<?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>0035-0052</journal-id>
<journal-title><![CDATA[Revista mexicana de pediatría]]></journal-title>
<abbrev-journal-title><![CDATA[Rev. mex. pediatr.]]></abbrev-journal-title>
<issn>0035-0052</issn>
<publisher>
<publisher-name><![CDATA[Sociedad Mexicana de Pediatría A.C.]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0035-00522024000600244</article-id>
<article-id pub-id-type="doi">10.35366/120541</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[El uso de la inteligencia artificial en la oncología pediátrica: avances y perspectivas]]></article-title>
<article-title xml:lang="en"><![CDATA[The use of artificial intelligence in pediatric oncology: advances and perspectives]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Hernández-Zárate]]></surname>
<given-names><![CDATA[Alejandro]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
<xref ref-type="aff" rid="Aaf"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Valdez-Álvarez]]></surname>
<given-names><![CDATA[Anaid]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Universidad La Salle Facultad Mexicana de Medicina ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Mexico</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>12</month>
<year>2024</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>12</month>
<year>2024</year>
</pub-date>
<volume>91</volume>
<numero>6</numero>
<fpage>244</fpage>
<lpage>247</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S0035-00522024000600244&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S0035-00522024000600244&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S0035-00522024000600244&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen: La inteligencia artificial (IA) está revolucionando algunas actividades en la medicina. En particular, en oncología pediátrica existen herramientas que tienen el propósito de mejorar el diagnóstico, tratamiento y pronóstico de los niños con cáncer. Este artículo revisa los avances recientes en la aplicación de la IA en este campo, centrándose en programas específicos y aplicaciones en algunos tipos de neoplasias de pacientes pediátricos. Se analiza cómo se utilizan estos sistemas, en qué enfermedades se aplican y los resultados obtenidos. También se abordan los desafíos éticos y prácticos asociados con su implementación.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract: Artificial intelligence (AI) is revolutionizing some areas of medicine. In pediatric oncology, there are already tools that aim to improve the diagnosis, treatment, and prognosis of children with cancer. This article reviews recent advances in the application of AI in this field, focusing on specific programs and applications in certain types of neoplasia in pediatric patients. It also analyzes how these systems are used, the diseases in which they are applied, and the results obtained, in addition to addressing the ethical and practical challenges associated with their implementation.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[inteligencia artificial]]></kwd>
<kwd lng="es"><![CDATA[oncología]]></kwd>
<kwd lng="es"><![CDATA[diagnóstico]]></kwd>
<kwd lng="es"><![CDATA[tratamiento]]></kwd>
<kwd lng="es"><![CDATA[niños y adolescentes]]></kwd>
<kwd lng="en"><![CDATA[artificial intelligence]]></kwd>
<kwd lng="en"><![CDATA[oncology]]></kwd>
<kwd lng="en"><![CDATA[diagnostics]]></kwd>
<kwd lng="en"><![CDATA[personalized]]></kwd>
<kwd lng="en"><![CDATA[children and adolescents]]></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[Ward]]></surname>
<given-names><![CDATA[E]]></given-names>
</name>
<name>
<surname><![CDATA[DeSantis]]></surname>
<given-names><![CDATA[C]]></given-names>
</name>
<name>
<surname><![CDATA[Robbins]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[Kohler]]></surname>
<given-names><![CDATA[B]]></given-names>
</name>
<name>
<surname><![CDATA[Jemal]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Childhood and adolescent cancer statistics, 2014]]></article-title>
<source><![CDATA[CA Cancer J Clin]]></source>
<year>2014</year>
<volume>64</volume>
<numero>2</numero>
<issue>2</issue>
<page-range>83-103</page-range></nlm-citation>
</ref>
<ref id="B2">
<label>2</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Siegel]]></surname>
<given-names><![CDATA[RL]]></given-names>
</name>
<name>
<surname><![CDATA[Miller]]></surname>
<given-names><![CDATA[KD]]></given-names>
</name>
<name>
<surname><![CDATA[Fuchs]]></surname>
<given-names><![CDATA[HE]]></given-names>
</name>
<name>
<surname><![CDATA[Jemal]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Cancer statistics, 2022]]></article-title>
<source><![CDATA[CA Cancer J Clin]]></source>
<year>2022</year>
<volume>72</volume>
<numero>1</numero>
<issue>1</issue>
<page-range>7-33</page-range></nlm-citation>
</ref>
<ref id="B3">
<label>3</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Gatta]]></surname>
<given-names><![CDATA[G]]></given-names>
</name>
<name>
<surname><![CDATA[Botta]]></surname>
<given-names><![CDATA[L]]></given-names>
</name>
<name>
<surname><![CDATA[Rossi]]></surname>
<given-names><![CDATA[S]]></given-names>
</name>
<name>
<surname><![CDATA[Aareleid]]></surname>
<given-names><![CDATA[T]]></given-names>
</name>
<name>
<surname><![CDATA[Bielska-Lasota]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
<name>
<surname><![CDATA[Clavel]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Childhood cancer survival in Europe 1999-2007: results of EUROCARE-5&#8212;a population-based study]]></article-title>
<source><![CDATA[Lancet Oncol]]></source>
<year>2014</year>
<volume>15</volume>
<numero>1</numero>
<issue>1</issue>
<page-range>35-47</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[Topol]]></surname>
<given-names><![CDATA[EJ]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[High-performance medicine: the convergence of human and artificial intelligence]]></article-title>
<source><![CDATA[Nat Med]]></source>
<year>2019</year>
<volume>25</volume>
<numero>1</numero>
<issue>1</issue>
<page-range>44-56</page-range></nlm-citation>
</ref>
<ref id="B5">
<label>5</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Esteva]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[Robicquet]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[Ramsundar]]></surname>
<given-names><![CDATA[B]]></given-names>
</name>
<name>
<surname><![CDATA[Kuleshov]]></surname>
<given-names><![CDATA[V]]></given-names>
</name>
<name>
<surname><![CDATA[DePristo]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
<name>
<surname><![CDATA[Chou]]></surname>
<given-names><![CDATA[K]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[A guide to deep learning in healthcare]]></article-title>
<source><![CDATA[Nat Med]]></source>
<year>2019</year>
<volume>25</volume>
<numero>1</numero>
<issue>1</issue>
<page-range>24-9</page-range></nlm-citation>
</ref>
<ref id="B6">
<label>6</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Malard]]></surname>
<given-names><![CDATA[F]]></given-names>
</name>
<name>
<surname><![CDATA[Mohty]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Acute lymphoblastic leukaemia]]></article-title>
<source><![CDATA[Lancet]]></source>
<year>2020</year>
<volume>395</volume>
<numero>10230</numero>
<issue>10230</issue>
<page-range>1146-62</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[Zhong]]></surname>
<given-names><![CDATA[P]]></given-names>
</name>
<name>
<surname><![CDATA[Hong]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
<name>
<surname><![CDATA[He]]></surname>
<given-names><![CDATA[H]]></given-names>
</name>
<name>
<surname><![CDATA[Zhang]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
<name>
<surname><![CDATA[Chen]]></surname>
<given-names><![CDATA[Y]]></given-names>
</name>
<name>
<surname><![CDATA[Wang]]></surname>
<given-names><![CDATA[Z]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Diagnosis of acute leukemia by multiparameter flow cytometry with the assistance of artificial intelligence]]></article-title>
<source><![CDATA[Diagnostics (Basel)]]></source>
<year>2022</year>
<volume>12</volume>
<numero>4</numero>
<issue>4</issue>
<page-range>827</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[Ostrom]]></surname>
<given-names><![CDATA[QT]]></given-names>
</name>
<name>
<surname><![CDATA[Price]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
<name>
<surname><![CDATA[Neff]]></surname>
<given-names><![CDATA[C]]></given-names>
</name>
<name>
<surname><![CDATA[Cioffi]]></surname>
<given-names><![CDATA[G]]></given-names>
</name>
<name>
<surname><![CDATA[Waite]]></surname>
<given-names><![CDATA[KA]]></given-names>
</name>
<name>
<surname><![CDATA[Kruchko]]></surname>
<given-names><![CDATA[C]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[CBTRUS statistical report: primary brain and other central nervous system tumors diagnosed in the United States in 2015-2019]]></article-title>
<source><![CDATA[Neuro Oncol]]></source>
<year>2022</year>
<volume>24</volume>
<numero>^s5</numero>
<issue>^s5</issue>
<supplement>5</supplement>
<page-range>v1-v95</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[Kamnitsas]]></surname>
<given-names><![CDATA[K]]></given-names>
</name>
<name>
<surname><![CDATA[Ledig]]></surname>
<given-names><![CDATA[C]]></given-names>
</name>
<name>
<surname><![CDATA[Newcombe]]></surname>
<given-names><![CDATA[VFJ]]></given-names>
</name>
<name>
<surname><![CDATA[Simpson]]></surname>
<given-names><![CDATA[JP]]></given-names>
</name>
<name>
<surname><![CDATA[Kane]]></surname>
<given-names><![CDATA[AD]]></given-names>
</name>
<name>
<surname><![CDATA[Menon]]></surname>
<given-names><![CDATA[DK]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation]]></article-title>
<source><![CDATA[Med Image Anal]]></source>
<year>2017</year>
<volume>36</volume>
<page-range>61-78</page-range></nlm-citation>
</ref>
<ref id="B10">
<label>10</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Maris]]></surname>
<given-names><![CDATA[JM]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Recent advances in neuroblastoma]]></article-title>
<source><![CDATA[N Engl J Med]]></source>
<year>2010</year>
<volume>362</volume>
<numero>23</numero>
<issue>23</issue>
<page-range>2202-11</page-range></nlm-citation>
</ref>
<ref id="B11">
<label>11</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Samim]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[Tytgat]]></surname>
<given-names><![CDATA[GAM]]></given-names>
</name>
<name>
<surname><![CDATA[Bleeker]]></surname>
<given-names><![CDATA[G]]></given-names>
</name>
<name>
<surname><![CDATA[Wenker]]></surname>
<given-names><![CDATA[STM]]></given-names>
</name>
<name>
<surname><![CDATA[Chatalic]]></surname>
<given-names><![CDATA[KLS]]></given-names>
</name>
<name>
<surname><![CDATA[Poot]]></surname>
<given-names><![CDATA[AJ]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Nuclear medicine imaging in neuroblastoma: current status and new developments]]></article-title>
<source><![CDATA[J Pers Med]]></source>
<year>2021</year>
<volume>11</volume>
<numero>4</numero>
<issue>4</issue>
<page-range>270</page-range></nlm-citation>
</ref>
<ref id="B12">
<label>12</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Downing]]></surname>
<given-names><![CDATA[JR]]></given-names>
</name>
<name>
<surname><![CDATA[Wilson]]></surname>
<given-names><![CDATA[RK]]></given-names>
</name>
<name>
<surname><![CDATA[Zhang]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
<name>
<surname><![CDATA[Mardis]]></surname>
<given-names><![CDATA[ER]]></given-names>
</name>
<name>
<surname><![CDATA[Pui]]></surname>
<given-names><![CDATA[CH]]></given-names>
</name>
<name>
<surname><![CDATA[Ding]]></surname>
<given-names><![CDATA[L]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[The Pediatric Cancer Genome Project]]></article-title>
<source><![CDATA[Nat Genet]]></source>
<year>2012</year>
<volume>44</volume>
<numero>6</numero>
<issue>6</issue>
<page-range>619-22</page-range></nlm-citation>
</ref>
<ref id="B13">
<label>13</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Grobner]]></surname>
<given-names><![CDATA[SN]]></given-names>
</name>
<name>
<surname><![CDATA[Worst]]></surname>
<given-names><![CDATA[BC]]></given-names>
</name>
<name>
<surname><![CDATA[Weischenfeldt]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
<name>
<surname><![CDATA[Buchhalter]]></surname>
<given-names><![CDATA[I]]></given-names>
</name>
<name>
<surname><![CDATA[Kleinheinz]]></surname>
<given-names><![CDATA[K]]></given-names>
</name>
<name>
<surname><![CDATA[Rudneva]]></surname>
<given-names><![CDATA[VA]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[The landscape of genomic alterations across childhood cancers]]></article-title>
<source><![CDATA[Nature]]></source>
<year>2018</year>
<volume>555</volume>
<numero>7696</numero>
<issue>7696</issue>
<page-range>321-7</page-range></nlm-citation>
</ref>
<ref id="B14">
<label>14</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Sheng]]></surname>
<given-names><![CDATA[L]]></given-names>
</name>
<name>
<surname><![CDATA[Zhuang]]></surname>
<given-names><![CDATA[L]]></given-names>
</name>
<name>
<surname><![CDATA[Yang]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
<name>
<surname><![CDATA[Zhang]]></surname>
<given-names><![CDATA[D]]></given-names>
</name>
<name>
<surname><![CDATA[Chen]]></surname>
<given-names><![CDATA[Y]]></given-names>
</name>
<name>
<surname><![CDATA[Zhang]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Radiation pneumonia predictive model for radiotherapy in esophageal carcinoma patients]]></article-title>
<source><![CDATA[BMC Cancer]]></source>
<year>2023</year>
<volume>23</volume>
<numero>1</numero>
<issue>1</issue>
<page-range>988</page-range></nlm-citation>
</ref>
<ref id="B15">
<label>15</label><nlm-citation citation-type="book">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Mondal]]></surname>
<given-names><![CDATA[C]]></given-names>
</name>
<name>
<surname><![CDATA[Hasan]]></surname>
<given-names><![CDATA[MK]]></given-names>
</name>
<name>
<surname><![CDATA[Jawad]]></surname>
<given-names><![CDATA[MT]]></given-names>
</name>
<name>
<surname><![CDATA[Dutta]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[Islam]]></surname>
<given-names><![CDATA[MR]]></given-names>
</name>
<name>
<surname><![CDATA[Awal]]></surname>
<given-names><![CDATA[MA]]></given-names>
</name>
</person-group>
<source><![CDATA[Acute Lymphoblastic Leukemia detection from microscopic images using weighted ensemble of Convolutional Neural Networks]]></source>
<year>2021</year>
<publisher-name><![CDATA[Preprints]]></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[Sarhan]]></surname>
<given-names><![CDATA[AM]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Brain tumor classification in magnetic resonance images using deep learning and wavelet transform]]></article-title>
<source><![CDATA[J Biomed Sci Eng]]></source>
<year>2020</year>
<volume>13</volume>
<numero>6</numero>
<issue>6</issue>
<page-range>102-12</page-range></nlm-citation>
</ref>
<ref id="B17">
<label>17</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Char]]></surname>
<given-names><![CDATA[DS]]></given-names>
</name>
<name>
<surname><![CDATA[Shah]]></surname>
<given-names><![CDATA[NH]]></given-names>
</name>
<name>
<surname><![CDATA[Magnus]]></surname>
<given-names><![CDATA[D]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Implementing machine learning in health care-addressing ethical challenges]]></article-title>
<source><![CDATA[N Engl J Med]]></source>
<year>2018</year>
<volume>378</volume>
<numero>11</numero>
<issue>11</issue>
<page-range>981-3</page-range></nlm-citation>
</ref>
<ref id="B18">
<label>18</label><nlm-citation citation-type="journal">
<collab>European Parliament</collab>
<article-title xml:lang=""><![CDATA[Regulation (EU) 2016/679 (General Data Protection Regulation)]]></article-title>
<source><![CDATA[Off J Eur Union]]></source>
<year>2016</year>
<volume>L119</volume>
<page-range>1-88</page-range></nlm-citation>
</ref>
<ref id="B19">
<label>19</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Obermeyer]]></surname>
<given-names><![CDATA[Z]]></given-names>
</name>
<name>
<surname><![CDATA[Powers]]></surname>
<given-names><![CDATA[B]]></given-names>
</name>
<name>
<surname><![CDATA[Vogeli]]></surname>
<given-names><![CDATA[C]]></given-names>
</name>
<name>
<surname><![CDATA[Mullainathan]]></surname>
<given-names><![CDATA[S]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Dissecting racial bias in an algorithm used to manage the health of populations]]></article-title>
<source><![CDATA[Science]]></source>
<year>2019</year>
<volume>366</volume>
<numero>6464</numero>
<issue>6464</issue>
<page-range>447-53</page-range></nlm-citation>
</ref>
<ref id="B20">
<label>20</label><nlm-citation citation-type="book">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Beauchamp]]></surname>
<given-names><![CDATA[TL]]></given-names>
</name>
<name>
<surname><![CDATA[Childress]]></surname>
<given-names><![CDATA[JF]]></given-names>
</name>
</person-group>
<source><![CDATA[Principles of biomedical ethics]]></source>
<year>2019</year>
<edition>8th</edition>
<publisher-loc><![CDATA[New York, NY ]]></publisher-loc>
<publisher-name><![CDATA[Oxford University Press]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B21">
<label>21</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Holzinger]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[Langs]]></surname>
<given-names><![CDATA[G]]></given-names>
</name>
<name>
<surname><![CDATA[Denk]]></surname>
<given-names><![CDATA[H]]></given-names>
</name>
<name>
<surname><![CDATA[Zatloukal]]></surname>
<given-names><![CDATA[K]]></given-names>
</name>
<name>
<surname><![CDATA[Müller]]></surname>
<given-names><![CDATA[H]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Causability and explainability of artificial intelligence in medicine]]></article-title>
<source><![CDATA[Wiley Interdiscip Rev Data Min Knowl Discov]]></source>
<year>2019</year>
<volume>9</volume>
<numero>4</numero>
<issue>4</issue>
</nlm-citation>
</ref>
<ref id="B22">
<label>22</label><nlm-citation citation-type="">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Samek]]></surname>
<given-names><![CDATA[W]]></given-names>
</name>
<name>
<surname><![CDATA[Wiegand]]></surname>
<given-names><![CDATA[T]]></given-names>
</name>
<name>
<surname><![CDATA[Müller]]></surname>
<given-names><![CDATA[K-R]]></given-names>
</name>
</person-group>
<source><![CDATA[Explainable artificial intelligence: Understanding, visualizing and interpreting deep learning models]]></source>
<year>2017</year>
</nlm-citation>
</ref>
<ref id="B23">
<label>23</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Davenport]]></surname>
<given-names><![CDATA[T]]></given-names>
</name>
<name>
<surname><![CDATA[Kalakota]]></surname>
<given-names><![CDATA[R]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[The potential for artificial intelligence in healthcare]]></article-title>
<source><![CDATA[Future Healthc J]]></source>
<year>2019</year>
<volume>6</volume>
<numero>2</numero>
<issue>2</issue>
<page-range>94-8</page-range></nlm-citation>
</ref>
<ref id="B24">
<label>24</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Rieke]]></surname>
<given-names><![CDATA[N]]></given-names>
</name>
<name>
<surname><![CDATA[Hancox]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
<name>
<surname><![CDATA[Li]]></surname>
<given-names><![CDATA[W]]></given-names>
</name>
<name>
<surname><![CDATA[Milletari]]></surname>
<given-names><![CDATA[F]]></given-names>
</name>
<name>
<surname><![CDATA[Roth]]></surname>
<given-names><![CDATA[HR]]></given-names>
</name>
<name>
<surname><![CDATA[Albarqouni]]></surname>
<given-names><![CDATA[S]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[The future of digital health with federated learning]]></article-title>
<source><![CDATA[NPJ Digit Med]]></source>
<year>2020</year>
<volume>3</volume>
<page-range>119</page-range></nlm-citation>
</ref>
<ref id="B25">
<label>25</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Kersey]]></surname>
<given-names><![CDATA[JH]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Fifty years of studies of the biology and therapy of childhood leukemia]]></article-title>
<source><![CDATA[Blood]]></source>
<year>1997</year>
<volume>90</volume>
<numero>11</numero>
<issue>11</issue>
<page-range>4243-51</page-range></nlm-citation>
</ref>
<ref id="B26">
<label>26</label><nlm-citation citation-type="book">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Khosla]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[Cao]]></surname>
<given-names><![CDATA[Y]]></given-names>
</name>
<name>
<surname><![CDATA[Lin]]></surname>
<given-names><![CDATA[CC-Y]]></given-names>
</name>
<name>
<surname><![CDATA[Chiu]]></surname>
<given-names><![CDATA[H-K]]></given-names>
</name>
<name>
<surname><![CDATA[Hu]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
<name>
<surname><![CDATA[Lee]]></surname>
<given-names><![CDATA[H]]></given-names>
</name>
</person-group>
<source><![CDATA[An integrated machine learning approach to stroke prediction. En: Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining]]></source>
<year>2010</year>
<publisher-loc><![CDATA[New York, NY, USA ]]></publisher-loc>
<publisher-name><![CDATA[ACM]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B27">
<label>27</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Jiao]]></surname>
<given-names><![CDATA[W]]></given-names>
</name>
<name>
<surname><![CDATA[Atwal]]></surname>
<given-names><![CDATA[G]]></given-names>
</name>
<name>
<surname><![CDATA[Polak]]></surname>
<given-names><![CDATA[P]]></given-names>
</name>
<name>
<surname><![CDATA[Karlic]]></surname>
<given-names><![CDATA[R]]></given-names>
</name>
<name>
<surname><![CDATA[Cibulskis]]></surname>
<given-names><![CDATA[K]]></given-names>
</name>
<name>
<surname><![CDATA[Sivachenko]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[A deep learning system accurately classifies primary and metastatic cancers using passenger mutation patterns]]></article-title>
<source><![CDATA[Nat Commun]]></source>
<year>2020</year>
<volume>11</volume>
<numero>1</numero>
<issue>1</issue>
<page-range>728</page-range></nlm-citation>
</ref>
<ref id="B28">
<label>28</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Mesko]]></surname>
<given-names><![CDATA[B]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[The role of artificial intelligence in precision medicine]]></article-title>
<source><![CDATA[Expert Rev Precis Med Drug Dev]]></source>
<year>2017</year>
<volume>2</volume>
<numero>5</numero>
<issue>5</issue>
<page-range>239-41</page-range></nlm-citation>
</ref>
</ref-list>
</back>
</article>
