<?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>1645-0086</journal-id>
<journal-title><![CDATA[Psicologia, Saúde & Doenças]]></journal-title>
<abbrev-journal-title><![CDATA[Psic., Saúde & Doenças]]></abbrev-journal-title>
<issn>1645-0086</issn>
<publisher>
<publisher-name><![CDATA[Sociedade Portuguesa de Psicologia da Saúde]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S1645-00862023000100189</article-id>
<article-id pub-id-type="doi">10.15309/23psd240116</article-id>
<title-group>
<article-title xml:lang="pt"><![CDATA[Redes neurais artificiais e satisfação por compaixão em profissionais de saúde]]></article-title>
<article-title xml:lang="en"><![CDATA[Artificial neural networks and satisfaction for compassion in health professionals]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Torres]]></surname>
<given-names><![CDATA[Jaqueline]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Silva Junior]]></surname>
<given-names><![CDATA[Rene]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Barbosa]]></surname>
<given-names><![CDATA[Henrique]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Alves]]></surname>
<given-names><![CDATA[Elaine]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Mendes]]></surname>
<given-names><![CDATA[Danilo]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[D`Angelo]]></surname>
<given-names><![CDATA[Marcos]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Silva]]></surname>
<given-names><![CDATA[Carla]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidade Estadual de Montes Claros  ]]></institution>
<addr-line><![CDATA[Montes Claros ]]></addr-line>
<country>Brazil</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Universidade Estadual de Montes Claros Departamento de enfermagem ]]></institution>
<addr-line><![CDATA[Montes Claros ]]></addr-line>
<country>Brazil</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>04</month>
<year>2023</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>04</month>
<year>2023</year>
</pub-date>
<volume>24</volume>
<numero>1</numero>
<fpage>189</fpage>
<lpage>198</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://scielo.pt/scielo.php?script=sci_arttext&amp;pid=S1645-00862023000100189&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.pt/scielo.php?script=sci_abstract&amp;pid=S1645-00862023000100189&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.pt/scielo.php?script=sci_pdf&amp;pid=S1645-00862023000100189&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="pt"><p><![CDATA[Resumo Este estudo objetiva construir um modelo de predição à satisfação por compaixão entre os profissionais de saúde que atendem pacientes críticos e crônicos, por meio da criação de uma rede neural artificial. A rede neural resultante possui sete camadas com 12 neurônios na camada de entrada, representados por características sociodemográficas; 20, 10, 10, 5 e 4 neurônios nas camadas intermediárias; e 1 neurônio na camada de saída representando a &#8220;Satisfação por Compaixão&#8221;. Foi utilizada a função logística como função de transferência dos neurônios das 5 primeiras camadas, onde a ativação da última camada foi linear. Adotou-se o Algoritmo Genético de Classificação Não Dominante, em sua segunda versão. As simulações foram realizadas com o software MATLAB® versão R2017a. O melhor resultado foi apresentado pela inclusão de 12 variáveis, com acurácia final de 94,5%. A rede neural artificial construída é uma ferramenta inovadora para o estudo da qualidade de vida profissional.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract This study aims to build a model of prediction of satisfaction by compassion among health professionals who care for critical and chronic patients, through the creation of an artificial neural network. The resulting neural network has seven layers with 12 neurons in the input layer, represented by sociodemographic characteristics; 20, 10, 10, 5 and 4 neurons in the intermediate layers; and 1 neuron in the output layer representing &#8220;Satisfaction by Compassion&#8221;. The logistic function was used as a transfer function for neurons in the first 5 layers, where the activation of the last layer was linear. The Non-Dominant Genetic Classification Algorithm was adopted in its second version. The simulations were carried out with MATLAB® software version R2017a. The best result was presented by the inclusion of 12 variables, with a final accuracy of 94.5%. The artificial neural network built is an innovative tool for studying the quality of professional life.]]></p></abstract>
<kwd-group>
<kwd lng="pt"><![CDATA[Inteligência artificial]]></kwd>
<kwd lng="pt"><![CDATA[Fadiga por compaixão]]></kwd>
<kwd lng="pt"><![CDATA[Qualidade de vida]]></kwd>
<kwd lng="pt"><![CDATA[Saúde do trabalhador]]></kwd>
<kwd lng="pt"><![CDATA[Satisfação no emprego]]></kwd>
<kwd lng="en"><![CDATA[Artificial intelligence]]></kwd>
<kwd lng="en"><![CDATA[Compassion fatigue]]></kwd>
<kwd lng="en"><![CDATA[Quality of life]]></kwd>
<kwd lng="en"><![CDATA[Occupational health]]></kwd>
<kwd lng="en"><![CDATA[Job satisfaction]]></kwd>
</kwd-group>
</article-meta>
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<given-names><![CDATA[J.]]></given-names>
</name>
<name>
<surname><![CDATA[Barbosa]]></surname>
<given-names><![CDATA[H.]]></given-names>
</name>
<name>
<surname><![CDATA[Pereira]]></surname>
<given-names><![CDATA[S.]]></given-names>
</name>
<name>
<surname><![CDATA[Cunha]]></surname>
<given-names><![CDATA[F.]]></given-names>
</name>
<name>
<surname><![CDATA[Torres]]></surname>
<given-names><![CDATA[S.]]></given-names>
</name>
<name>
<surname><![CDATA[Brito]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
<name>
<surname><![CDATA[Pinho]]></surname>
<given-names><![CDATA[L.]]></given-names>
</name>
<name>
<surname><![CDATA[Mendes]]></surname>
<given-names><![CDATA[D.]]></given-names>
</name>
<name>
<surname><![CDATA[Silva]]></surname>
<given-names><![CDATA[C.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Qualidade de vida profissional e fatores associados em profissionais de saúde]]></article-title>
<source><![CDATA[Psicologia, Saúde &amp; Doenças]]></source>
<year>2019</year>
<volume>20</volume>
<numero>3</numero>
<issue>3</issue>
<page-range>670-81</page-range></nlm-citation>
</ref>
</ref-list>
</back>
</article>
