<?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>S1405-55462025000100241</article-id>
<article-id pub-id-type="doi">10.13053/cys-29-1-5502</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[Applied Unsupervised Learning for Pattern Recognition of Depression Cases within a Young Adult Population]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Mendoza]]></surname>
<given-names><![CDATA[Octavio]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Tovar Vidal]]></surname>
<given-names><![CDATA[Mireya]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Contreras]]></surname>
<given-names><![CDATA[Meliza]]></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[ ]]></addr-line>
<country>Mexico</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>03</month>
<year>2025</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>03</month>
<year>2025</year>
</pub-date>
<volume>29</volume>
<numero>1</numero>
<fpage>241</fpage>
<lpage>251</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S1405-55462025000100241&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S1405-55462025000100241&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S1405-55462025000100241&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract: This study uses unsupervised learning to identify depression patterns in Mexican university students. By analyzing demographic, academic, and psychological factors, it aims to uncover subgroups with similar depression profiles and identify risk and protective factors. The study compares clustering algorithms and evaluates their performance using metrics like the Silhouette Coefficient and Davies-Bouldin Index. This research contributes to the field of machine learning in mental health and may improve support services for students at risk of depression.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[Clustering]]></kwd>
<kwd lng="en"><![CDATA[pattern recognition]]></kwd>
<kwd lng="en"><![CDATA[depression]]></kwd>
</kwd-group>
</article-meta>
</front><back>
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