<?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>0121-1129</journal-id>
<journal-title><![CDATA[Revista Facultad de Ingeniería]]></journal-title>
<abbrev-journal-title><![CDATA[Rev. Fac. ing.]]></abbrev-journal-title>
<issn>0121-1129</issn>
<publisher>
<publisher-name><![CDATA[Universidad Pedagógica y Tecnológica de Colombia]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0121-11292024000100005</article-id>
<article-id pub-id-type="doi">10.19053/01211129.v33.n67.2024.16943</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[HASCC: A Hybrid Algorithm for Skin Cancer Classification]]></article-title>
<article-title xml:lang="es"><![CDATA[HASCC: Algoritmo Híbrido para Clasificación de Cáncer de Piel]]></article-title>
<article-title xml:lang="pt"><![CDATA[HASCC: Algoritmo Híbrido para Classificação de Câncer de Pele]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Niño-Rondón]]></surname>
<given-names><![CDATA[Carlos-Vicente]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Castellano-Carvajal]]></surname>
<given-names><![CDATA[Diego-Andrés]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Castro-Casadiego]]></surname>
<given-names><![CDATA[Sergio-Alexander]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Medina-Delgado]]></surname>
<given-names><![CDATA[Byron]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Puerto-López]]></surname>
<given-names><![CDATA[Karla-Cecilia]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Pontificia Universidad Javeriana  ]]></institution>
<addr-line><![CDATA[Cali Valle del Cauca]]></addr-line>
<country>Colombia</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Universidad Francisco de Paula Santander  ]]></institution>
<addr-line><![CDATA[Cucutá Norte de Santander]]></addr-line>
<country>Colombia</country>
</aff>
<aff id="Af3">
<institution><![CDATA[,Universidad Francisco de Paula Santander  ]]></institution>
<addr-line><![CDATA[Cucutá Norte de Santander]]></addr-line>
<country>Colombia</country>
</aff>
<aff id="Af4">
<institution><![CDATA[,Universidad Francisco de Paula Santander  ]]></institution>
<addr-line><![CDATA[Cucutá Norte de Santander]]></addr-line>
<country>Colombia</country>
</aff>
<aff id="Af5">
<institution><![CDATA[,Universidad Francisco de Paula Santander  ]]></institution>
<addr-line><![CDATA[Cucutá Norte de Santander]]></addr-line>
<country>Colombia</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>03</month>
<year>2024</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>03</month>
<year>2024</year>
</pub-date>
<volume>33</volume>
<numero>67</numero>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_arttext&amp;pid=S0121-11292024000100005&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_abstract&amp;pid=S0121-11292024000100005&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_pdf&amp;pid=S0121-11292024000100005&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract Skin cancer is a dangerous and potentially lethal disease that is steadily increasing worldwide. Signs of skin cancer may include changes in the appearance of moles or the emergence of new spots on the skin. Early detection is crucial, as many types of skin cancer respond well to treatment when addressed in the early stages. Computer-aided diagnostic tools are employed to aid in the diagnosis of this disease. This article introduces HASCC, a hybrid algorithm implemented through a graphical user interface for skin cancer classification. The algorithm integrates image processing, feature extraction using the VGG16 algorithm with component reduction through PCA, and classification using XGBoost trained on images from the HAM10000 dataset. The hybrid algorithm was executed and tested on a Raspberry Pi 4 embedded system. HASCC was compared at both hardware and software levels with other computational intelligence methods and architectures, revealing notable improvements in terms of accuracy, ranging from 88.2% to 93.2%, with an average execution time of 250 milliseconds at low machine resource demand during the diagnostic process. Additionally, HASCC's performance was compared against previous research focused on skin cancer detection and classification. The hardware performance demonstrates that HASCC can be implemented on single-board microprocessor devices, and its software performance suggests viability for supporting the diagnosis and classification of skin cancer.]]></p></abstract>
<abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen El cáncer de piel es una enfermedad peligrosa y potencialmente letal que aumenta constantemente en los reportes de casos de cáncer a nivel mundial. Los signos de cáncer de piel pueden incluir cambios en la apariencia de los lunares o la aparición de nuevas manchas en la piel. La detección temprana es fundamental, ya que muchos tipos de cáncer de piel responden bien al tratamiento si se abordan en las etapas iniciales. Para el apoyo en el diagnóstico de esta enfermedad se emplean herramientas de diagnóstico asistido. Este artículo presenta HASCC, un algoritmo híbrido implementado mediante una interfaz gráfica de usuario para la clasificación del cáncer de piel. El algoritmo integra procesamiento de imágenes, extracción de características mediante el algoritmo VGG16 con reducción de componentes mediante PCA y clasificación mediante XGBoost entrenado con imágenes del Conjunto de Datos HAM10000. El algoritmo híbrido se ejecutó y se probó sobre un sistema embebido Raspberry Pi 4. HASCC se comparó a nivel hardware y a nivel software con otros métodos y arquitecturas de inteligencia computacional, y se obtuvo que el sistema propuesto mostró mejores notables en términos de precisión, que osciló entre el 88.2 % y 93.2 %, con un tiempo promedio de ejecución de 250 milisegundos a baja demanda de recursos de máquina durante el proceso de diagnóstico. Adicionalmente, el rendimiento de HASCC se comparó contra investigaciones previas enfocadas a la detección y clasificación de cáncer de piel. El rendimiento a nivel hardware demuestra que HASCC es viable para implementación en dispositivos microprocesadores de placa única, y con su desempeño a nivel de software se infiere que es viable para el apoyo en el diagnóstico y clasificación del cáncer de piel.]]></p></abstract>
<abstract abstract-type="short" xml:lang="pt"><p><![CDATA[Resumo O câncer de pele é uma doença perigosa e potencialmente letal que vem aumentando constantemente nos relatos de casos de câncer em todo o mundo. Os sinais de câncer de pele podem incluir alterações na aparência de manchas ou aparecimento de novas manchas na pele. A detecção precoce é essencial, pois muitos tipos de câncer de pele respondem bem ao tratamento se tratados nos estágios iniciais. Ferramentas de diagnóstico assistido são utilizadas para apoiar o diagnóstico desta doença. Este artigo apresenta o HASCC, um algoritmo híbrido implementado usando uma interface gráfica de usuário para classificação do câncer de pele. O algoritmo integra processamento de imagens, extração de características usando o algoritmo VGG16 com redução de componentes usando PCA e classificação usando XGBoost treinado com imagens do Dataset HAM10000. O algoritmo híbrido foi executado e testado em um sistema embarcado Raspberry Pi 4 e comparado a nível de hardware e a nível de software com outros métodos e arquiteturas de inteligência computacional, e obteve-se que o sistema proposto apresentou melhores resultados em termos de precisão. , que variou de 88,2% a 93,2%, com tempo médio de execução de 250 milissegundos com baixa demanda de recursos da máquina durante o processo de diagnóstico. Além disso, o desempenho do HASCC foi comparado com pesquisas anteriores focadas na detecção e classificação do câncer de pele. O desempenho ao nível do hardware demonstra que o HASCC é viável para implementação em dispositivos microprocessados &#8203;&#8203;de placa única, e com o seu desempenho ao nível do software infere-se que é viável para apoiar o diagnóstico e classificação do cancro da pele.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[computer-aided diagnosis]]></kwd>
<kwd lng="en"><![CDATA[embedded system]]></kwd>
<kwd lng="en"><![CDATA[graphical user interface]]></kwd>
<kwd lng="en"><![CDATA[hybrid algorithm]]></kwd>
<kwd lng="en"><![CDATA[open-source]]></kwd>
<kwd lng="en"><![CDATA[skin cancer]]></kwd>
<kwd lng="es"><![CDATA[algoritmo híbrido]]></kwd>
<kwd lng="es"><![CDATA[cáncer de piel]]></kwd>
<kwd lng="es"><![CDATA[código abierto]]></kwd>
<kwd lng="es"><![CDATA[diagnóstico asistido por computador]]></kwd>
<kwd lng="es"><![CDATA[interfaz gráfica de usuario]]></kwd>
<kwd lng="es"><![CDATA[sistema embebido]]></kwd>
<kwd lng="pt"><![CDATA[algoritmo híbrido]]></kwd>
<kwd lng="pt"><![CDATA[câncer de pele]]></kwd>
<kwd lng="pt"><![CDATA[código aberto]]></kwd>
<kwd lng="pt"><![CDATA[diagnóstico auxiliado por computador]]></kwd>
<kwd lng="pt"><![CDATA[interface gráfica do usuário]]></kwd>
<kwd lng="pt"><![CDATA[sistema embarcado]]></kwd>
</kwd-group>
</article-meta>
</front><back>
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