<?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>1646-9895</journal-id>
<journal-title><![CDATA[RISTI - Revista Ibérica de Sistemas e Tecnologias de Informação]]></journal-title>
<abbrev-journal-title><![CDATA[RISTI]]></abbrev-journal-title>
<issn>1646-9895</issn>
<publisher>
<publisher-name><![CDATA[AISTI - Associação Ibérica de Sistemas e Tecnologias de Informação]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S1646-98952023000200005</article-id>
<article-id pub-id-type="doi">10.17013/risti.50.5-27</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Una revisión sistemática de Modelos de clasificación de dengue utilizando machine learning]]></article-title>
<article-title xml:lang="en"><![CDATA[A systematic review of dengue classification models using machine learning.]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Maquen-Niño]]></surname>
<given-names><![CDATA[Gisella Luisa Elena]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Bravo]]></surname>
<given-names><![CDATA[Jessie]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Alarcón]]></surname>
<given-names><![CDATA[Roger]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Adrianzén-Olano]]></surname>
<given-names><![CDATA[Ivan]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Vega-Huerta]]></surname>
<given-names><![CDATA[Hugo]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad Nacional Pedro Ruiz Gallo Grupo de Investigación en transformación digital ]]></institution>
<addr-line><![CDATA[Lambayeque ]]></addr-line>
<country>Peru</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Universidad Nacional Toribio Rodriguez de Mendoza  ]]></institution>
<addr-line><![CDATA[Chachapoyas ]]></addr-line>
<country>Peru</country>
</aff>
<aff id="Af3">
<institution><![CDATA[,Universidad Nacional Mayor de San Marcos UNMSM  ]]></institution>
<addr-line><![CDATA[Lima ]]></addr-line>
<country>Peru</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>06</month>
<year>2023</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>06</month>
<year>2023</year>
</pub-date>
<numero>50</numero>
<fpage>5</fpage>
<lpage>27</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://scielo.pt/scielo.php?script=sci_arttext&amp;pid=S1646-98952023000200005&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.pt/scielo.php?script=sci_abstract&amp;pid=S1646-98952023000200005&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.pt/scielo.php?script=sci_pdf&amp;pid=S1646-98952023000200005&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[El dengue es una enfermedad arboviral que anualmente reporta un gran número de infectados en la costa norte y la selva peruana. Según las estadísticas, está aumentando cada año. Este artículo tiene como objetivo desarrollar una revisión sistemática de la literatura científica sobre las variables de estudio y los métodos de aprendizaje automático utilizados actualmente para detectar la infección por dengue. La metodología utilizada fue PRISMA, mapeando inicialmente la literatura de 274 artículos científicos, quedando seleccionados 33 artículos para la revisión sistemática. Los resultados obtenidos son que los algoritmos de aprendizaje automático más utilizados son las redes neuronales (NN) y support vector machine (SVM). Asimismo, se ha encontrado que los científicos tienden a realizar investigaciones con variables climáticas o demográficas para obtener mejores resultados. Se concluye que los métodos de aprendizaje automático que más se han utilizado son las redes neuronales de diferentes tipos: convolucional, recurrente, profunda y multicapa, y para la predicción de brotes de dengue predominaron los métodos de series de tiempo con LSTM y ARIMA, también se estableció que la tendencia es hacia la inclusión de variables climáticas y demográficas en los modelos de predicción.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract Dengue is an arboviral disease that annually reports a large number of infected on the north coast and the Peruvian jungle. According to statistics, it is increasing yearly. This article aims to develop a systematic review of the scientific literature on the study variables and the machine learning methods currently used for detecting dengue infection. The methodology used was PRISMA, initially mapping the literature of 274 scientific articles, leaving 33 articles selected for the systematic review. The results obtained are that the most used machine learning algorithms are neural networks (NN) and support vector machine (SVM). Likewise, it has been found that scientists tend to carry out research with climatic or demographic variables to obtain better results. It is concluded that the machine learning methods that have been used the most are neural networks of different types: convolutional, recurrent, deep, and multilayer, and for the prediction of dengue outbreaks the time series methods with LSTM and ARIMA were the predominant ones, it was also established that the trend is towards the inclusion of climatic and demographic variables in the prediction models.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[Dengue]]></kwd>
<kwd lng="es"><![CDATA[detección]]></kwd>
<kwd lng="es"><![CDATA[machine learning]]></kwd>
<kwd lng="es"><![CDATA[métodos de clasificación]]></kwd>
<kwd lng="es"><![CDATA[algoritmos de clasificación]]></kwd>
<kwd lng="es"><![CDATA[random forest]]></kwd>
<kwd lng="es"><![CDATA[support vector machine]]></kwd>
<kwd lng="es"><![CDATA[artificial neural networks]]></kwd>
<kwd lng="en"><![CDATA[Dengue]]></kwd>
<kwd lng="en"><![CDATA[detection]]></kwd>
<kwd lng="en"><![CDATA[machine learning]]></kwd>
<kwd lng="en"><![CDATA[classification methods]]></kwd>
<kwd lng="en"><![CDATA[classification algorithms]]></kwd>
<kwd lng="en"><![CDATA[random forest]]></kwd>
<kwd lng="en"><![CDATA[support vector machine]]></kwd>
<kwd lng="en"><![CDATA[artificial neural networks]]></kwd>
</kwd-group>
</article-meta>
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