<?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>0035-001X</journal-id>
<journal-title><![CDATA[Revista mexicana de física]]></journal-title>
<abbrev-journal-title><![CDATA[Rev. mex. fis.]]></abbrev-journal-title>
<issn>0035-001X</issn>
<publisher>
<publisher-name><![CDATA[Sociedad Mexicana de Física]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0035-001X2023000600601</article-id>
<article-id pub-id-type="doi">10.31349/revmexfis.69.061101</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[Automatic image processing to identify post-COVID conditions by using deep learning]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Hernández-Trinidad]]></surname>
<given-names><![CDATA[A.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Córdova-Fraga]]></surname>
<given-names><![CDATA[T.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Padierna-García]]></surname>
<given-names><![CDATA[L. C.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Lopez-Hernández]]></surname>
<given-names><![CDATA[J. L.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Murillo-Ortiz]]></surname>
<given-names><![CDATA[B. O.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Guzmán-Cabrera]]></surname>
<given-names><![CDATA[R.]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad de Guanajuato División de Ciencias e Ingenierías ]]></institution>
<addr-line><![CDATA[Leon GTO]]></addr-line>
<country>Mexico</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Instituto Mexicano del Seguro Social Unidad de Investigacion en Epidemiología ]]></institution>
<addr-line><![CDATA[León GTO]]></addr-line>
<country>Mexico</country>
</aff>
<aff id="Af3">
<institution><![CDATA[,Universidad de Guanajuato División de Ingenierías ]]></institution>
<addr-line><![CDATA[Salamanca GTO]]></addr-line>
<country>Mexico</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>12</month>
<year>2023</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>12</month>
<year>2023</year>
</pub-date>
<volume>69</volume>
<numero>6</numero>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S0035-001X2023000600601&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S0035-001X2023000600601&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S0035-001X2023000600601&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract In the present research, a supervised learning classification methodology is proposed to identify post-COVID conditions. Image processing and deep learning methods were employed to analyze a data set provided by the High Specialty Medical Unit No.1 of the Mexican Institute of Social Security (T1-IMSS) of Leon, Guanajuato, Mexico, of Mexican patients infected with COVID-19. The dataset is classified into postCOVID findings and no post-COVID findings. A deep neural network of 50 hidden layers is used to extract regions of interest, with properties that can potentially be related to computer-aided medical diagnosis. Different patterns were found in the post-COVID computed tomography scans: pulmonary fibrosis, ground glass pattern, etc. The efficiency of the proposed method was 97% precision using the cross-validation classification scenario. This result allows to provide an auxiliary tool in medical diagnosis, through computer-aided diagnosis. This model provides an automatic and objective estimation of post-COVID conditions of Mexican patients, facilitating the expert interpretation during the COVID-19 pandemic.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[Image processing]]></kwd>
<kwd lng="en"><![CDATA[deep learning]]></kwd>
<kwd lng="en"><![CDATA[COVID-19]]></kwd>
<kwd lng="en"><![CDATA[Mexican patients]]></kwd>
<kwd lng="en"><![CDATA[medical diagnosis]]></kwd>
</kwd-group>
</article-meta>
</front><back>
<ref-list>
<ref id="B1">
<label>1</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Muñoz-Jarillo]]></surname>
<given-names><![CDATA[N. Y.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Infección por SARS-CoV-2 (COVID-19) y sus hallazgos por imagen]]></article-title>
<source><![CDATA[Rev. Fac. Med. (Mex.)]]></source>
<year>2020</year>
<volume>63</volume>
</nlm-citation>
</ref>
<ref id="B2">
<label>2</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Bakator]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
<name>
<surname><![CDATA[Radosav]]></surname>
<given-names><![CDATA[D.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Deep Learning and Medical Diagnosis: A Review of Literature]]></article-title>
<source><![CDATA[Multimodal Technol. Interact.]]></source>
<year>2018</year>
<volume>2</volume>
</nlm-citation>
</ref>
<ref id="B3">
<label>3</label><nlm-citation citation-type="confpro">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Mondal]]></surname>
<given-names><![CDATA[S.]]></given-names>
</name>
<name>
<surname><![CDATA[Agarwal]]></surname>
<given-names><![CDATA[K.]]></given-names>
</name>
<name>
<surname><![CDATA[Rashid]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
</person-group>
<source><![CDATA[Deep learning approach for automatic classification of x-ray images using convolutional neural network]]></source>
<year>2019</year>
<conf-name><![CDATA[ 2019 Fifth international conference on image information processing]]></conf-name>
<conf-loc> </conf-loc>
<page-range>326-31</page-range></nlm-citation>
</ref>
<ref id="B4">
<label>4</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Lakhani]]></surname>
<given-names><![CDATA[P.]]></given-names>
</name>
<name>
<surname><![CDATA[Sundaram]]></surname>
<given-names><![CDATA[B.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Deep learning at chest radiography: automated classification of pulmonary tuberculosis by using convolutional neural networks]]></article-title>
<source><![CDATA[Radiology]]></source>
<year>2017</year>
<volume>284</volume>
</nlm-citation>
</ref>
<ref id="B5">
<label>5</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Cichy]]></surname>
<given-names><![CDATA[R. M.]]></given-names>
</name>
<name>
<surname><![CDATA[Kaiser]]></surname>
<given-names><![CDATA[D.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Deep neural networks as scientific models]]></article-title>
<source><![CDATA[Trends Cogn. Sci.]]></source>
<year>2019</year>
<volume>23</volume>
</nlm-citation>
</ref>
<ref id="B6">
<label>6</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[LeCun]]></surname>
<given-names><![CDATA[Y.]]></given-names>
</name>
<name>
<surname><![CDATA[Bengio]]></surname>
<given-names><![CDATA[Y.]]></given-names>
</name>
<name>
<surname><![CDATA[Hinton]]></surname>
<given-names><![CDATA[G.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Deep learning]]></article-title>
<source><![CDATA[Nature]]></source>
<year>2015</year>
<volume>521</volume>
</nlm-citation>
</ref>
<ref id="B7">
<label>7</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Ranganathan]]></surname>
<given-names><![CDATA[G.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[A study to find facts behind preprocessing on deep learning algorithms]]></article-title>
<source><![CDATA[Journal of Innovative Image Processing (JIIP)]]></source>
<year>2021</year>
<volume>3</volume>
</nlm-citation>
</ref>
<ref id="B8">
<label>8</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Castiglioni]]></surname>
<given-names><![CDATA[I.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[AI applications to medical images: From machine learning to deep learning]]></article-title>
<source><![CDATA[Physica Medica]]></source>
<year>2021</year>
<volume>83</volume>
</nlm-citation>
</ref>
<ref id="B9">
<label>9</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Das]]></surname>
<given-names><![CDATA[S.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[An artificial intelligence framework and its bias for brain tumor segmentation: A narrative review]]></article-title>
<source><![CDATA[Computers in Biology and Medicine]]></source>
<year>2022</year>
<volume>143</volume>
</nlm-citation>
</ref>
<ref id="B10">
<label>10</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[McBee]]></surname>
<given-names><![CDATA[M. P.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Deep learning in radiology]]></article-title>
<source><![CDATA[Academic radiology]]></source>
<year>2018</year>
<volume>25</volume>
</nlm-citation>
</ref>
<ref id="B11">
<label>11</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Garg]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Computed tomography chest in COVID- 19: When &amp; why?]]></article-title>
<source><![CDATA[Indian J. Med. Res.]]></source>
<year>2021</year>
<volume>153</volume>
</nlm-citation>
</ref>
<ref id="B12">
<label>12</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Hansell]]></surname>
<given-names><![CDATA[D. M.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Fleischner Society: glossary of terms for thoracic imaging]]></article-title>
<source><![CDATA[Radiology]]></source>
<year>2008</year>
<volume>246</volume>
</nlm-citation>
</ref>
<ref id="B13">
<label>13</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Cinar]]></surname>
<given-names><![CDATA[A.]]></given-names>
</name>
<name>
<surname><![CDATA[Yildirim]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Detection of tumors on brain MRI images using the hybrid convolutional neural network architecture]]></article-title>
<source><![CDATA[Med. hypotheses]]></source>
<year>2020</year>
<volume>139</volume>
</nlm-citation>
</ref>
<ref id="B14">
<label>14</label><nlm-citation citation-type="confpro">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Jogin]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
</person-group>
<source><![CDATA[Feature extraction using convolution neural networks (CNN) and deep learning]]></source>
<year>2018</year>
<conf-name><![CDATA[ 2018 3rd IEEE international conference on recent trends in electronics, information &amp; communication technology]]></conf-name>
<conf-loc> </conf-loc>
<page-range>2319-23</page-range></nlm-citation>
</ref>
<ref id="B15">
<label>15</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Zebari]]></surname>
<given-names><![CDATA[R.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[A comprehensive review of dimensionality reduction techniques for feature selection and feature extraction]]></article-title>
<source><![CDATA[Journal of Applied Science and Technology Trends]]></source>
<year>2020</year>
<volume>1</volume>
</nlm-citation>
</ref>
<ref id="B16">
<label>16</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Browne]]></surname>
<given-names><![CDATA[M. W.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Cross-validation methods]]></article-title>
<source><![CDATA[J. Math. Psychol.]]></source>
<year>2000</year>
<volume>4</volume>
</nlm-citation>
</ref>
<ref id="B17">
<label>17</label><nlm-citation citation-type="">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Anguita]]></surname>
<given-names><![CDATA[D.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[The &#8216;K&#8217; in K-fold cross validation, In 20th European Symposium on Artificial Neural Networks]]></article-title>
<source><![CDATA[Computational Intelligence and Machine Learning]]></source>
<year>2012</year>
<page-range>441-6</page-range></nlm-citation>
</ref>
<ref id="B18">
<label>18</label><nlm-citation citation-type="book">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Sen]]></surname>
<given-names><![CDATA[P. C.]]></given-names>
</name>
<name>
<surname><![CDATA[Hajra]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
<name>
<surname><![CDATA[Ghosh]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Supervised classification algorithms in machine learning: A survey and review]]></article-title>
<source><![CDATA[Emerging technology in modelling and graphics]]></source>
<year>2020</year>
<page-range>99-111</page-range><publisher-name><![CDATA[Springer]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B19">
<label>19</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Wong]]></surname>
<given-names><![CDATA[T.-T.]]></given-names>
</name>
<name>
<surname><![CDATA[Yeh]]></surname>
<given-names><![CDATA[P.-Y.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Reliable accuracy estimates from kfold cross validation]]></article-title>
<source><![CDATA[IEEE Trans. Knowl. Data Eng.]]></source>
<year>2019</year>
<volume>32</volume>
</nlm-citation>
</ref>
<ref id="B20">
<label>20</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Visa]]></surname>
<given-names><![CDATA[S.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Confusion matrix-based feature selection]]></article-title>
<source><![CDATA[MAICS]]></source>
<year>2011</year>
<volume>710</volume>
</nlm-citation>
</ref>
<ref id="B21">
<label>21</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Walther]]></surname>
<given-names><![CDATA[B. A.]]></given-names>
</name>
<name>
<surname><![CDATA[Moore]]></surname>
<given-names><![CDATA[J. L.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[The concepts of bias, precision and accuracy, and their use in testing the performance of species richness estimators, with a literature review of estimator performance]]></article-title>
<source><![CDATA[Ecography]]></source>
<year>2005</year>
<volume>28</volume>
</nlm-citation>
</ref>
<ref id="B22">
<label>22</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Schenker]]></surname>
<given-names><![CDATA[B.]]></given-names>
</name>
<name>
<surname><![CDATA[Agarwal]]></surname>
<given-names><![CDATA[M.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Cross-validated structure selection for neural networks]]></article-title>
<source><![CDATA[Comput. Chem. Eng.]]></source>
<year>1996</year>
<volume>20</volume>
</nlm-citation>
</ref>
<ref id="B23">
<label>23</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Hassanat]]></surname>
<given-names><![CDATA[A. B.]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Solving the problem of the K parameter in the KNN classifier using an ensemble learning approach]]></article-title>
<source><![CDATA[(IJCSIS) International Journal of Computer Science and Information Security]]></source>
<year>2014</year>
<volume>12</volume>
</nlm-citation>
</ref>
</ref-list>
</back>
</article>
