<?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>1684-1859</journal-id>
<journal-title><![CDATA[Revista Cubana de Informática Médica]]></journal-title>
<abbrev-journal-title><![CDATA[RCIM]]></abbrev-journal-title>
<issn>1684-1859</issn>
<publisher>
<publisher-name><![CDATA[Universidad de Ciencias Médicas de La Habana]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S1684-18592023000100013</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Impacto de la Inteligencia Artificial en la Radiología]]></article-title>
<article-title xml:lang="en"><![CDATA[Impact of Artificial Intelligence in Radiology]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Iglesias López]]></surname>
<given-names><![CDATA[Dannier]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad de Ciencias Médicas Camagüey Facultad Tecnológica ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Cuba</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>
<volume>15</volume>
<numero>1</numero>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://scielo.sld.cu/scielo.php?script=sci_arttext&amp;pid=S1684-18592023000100013&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.sld.cu/scielo.php?script=sci_abstract&amp;pid=S1684-18592023000100013&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.sld.cu/scielo.php?script=sci_pdf&amp;pid=S1684-18592023000100013&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[RESUMEN  Introducción:  El creciente desarrollo computacional ocurrido en los últimos años, así como el acceso a gran número de datos (Big Data) ha posibilitado la explotación de los recursos informáticos para el desarrollo de algoritmos que aumentan la calidad y alcance de la inteligencia artificial (IA), la cual está tomando un rol central en la radiología.  Objetivo:  Analizar el impacto de la Inteligencia Artificial en la Radiología y la necesidad de implementación en los servicios de imagenología.  Método:  Se emplearon 23 referencias bibliográficas en inglés y español, la mayoría extraídas de PubMed, SciELO y ScienceDirect usando los descriptores &#8220;Inteligencia Artificial&#8221;, &#8220;Radiología&#8221; y &#8220;Aprendizaje automático&#8221; en idioma español y &#8220;Artificial Intelligence&#8221;, &#8220;Radiology&#8221; y &#8220;Machine Learning&#8221; para el inglés.  Desarrollo:  No existe área de la Radiología en la cual no se haya implementado la inteligencia artificial, con el fin de mejorar y desarrollar programas que le faciliten al radiólogo y al técnico, la obtención y diagnóstico de imágenes. Cuba también está inmersa en este proceso; se están dando los primeros pasos por el desarrollo de estas tecnologías.  Conclusiones:  La investigación, optimización de flujo de trabajo, radiómica, predicción y clasificación de imágenes son beneficios que nos aporta la IA; lograr un aumento en la calidad de estos procesos solo es posible a través de la alianza entre las ciencias médicas e informáticas.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[ABSTRACT  Introduction:  The growing computational development that has occurred in recent years, as well as the access to a large number of data (Big Data), has made the exploitation of computing resources possible to develop algorithms that increase the quality and scope of artificial intelligence (AI), which is taking a central role in radiology.  Objective:  To analyze the impact of artificial intelligence in radiology and the need for its implementation in imaging services.  Method:  A total of 23 bibliographical references in English and Spanish, most of them obtained from PubMed, SciELO and ScienceDirect databases, were analyzed using descriptors such as &#8220;inteligencia artificial&#8221;, &#8220;radiología&#8221; and &#8220;aprendizaje automático&#8221; for the Spanish language and "artificial intelligence", &#8220;radiology&#8221; and &#8220;machine learning&#8221; for the English language.  Results:  There is no area of &#8203;&#8203;Radiology in which artificial intelligence has not been implemented in order to improve and develop programs that make it easier for the radiologist and the technician to obtain and diagnose images. Cuba is also immersed in this process; the first steps are being taken towards the development of these technologies.  Conclusions:  Research, workflow optimization, radiomics, prediction and classification of images are benefits that AI brings us; achieving an increase in the quality of these processes is only possible through the alliance between medical and computer sciences.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[inteligencia artificial]]></kwd>
<kwd lng="es"><![CDATA[radiología]]></kwd>
<kwd lng="es"><![CDATA[aprendizaje automático]]></kwd>
<kwd lng="en"><![CDATA[artificial intelligence]]></kwd>
<kwd lng="en"><![CDATA[radiology]]></kwd>
<kwd lng="en"><![CDATA[automatic learning]]></kwd>
</kwd-group>
</article-meta>
</front><back>
<ref-list>
<ref id="B1">
<label>1</label><nlm-citation citation-type="book">
<source><![CDATA[IBM Cloud Education. What is artificial intelligence (AI)]]></source>
<year>c202</year>
<month>2</month>
<publisher-loc><![CDATA[New York ]]></publisher-loc>
<publisher-name><![CDATA[IBM]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B2">
<label>2</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Pérez del Barrio]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[Menéndez Fernández-Miranda]]></surname>
<given-names><![CDATA[P]]></given-names>
</name>
<name>
<surname><![CDATA[Sanz Bellón]]></surname>
<given-names><![CDATA[P]]></given-names>
</name>
<name>
<surname><![CDATA[Lloret Iglesias]]></surname>
<given-names><![CDATA[L]]></given-names>
</name>
<name>
<surname><![CDATA[Rodríguez González]]></surname>
<given-names><![CDATA[D]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Inteligencia artificial en Radiología: introducción a los conceptos más importantes]]></article-title>
<source><![CDATA[Radiol]]></source>
<year>2022</year>
<volume>64</volume>
<numero>3</numero>
<issue>3</issue>
<page-range>228-36</page-range></nlm-citation>
</ref>
<ref id="B3">
<label>3</label><nlm-citation citation-type="book">
<collab>SAS</collab>
<source><![CDATA[Machine Learning: Qué es y por qué es importante]]></source>
<year>2022</year>
<publisher-loc><![CDATA[North Carolina ]]></publisher-loc>
<publisher-name><![CDATA[SAS Institute Inc]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B4">
<label>4</label><nlm-citation citation-type="book">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Kelleher]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
</person-group>
<source><![CDATA[Deep learning]]></source>
<year>2019</year>
<publisher-loc><![CDATA[Massachusetts ]]></publisher-loc>
<publisher-name><![CDATA[The MIT Press]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B5">
<label>5</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Hardy]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
<name>
<surname><![CDATA[Harvey]]></surname>
<given-names><![CDATA[H]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Artificial intelligence in diagnostic imaging: impact on the radiography profession]]></article-title>
<source><![CDATA[Br J Radiol]]></source>
<year>2020</year>
<volume>93</volume>
<numero>1108</numero>
<issue>1108</issue>
</nlm-citation>
</ref>
<ref id="B6">
<label>6</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Takahashi]]></surname>
<given-names><![CDATA[R]]></given-names>
</name>
<name>
<surname><![CDATA[Kajikawa]]></surname>
<given-names><![CDATA[Y]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Computer-aided diagnosis: A survey with bibliometric analysis]]></article-title>
<source><![CDATA[Int J Med Inf]]></source>
<year>2017</year>
<volume>101</volume>
<page-range>58-67</page-range></nlm-citation>
</ref>
<ref id="B7">
<label>7</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Shi]]></surname>
<given-names><![CDATA[F]]></given-names>
</name>
<name>
<surname><![CDATA[Wang]]></surname>
<given-names><![CDATA[F]]></given-names>
</name>
<name>
<surname><![CDATA[Shi]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
<name>
<surname><![CDATA[Wu]]></surname>
<given-names><![CDATA[Z]]></given-names>
</name>
<name>
<surname><![CDATA[Wang]]></surname>
<given-names><![CDATA[Q]]></given-names>
</name>
<name>
<surname><![CDATA[Tang]]></surname>
<given-names><![CDATA[Z]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Review of Artificial Intelligence Techniques in Imaging Data Acquisition, Segmentation, and Diagnosis for COVID-19]]></article-title>
<source><![CDATA[IEEE Rev Biomed Eng]]></source>
<year>2021</year>
<volume>14</volume>
<page-range>4-15</page-range></nlm-citation>
</ref>
<ref id="B8">
<label>8</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Hong]]></surname>
<given-names><![CDATA[Y]]></given-names>
</name>
<name>
<surname><![CDATA[Fleming]]></surname>
<given-names><![CDATA[L]]></given-names>
</name>
<name>
<surname><![CDATA[Hengyuan]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
<name>
<surname><![CDATA[Ziqi]]></surname>
<given-names><![CDATA[Z]]></given-names>
</name>
<name>
<surname><![CDATA[Stefan]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
<name>
<surname><![CDATA[Jinxin]]></surname>
<given-names><![CDATA[L]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Using artificial intelligence to assist radiologists in distinguishing COVID-19 from other pulmonary infections]]></article-title>
<source><![CDATA[J X-Ray Sci Technol]]></source>
<year>2021</year>
<volume>29</volume>
<numero>1</numero>
<issue>1</issue>
<page-range>1-17</page-range></nlm-citation>
</ref>
<ref id="B9">
<label>9</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Jin Choi]]></surname>
<given-names><![CDATA[K]]></given-names>
</name>
<name>
<surname><![CDATA[Keon Jang]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
<name>
<surname><![CDATA[Soo Lee]]></surname>
<given-names><![CDATA[S]]></given-names>
</name>
<name>
<surname><![CDATA[Sub Sung]]></surname>
<given-names><![CDATA[Y]]></given-names>
</name>
<name>
<surname><![CDATA[Hyun Shim]]></surname>
<given-names><![CDATA[W]]></given-names>
</name>
<name>
<surname><![CDATA[Sung Kim]]></surname>
<given-names><![CDATA[H]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Development and Validation of a Deep Learning System for Staging Liver Fibrosis by Using Contrast Agent-enhanced CT Images in the Liver]]></article-title>
<source><![CDATA[Radiol]]></source>
<year>2018</year>
<volume>289</volume>
<numero>3</numero>
<issue>3</issue>
</nlm-citation>
</ref>
<ref id="B10">
<label>10</label><nlm-citation citation-type="book">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Beunza Nuin]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
<name>
<surname><![CDATA[Puertas Sanz]]></surname>
<given-names><![CDATA[E]]></given-names>
</name>
<name>
<surname><![CDATA[Condés Moreno]]></surname>
<given-names><![CDATA[E]]></given-names>
</name>
</person-group>
<source><![CDATA[Manual práctico de inteligencia artificial en entornos sanitarios]]></source>
<year>2020</year>
<publisher-loc><![CDATA[Barcelona ]]></publisher-loc>
<publisher-name><![CDATA[Elsevier]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B11">
<label>11</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Elton]]></surname>
<given-names><![CDATA[D]]></given-names>
</name>
<name>
<surname><![CDATA[Yang]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[Kleiner]]></surname>
<given-names><![CDATA[D]]></given-names>
</name>
<name>
<surname><![CDATA[Lubner]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
<name>
<surname><![CDATA[Pickhardt]]></surname>
<given-names><![CDATA[P]]></given-names>
</name>
<name>
<surname><![CDATA[Veranos]]></surname>
<given-names><![CDATA[R]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Fully Automated and Explainable Liver Segmental Volume Ratio and Spleen Segmentation at CT for Diagnosing Cirrhosis]]></article-title>
<source><![CDATA[Radiol Artif Intell]]></source>
<year>2022</year>
<volume>4</volume>
<numero>5</numero>
<issue>5</issue>
</nlm-citation>
</ref>
<ref id="B12">
<label>12</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Nguyen]]></surname>
<given-names><![CDATA[T]]></given-names>
</name>
<name>
<surname><![CDATA[Pérez]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[Graffy]]></surname>
<given-names><![CDATA[P]]></given-names>
</name>
<name>
<surname><![CDATA[Jang]]></surname>
<given-names><![CDATA[S]]></given-names>
</name>
<name>
<surname><![CDATA[Veranos]]></surname>
<given-names><![CDATA[R]]></given-names>
</name>
<name>
<surname><![CDATA[Garrett]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Improved CT-based Osteoporosis Assessment with a Fully Automated Deep Learning Tool]]></article-title>
<source><![CDATA[Radiol Artif Intell]]></source>
<year>2022</year>
<volume>4</volume>
<numero>5</numero>
<issue>5</issue>
</nlm-citation>
</ref>
<ref id="B13">
<label>13</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Khosravi]]></surname>
<given-names><![CDATA[B]]></given-names>
</name>
<name>
<surname><![CDATA[Rouzrokh]]></surname>
<given-names><![CDATA[P]]></given-names>
</name>
<name>
<surname><![CDATA[Maradit Kremers]]></surname>
<given-names><![CDATA[H]]></given-names>
</name>
<name>
<surname><![CDATA[Larson]]></surname>
<given-names><![CDATA[D]]></given-names>
</name>
<name>
<surname><![CDATA[Johnson]]></surname>
<given-names><![CDATA[Q]]></given-names>
</name>
<name>
<surname><![CDATA[Faghani]]></surname>
<given-names><![CDATA[S]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Patient-specific Hip Arthroplasty Dislocation Risk Calculator: An Explainable Multimodal Machine Learning-based Approach]]></article-title>
<source><![CDATA[Radiol Artif Intell]]></source>
<year>2022</year>
<volume>4</volume>
<numero>6</numero>
<issue>6</issue>
</nlm-citation>
</ref>
<ref id="B14">
<label>14</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Raschio]]></surname>
<given-names><![CDATA[E]]></given-names>
</name>
<name>
<surname><![CDATA[Contreras]]></surname>
<given-names><![CDATA[C]]></given-names>
</name>
<name>
<surname><![CDATA[Allende]]></surname>
<given-names><![CDATA[F]]></given-names>
</name>
<name>
<surname><![CDATA[Maturana]]></surname>
<given-names><![CDATA[P]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Inteligencia artificial: Desarrollo de algoritmos de clasificación y segmentación en radiografía de tórax]]></article-title>
<source><![CDATA[Rev Chil Radiol]]></source>
<year>2021</year>
<volume>27</volume>
<numero>1</numero>
<issue>1</issue>
</nlm-citation>
</ref>
<ref id="B15">
<label>15</label><nlm-citation citation-type="book">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Francois Paul]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
<name>
<surname><![CDATA[Rohnean]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
</person-group>
<source><![CDATA[Eight clinical cases demonstrating the diagnostic value of ViosWorks 4D powered by Arterys]]></source>
<year>2018</year>
<publisher-loc><![CDATA[Paris ]]></publisher-loc>
<publisher-name><![CDATA[General Electric Company]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B16">
<label>16</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Seetharam]]></surname>
<given-names><![CDATA[K]]></given-names>
</name>
<name>
<surname><![CDATA[Lerakis]]></surname>
<given-names><![CDATA[S]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Cardiac magnetic resonance imaging: the future is bright]]></article-title>
<source><![CDATA[peer review: 2 approved]]></source>
<year>2019</year>
<volume>8</volume>
</nlm-citation>
</ref>
<ref id="B17">
<label>17</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Cirio]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
<name>
<surname><![CDATA[Ciardi]]></surname>
<given-names><![CDATA[C]]></given-names>
</name>
<name>
<surname><![CDATA[Buezasa]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
<name>
<surname><![CDATA[Dilucab]]></surname>
<given-names><![CDATA[P]]></given-names>
</name>
<name>
<surname><![CDATA[Caballeroa]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
<name>
<surname><![CDATA[Lopeza]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Implementación de la inteligencia artificial en el tratamiento hiperagudo de reperfusión arterial en un centro integral de ataque cerebrovascular]]></article-title>
<source><![CDATA[Neurol Arg]]></source>
<year>2021</year>
<volume>13</volume>
<numero>4</numero>
<issue>4</issue>
<page-range>212-20</page-range></nlm-citation>
</ref>
<ref id="B18">
<label>18</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Zhuo]]></surname>
<given-names><![CDATA[Z]]></given-names>
</name>
<name>
<surname><![CDATA[Zhang]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
<name>
<surname><![CDATA[Duan]]></surname>
<given-names><![CDATA[Y]]></given-names>
</name>
<name>
<surname><![CDATA[Qu]]></surname>
<given-names><![CDATA[L]]></given-names>
</name>
<name>
<surname><![CDATA[Ye]]></surname>
<given-names><![CDATA[C]]></given-names>
</name>
<name>
<surname><![CDATA[Liu]]></surname>
<given-names><![CDATA[Y]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Automated Classification of Intramedullary Spinal Cord Tumors and Inflammatory Demyelinating Lesions Using Deep Learning]]></article-title>
<source><![CDATA[Radiol Artif Intell]]></source>
<year>2022</year>
<volume>4</volume>
<numero>6</numero>
<issue>6</issue>
</nlm-citation>
</ref>
<ref id="B19">
<label>19</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Zaharchuk]]></surname>
<given-names><![CDATA[G]]></given-names>
</name>
<name>
<surname><![CDATA[Gong]]></surname>
<given-names><![CDATA[E]]></given-names>
</name>
<name>
<surname><![CDATA[Wintermark]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
<name>
<surname><![CDATA[Rubin]]></surname>
<given-names><![CDATA[D]]></given-names>
</name>
<name>
<surname><![CDATA[Langlotz]]></surname>
<given-names><![CDATA[C]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Deep Learning in Neuroradiology]]></article-title>
<source><![CDATA[Am J Neuroradiol]]></source>
<year>2018</year>
<volume>39</volume>
<numero>10</numero>
<issue>10</issue>
<page-range>1776-84</page-range></nlm-citation>
</ref>
<ref id="B20">
<label>20</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Shur]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
<name>
<surname><![CDATA[Doran]]></surname>
<given-names><![CDATA[S]]></given-names>
</name>
<name>
<surname><![CDATA[Kumar]]></surname>
<given-names><![CDATA[S]]></given-names>
</name>
<name>
<surname><![CDATA[Downey]]></surname>
<given-names><![CDATA[K]]></given-names>
</name>
<name>
<surname><![CDATA[O'Connor]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
<name>
<surname><![CDATA[Papanikolaou]]></surname>
<given-names><![CDATA[N]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Radiomics in Oncology: A Practical Guide]]></article-title>
<source><![CDATA[Radiophys]]></source>
<year>2021</year>
<volume>41</volume>
<numero>6</numero>
<issue>6</issue>
</nlm-citation>
</ref>
<ref id="B21">
<label>21</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Malik]]></surname>
<given-names><![CDATA[N]]></given-names>
</name>
<name>
<surname><![CDATA[Geraghty]]></surname>
<given-names><![CDATA[B]]></given-names>
</name>
<name>
<surname><![CDATA[Dasgupta]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[Jabehdar Maralani]]></surname>
<given-names><![CDATA[P]]></given-names>
</name>
<name>
<surname><![CDATA[Sandhu]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
<name>
<surname><![CDATA[Lin Tseng]]></surname>
<given-names><![CDATA[C]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[MRI radiomics to differentiate between low grade glioma and glioblastoma peritumoral region]]></article-title>
<source><![CDATA[J Neuro Oncol]]></source>
<year>2021</year>
<volume>155</volume>
<page-range>181-91</page-range></nlm-citation>
</ref>
<ref id="B22">
<label>22</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Mulet De los Reyes]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[C]]></surname>
<given-names><![CDATA[Suárez]]></given-names>
</name>
<name>
<surname><![CDATA[Noriega Alemán]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Herramienta para la detección automática de nódulos pulmonares solitarios en series de imágenes de tomografía computarizada multicorte]]></article-title>
<source><![CDATA[Rev Cub Investig Biomed]]></source>
<year>2020</year>
<volume>39</volume>
<numero>2</numero>
<issue>2</issue>
</nlm-citation>
</ref>
<ref id="B23">
<label>23</label><nlm-citation citation-type="book">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Larrondo Pons]]></surname>
<given-names><![CDATA[E]]></given-names>
</name>
</person-group>
<source><![CDATA[Imagis 2.0, un sistema de información PACS basado en DICOM]]></source>
<year>c202</year>
<month>1</month>
<publisher-loc><![CDATA[Santiago de Cuba ]]></publisher-loc>
<publisher-name><![CDATA[Centro de Biofísica Médica]]></publisher-name>
</nlm-citation>
</ref>
</ref-list>
</back>
</article>
