institution>
<addr-line><![CDATA[Puebla ]]></addr-line>
<country>Mexico</country>
</aff>
<aff id="Af3">
<institution><![CDATA[,Benemérita Universidad Autónoma de Puebla Facultad de Medicina ]]></institution>
<addr-line><![CDATA[Puebla ]]></addr-line>
<country>Mexico</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>12</month>
<year>2024</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>12</month>
<year>2024</year>
</pub-date>
<volume>28</volume>
<numero>4</numero>
<fpage>2221</fpage>
<lpage>2230</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S1405-55462024000402221&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S1405-55462024000402221&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S1405-55462024000402221&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract: An analysis is presented in this paper for benign and malignant diagnosis of tumors, biopsies have shown an increase of nuclear size, and changes in the texture of the tumor nucleus. In this article, an analysis is made using the unsupervised learning algorithm Expectation-Maximization (EM). Two variables are analyzed: the mean of the radius and texture of the tumors, being the former a measure of the average distances from the center of the tumor to its perimeter, and the latest is the variance of gray-scale values. Since the behavior of the said variables is similar to the mixture of normals in two opposing categories. The EM algorithms demonstrates ability to categorize the dataset into two different labels (malignant and benign). This model projects a classification with a high percentage of coincidence with the observed data.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[Maximum likelihood estimators]]></kwd>
<kwd lng="en"><![CDATA[breast cancer]]></kwd>
<kwd lng="en"><![CDATA[EM algorithm]]></kwd>
<kwd lng="en"><![CDATA[Gaussian mixture model]]></kwd>
</kwd-group>
</article-meta>
</front><back>
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