<?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>0120-4157</journal-id>
<journal-title><![CDATA[Biomédica]]></journal-title>
<abbrev-journal-title><![CDATA[Biomed.]]></abbrev-journal-title>
<issn>0120-4157</issn>
<publisher>
<publisher-name><![CDATA[Instituto Nacional de Salud]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0120-41572025000600071</article-id>
<article-id pub-id-type="doi">10.7705/biomedica.7937</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Datos sintéticos de un modelo de datos común para las aplicaciones de inteligencia artificial en salud materna: reporte de experiencia en el contexto colombiano]]></article-title>
<article-title xml:lang="en"><![CDATA[Synthetic data within a common data model for artificial intelligence applications in maternal health: experience report in the Colombian context]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Torres-Silva]]></surname>
<given-names><![CDATA[Ever Augusto]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Gaviria-Jiménez]]></surname>
<given-names><![CDATA[Juan José]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Guevara-Zambrano]]></surname>
<given-names><![CDATA[Ana María]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Herrera-Almanza]]></surname>
<given-names><![CDATA[Laura]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Flórez-Arango]]></surname>
<given-names><![CDATA[José]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Netux S.A.S. Futuro ]]></institution>
<addr-line><![CDATA[Medellín ]]></addr-line>
<country>Colombia</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,Universidad de Antioquia Facultad de Medicina ]]></institution>
<addr-line><![CDATA[Medellín ]]></addr-line>
<country>Colombia</country>
</aff>
<aff id="Af3">
<institution><![CDATA[,Hospital Pablo Tobón Uribe Ginecología y Obstetricia ]]></institution>
<addr-line><![CDATA[Medellín ]]></addr-line>
<country>Colombia</country>
</aff>
<aff id="Af4">
<institution><![CDATA[,Clínica Universitaria Bolivariana Investigación ]]></institution>
<addr-line><![CDATA[Medellín ]]></addr-line>
<country>Colombia</country>
</aff>
<aff id="Af5">
<institution><![CDATA[,Weill Cornell Medicine Population Health Sciences ]]></institution>
<addr-line><![CDATA[New York ]]></addr-line>
<country>USA</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>12</month>
<year>2025</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>12</month>
<year>2025</year>
</pub-date>
<volume>45</volume>
<fpage>71</fpage>
<lpage>83</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_arttext&amp;pid=S0120-41572025000600071&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_abstract&amp;pid=S0120-41572025000600071&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.co/scielo.php?script=sci_pdf&amp;pid=S0120-41572025000600071&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen  Introducción.  Los datos sintéticos en salud son una alternativa para generar registros clínicos que permitan obtener historias clínicas similares a las reales y que puedan ser usadas en diferentes situaciones clínicas.  Objetivo.  Formular un modelo basado en la generación de datos sintéticos para el proceso de atención de la gestación en Colombia y adaptarlo al modelo de datos común de la Observational Medical Outcomes Partnership (OMOP) para facilitar su integración en aplicaciones de inteligencia artificial en salud materna.  Materiales y métodos.  Se realizó un estudio de caso de formulación de datos completamente sintéticos, en el cual se incluyeron algunos de los desenlaces y condiciones más frecuentes de la gestación durante un proceso típico de atención de mujeres gestantes en Colombia. La propuesta se complementó con la generación de un modelo común de datos para facilitar la integración de los datos en futuras aplicaciones de inteligencia artificial o de sistemas complementarios que se beneficien de un lenguaje común, independiente del sistema o de la forma de clasificación.  Resultados.  Se logró la formulación de un modelo para la generación sintética de datos clínicos en el entorno clínico de atención de la gestación hasta el periodo perinatal. El modelo incluyó las condiciones clínicas y los desenlaces más frecuentes, los cuales se diagramaron en la herramienta Synthea&#8482; con sus respectivas probabilidades clínicas de ocurrencia, según la literatura reportada o la práctica habitual de los especialistas en obstetricia en Colombia.  Conclusiones.  Este estudio demuestra que la generación de datos sintéticos aplicados al proceso de atención de la gestación en Colombia es factible y constituye un aporte pionero en la región.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract  Introduction.  Synthetic data in healthcare is an alternative for generating clinical records that resemble those registered in real clinical scenarios. The benefits of synthetic data are: greater volume of data, the possibility of representing specific patient populations, protection of real-data privacy, and improved data-sharing among different actors.  Objective.  To formulate a synthetic data generation model for the gestational care process in Colombia and adapt it to the Observational Medical Outcomes Partnership (OMOP) common data model to facilitate its integration into artificial intelligence applications in maternal health.  Materials and methods.  We conducted a case study of fully synthetic data formulation that included some of the most frequent outcomes and conditions during gestation based on a typical care process for pregnant women in Colombia. This approach was complemented by the generation of a common data model to facilitate data integration in future artificial intelligence applications or complementary systems that benefit from a standardized language, regardless of the system or form of classification.  Results.  We formulated a model for the synthetic generation of clinical data -applicable to real clinical settings- that spans the entire gestational care until the perinatal period. The model included the most frequent clinical conditions and outcomes, which were diagrammed in the Synthea&#8482; tool with their corresponding clinical probabilities of occurrence based on the reported literature or the usual practice of obstetric specialists in Colombia.  Conclusions.  This study demonstrates that the generation of synthetic data applied to the gestational care process in Colombia was feasible and represents a pioneering contribution in the region.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[registros electrónicos de salud]]></kwd>
<kwd lng="es"><![CDATA[salud materna]]></kwd>
<kwd lng="es"><![CDATA[embarazo]]></kwd>
<kwd lng="es"><![CDATA[inteligencia artificial.]]></kwd>
<kwd lng="en"><![CDATA[Electronic health records]]></kwd>
<kwd lng="en"><![CDATA[maternal health]]></kwd>
<kwd lng="en"><![CDATA[pregnancy]]></kwd>
<kwd lng="en"><![CDATA[artificial intelligence.]]></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[Bernstam]]></surname>
<given-names><![CDATA[EV]]></given-names>
</name>
<name>
<surname><![CDATA[Smith]]></surname>
<given-names><![CDATA[JW]]></given-names>
</name>
<name>
<surname><![CDATA[Johnson]]></surname>
<given-names><![CDATA[TR]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[What is biomedical informatics?]]></article-title>
<source><![CDATA[J Biomed Inform]]></source>
<year>2010</year>
<volume>43</volume>
<page-range>104-10</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[Katalinic]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
<name>
<surname><![CDATA[Schenk]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
<name>
<surname><![CDATA[Franke]]></surname>
<given-names><![CDATA[S]]></given-names>
</name>
<name>
<surname><![CDATA[Katalinic]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[Neumuth]]></surname>
<given-names><![CDATA[T]]></given-names>
</name>
<name>
<surname><![CDATA[Dietz]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Generation of a realistic synthetic laryngeal cancer cohort for AI applications]]></article-title>
<source><![CDATA[Cancer]]></source>
<year>2024</year>
<volume>16</volume>
<page-range>639</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[Weldon]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
<name>
<surname><![CDATA[Ward]]></surname>
<given-names><![CDATA[T]]></given-names>
</name>
<name>
<surname><![CDATA[Brophy]]></surname>
<given-names><![CDATA[E]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Generation of synthetic electronic health records using a federated GAN]]></article-title>
<source><![CDATA[arXiv]]></source>
<year>2021</year>
</nlm-citation>
</ref>
<ref id="B4">
<label>4.</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Callahan]]></surname>
<given-names><![CDATA[TJ]]></given-names>
</name>
<name>
<surname><![CDATA[Al]]></surname>
<given-names><![CDATA[Stefanksi]]></given-names>
</name>
<name>
<surname><![CDATA[Dm]]></surname>
<given-names><![CDATA[Ostendorf]]></given-names>
</name>
<name>
<surname><![CDATA[Jm]]></surname>
<given-names><![CDATA[Wyrwa]]></given-names>
</name>
<name>
<surname><![CDATA[Sjd]]></surname>
<given-names><![CDATA[Davies]]></given-names>
</name>
<name>
<surname><![CDATA[Hripcsak]]></surname>
<given-names><![CDATA[G]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Characterizing patient representations for computational phenotyping]]></article-title>
<source><![CDATA[AMIA Annu Symp Proc]]></source>
<year>2023</year>
<volume>2022</volume>
<page-range>319-28</page-range></nlm-citation>
</ref>
<ref id="B5">
<label>5.</label><nlm-citation citation-type="">
<collab>United Nations</collab>
<source><![CDATA[Millennium Development Goals - GOAL 5: Improve maternal health]]></source>
<year></year>
</nlm-citation>
</ref>
<ref id="B6">
<label>6.</label><nlm-citation citation-type="">
<collab>Department of Economic and Social Affairs, United Nations</collab>
<source><![CDATA[Transforming our world: The 2030 agenda for sustainable development]]></source>
<year></year>
</nlm-citation>
</ref>
<ref id="B7">
<label>7.</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Lozano-Avendaño]]></surname>
<given-names><![CDATA[L]]></given-names>
</name>
<name>
<surname><![CDATA[Bohórquez-Ortiz]]></surname>
<given-names><![CDATA[AZ]]></given-names>
</name>
<name>
<surname><![CDATA[Zambrano-Plata]]></surname>
<given-names><![CDATA[GE]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Implicaciones familiares y sociales de la muerte materna]]></article-title>
<source><![CDATA[Univ Salud]]></source>
<year>2016</year>
<volume>18</volume>
<page-range>364-72</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[Sáenz]]></surname>
<given-names><![CDATA[R]]></given-names>
</name>
<name>
<surname><![CDATA[Nigenda]]></surname>
<given-names><![CDATA[G]]></given-names>
</name>
<name>
<surname><![CDATA[Gómez-Duarte]]></surname>
<given-names><![CDATA[I]]></given-names>
</name>
<name>
<surname><![CDATA[Rojas]]></surname>
<given-names><![CDATA[K]]></given-names>
</name>
<name>
<surname><![CDATA[Castro]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[Serván-Mori]]></surname>
<given-names><![CDATA[E]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Persistent inequities in maternal mortality in Latin America and the Caribbean, 1990-2019]]></article-title>
<source><![CDATA[Int J Equity Health]]></source>
<year>2024</year>
<volume>23</volume>
<page-range>96</page-range></nlm-citation>
</ref>
<ref id="B9">
<label>9.</label><nlm-citation citation-type="book">
<collab>Departamento Nacional de Planeación</collab>
<source><![CDATA[Plan Nacional de Desarrollo 2022-2026. Colombia, potencia mundial de la vida]]></source>
<year>2023</year>
<publisher-loc><![CDATA[Bogotá ]]></publisher-loc>
<publisher-name><![CDATA[Departamento Nacional de Planeación]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B10">
<label>10.</label><nlm-citation citation-type="">
<collab>Organización Panamericana de la Salud</collab>
<source><![CDATA[Cada dos minutos muere una mujer por problemas en el embarazo o el parto]]></source>
<year>2023</year>
</nlm-citation>
</ref>
<ref id="B11">
<label>11.</label><nlm-citation citation-type="">
<collab>World Health Organization</collab>
<source><![CDATA[Maternal mortality]]></source>
<year>2025</year>
</nlm-citation>
</ref>
<ref id="B12">
<label>12.</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Gonzales]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[Guruswamy]]></surname>
<given-names><![CDATA[G]]></given-names>
</name>
<name>
<surname><![CDATA[Smith]]></surname>
<given-names><![CDATA[SR]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Synthetic data in health care: A narrative review]]></article-title>
<source><![CDATA[PLOS Digit Health]]></source>
<year>2023</year>
<volume>2</volume>
</nlm-citation>
</ref>
<ref id="B13">
<label>13.</label><nlm-citation citation-type="">
<collab>Mitre Corporation</collab>
<source><![CDATA[GitHub - synthetichealth/synthea: synthetic patient population simulator]]></source>
<year>2025</year>
</nlm-citation>
</ref>
<ref id="B14">
<label>14.</label><nlm-citation citation-type="">
<collab>Observational Health Data Sciences and Informatics</collab>
<source><![CDATA[Standardized data: The OMOP common data model]]></source>
<year>2025</year>
</nlm-citation>
</ref>
<ref id="B15">
<label>15.</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Jones]]></surname>
<given-names><![CDATA[SE]]></given-names>
</name>
<name>
<surname><![CDATA[Bradwell]]></surname>
<given-names><![CDATA[KR]]></given-names>
</name>
<name>
<surname><![CDATA[Chan]]></surname>
<given-names><![CDATA[LE]]></given-names>
</name>
<name>
<surname><![CDATA[McMurry]]></surname>
<given-names><![CDATA[JA]]></given-names>
</name>
<name>
<surname><![CDATA[Olson-Chen]]></surname>
<given-names><![CDATA[C]]></given-names>
</name>
<name>
<surname><![CDATA[Tarleton]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Who is pregnant? Defining real-world data-based pregnancy episodes in the national COVID Cohort Collaborative (N3C)]]></article-title>
<source><![CDATA[JAMIA Open]]></source>
<year>2023</year>
<volume>6</volume>
</nlm-citation>
</ref>
<ref id="B16">
<label>16.</label><nlm-citation citation-type="book">
<collab>Ministerio de Salud y Protección Social</collab>
<source><![CDATA[Guías de práctica clínica para la prevención, detección temprana y tratamiento de las complicaciones del embarazo, parto o puerperio]]></source>
<year>2013</year>
<publisher-loc><![CDATA[Bogotá ]]></publisher-loc>
<publisher-name><![CDATA[Ministerio de Salud y Protección Social]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B17">
<label>17.</label><nlm-citation citation-type="">
<collab>Mitre Corporation</collab>
<source><![CDATA[GitHub - synthetichealth/synthea-international: Synthea metadata and configuration files for international locations]]></source>
<year>2025</year>
</nlm-citation>
</ref>
<ref id="B18">
<label>18.</label><nlm-citation citation-type="">
<collab>Departamento Administrativo Nacional de Estadísticas</collab>
<source><![CDATA[Censo Nacional de Población y Vivienda 2018]]></source>
<year>2025</year>
</nlm-citation>
</ref>
<ref id="B19">
<label>19.</label><nlm-citation citation-type="">
<collab>Ministerio de Tecnologías de la Información y las Comunicaciones</collab>
<source><![CDATA[DIVIPOLA: códigos de municipios geolocalizados]]></source>
<year>2025</year>
</nlm-citation>
</ref>
<ref id="B20">
<label>20.</label><nlm-citation citation-type="">
<collab>Ministerio de Salud y Protección Social</collab>
<source><![CDATA[Listado de IPS en Colombia según su nivel de complejidad]]></source>
<year>2025</year>
</nlm-citation>
</ref>
<ref id="B21">
<label>21.</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Walonoski]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
<name>
<surname><![CDATA[Kramer]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
<name>
<surname><![CDATA[Nichols]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
<name>
<surname><![CDATA[Quina]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[Moesel]]></surname>
<given-names><![CDATA[C]]></given-names>
</name>
<name>
<surname><![CDATA[Hall]]></surname>
<given-names><![CDATA[D]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Synthea: An approach, method, and software mechanism for generating synthetic patients and the synthetic electronic health care record]]></article-title>
<source><![CDATA[J Am Med Inform Assoc]]></source>
<year>2018</year>
<volume>25</volume>
<page-range>230-8</page-range></nlm-citation>
</ref>
<ref id="B22">
<label>22.</label><nlm-citation citation-type="">
<collab>Mitre Corporation</collab>
<source><![CDATA[GitHub. GitHub - OHDSI/ETL-Synthea: A package supporting the conversion from Synthea CSV to OMOP CDM]]></source>
<year>2025</year>
</nlm-citation>
</ref>
<ref id="B23">
<label>23.</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Po]]></surname>
<given-names><![CDATA[L]]></given-names>
</name>
<name>
<surname><![CDATA[Thomas]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
<name>
<surname><![CDATA[Mills]]></surname>
<given-names><![CDATA[K]]></given-names>
</name>
<name>
<surname><![CDATA[Zakhari]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[Tulandi]]></surname>
<given-names><![CDATA[T]]></given-names>
</name>
<name>
<surname><![CDATA[Shuman]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Guideline No. 414: Management of pregnancy of unknown location and tubal and nontubal ectopic pregnancies]]></article-title>
<source><![CDATA[J Obstet Gynaecol Can]]></source>
<year>2021</year>
<volume>43</volume>
<page-range>614-30</page-range></nlm-citation>
</ref>
<ref id="B24">
<label>24.</label><nlm-citation citation-type="journal">
<collab>American College of Obstetricians and Gynecologists</collab>
<article-title xml:lang=""><![CDATA[ACOG Practice Bulletin, number 200: Early pregnancy loss]]></article-title>
<source><![CDATA[Obstet Gynecol]]></source>
<year>2018</year>
<volume>132</volume>
</nlm-citation>
</ref>
<ref id="B25">
<label>25.</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Andersen]]></surname>
<given-names><![CDATA[AMN]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Maternal age and fetal loss: Population based register linkage study]]></article-title>
<source><![CDATA[BMJ]]></source>
<year>2000</year>
<volume>320</volume>
<page-range>1708-12</page-range></nlm-citation>
</ref>
<ref id="B26">
<label>26.</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Tong]]></surname>
<given-names><![CDATA[S]]></given-names>
</name>
<name>
<surname><![CDATA[Kaur]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[Sp]]></surname>
<given-names><![CDATA[Walker]]></given-names>
</name>
<name>
<surname><![CDATA[Bryant]]></surname>
<given-names><![CDATA[V]]></given-names>
</name>
<name>
<surname><![CDATA[Jl]]></surname>
<given-names><![CDATA[Onwude]]></given-names>
</name>
<name>
<surname><![CDATA[Permezel]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Miscarriage risk for asymptomatic women after a normal first-trimester prenatal visit]]></article-title>
<source><![CDATA[Obstet Gynecol]]></source>
<year>2008</year>
<volume>111</volume>
<page-range>710-4</page-range></nlm-citation>
</ref>
<ref id="B27">
<label>27.</label><nlm-citation citation-type="journal">
<collab>American Diabetes Association Professional Practice Committee</collab>
<article-title xml:lang=""><![CDATA[Management of diabetes in pregnancy: Standards of medical care in diabetes-2022]]></article-title>
<source><![CDATA[Diabetes Care]]></source>
<year>2022</year>
<volume>45</volume>
<numero>Suppl.1</numero>
<issue>Suppl.1</issue>
<page-range>S232-43</page-range></nlm-citation>
</ref>
<ref id="B28">
<label>28.</label><nlm-citation citation-type="journal">
<collab>American College of Obstetricians and Gynecologists</collab>
<article-title xml:lang=""><![CDATA[ACOG Practice Bulletin, number 227: Fetal growth restriction]]></article-title>
<source><![CDATA[Obstet Gynecol]]></source>
<year>2021</year>
<volume>137</volume>
</nlm-citation>
</ref>
<ref id="B29">
<label>29.</label><nlm-citation citation-type="journal">
<collab>American College of Obstetricians and Gynecologists</collab>
<article-title xml:lang=""><![CDATA[ACOG Practice Bulletin, number 234: Prediction and prevention of spontaneous preterm birth]]></article-title>
<source><![CDATA[Obstet Gynecol]]></source>
<year>2021</year>
<volume>138</volume>
</nlm-citation>
</ref>
<ref id="B30">
<label>30.</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Rivera Z]]></surname>
<given-names><![CDATA[René]]></given-names>
</name>
<name>
<surname><![CDATA[Caba BF]]></surname>
<given-names><![CDATA[Smirnow SM]]></given-names>
</name>
<name>
<surname><![CDATA[Aguilera TJ]]></surname>
<given-names><![CDATA[Larraín A]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Fisiopatología de la rotura prematura de las membranas ovulares en embarazos de pretérmino]]></article-title>
<source><![CDATA[Rev Chil Obstet Ginecol]]></source>
<year>2004</year>
<volume>69</volume>
<page-range>249-55</page-range></nlm-citation>
</ref>
<ref id="B31">
<label>31.</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Maldonado]]></surname>
<given-names><![CDATA[MD]]></given-names>
</name>
<name>
<surname><![CDATA[Lombardía]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
<name>
<surname><![CDATA[Rodríguez]]></surname>
<given-names><![CDATA[O]]></given-names>
</name>
<name>
<surname><![CDATA[Rincón]]></surname>
<given-names><![CDATA[P]]></given-names>
</name>
<name>
<surname><![CDATA[Sánchez Dehesa]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Hemorragias del tercer trimestre]]></article-title>
<source><![CDATA[SEMERGEN]]></source>
<year>2000</year>
<volume>26</volume>
<page-range>192-5</page-range></nlm-citation>
</ref>
<ref id="B32">
<label>32.</label><nlm-citation citation-type="journal">
<collab>American College of Obstetricians and Gynecologists</collab>
<article-title xml:lang=""><![CDATA[ACOG Practice Bulletin, number 183: Postpartum hemorrhage]]></article-title>
<source><![CDATA[Obstet Gynecol]]></source>
<year>2017</year>
<volume>130</volume>
</nlm-citation>
</ref>
<ref id="B33">
<label>33.</label><nlm-citation citation-type="">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Torres]]></surname>
<given-names><![CDATA[E.]]></given-names>
</name>
</person-group>
<source><![CDATA[Maternal health in Colombia: Synthetic data]]></source>
<year>2025</year>
</nlm-citation>
</ref>
<ref id="B34">
<label>34.</label><nlm-citation citation-type="book">
<collab>Synthea</collab>
<source><![CDATA[Pregnancy module Synthea]]></source>
<year>2025</year>
<publisher-name><![CDATA[GitHub]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B35">
<label>35.</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Rajotte]]></surname>
<given-names><![CDATA[JF]]></given-names>
</name>
<name>
<surname><![CDATA[Bergen]]></surname>
<given-names><![CDATA[R]]></given-names>
</name>
<name>
<surname><![CDATA[Buckeridge]]></surname>
<given-names><![CDATA[DL]]></given-names>
</name>
<name>
<surname><![CDATA[El Emam]]></surname>
<given-names><![CDATA[K]]></given-names>
</name>
<name>
<surname><![CDATA[Ng]]></surname>
<given-names><![CDATA[R]]></given-names>
</name>
<name>
<surname><![CDATA[Strome]]></surname>
<given-names><![CDATA[E]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Synthetic data as an enabler for machine learning applications in medicine]]></article-title>
<source><![CDATA[iScience]]></source>
<year>2022</year>
<volume>25</volume>
<page-range>105331</page-range></nlm-citation>
</ref>
<ref id="B36">
<label>36.</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Prasanna]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[Jing]]></surname>
<given-names><![CDATA[B]]></given-names>
</name>
<name>
<surname><![CDATA[Plopper]]></surname>
<given-names><![CDATA[G]]></given-names>
</name>
<name>
<surname><![CDATA[Miller]]></surname>
<given-names><![CDATA[KK]]></given-names>
</name>
<name>
<surname><![CDATA[Sanjak]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
<name>
<surname><![CDATA[Feng]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Synthetic health data can augment community research efforts to better inform the public during emerging pandemics]]></article-title>
<source><![CDATA[Preprint. medRxiv]]></source>
<year>2023</year>
<volume>2023</volume>
<numero>12</numero>
<issue>12</issue>
<page-range>11</page-range></nlm-citation>
</ref>
<ref id="B37">
<label>37.</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Pammi]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
<name>
<surname><![CDATA[Shah]]></surname>
<given-names><![CDATA[PS]]></given-names>
</name>
<name>
<surname><![CDATA[Yang]]></surname>
<given-names><![CDATA[LK]]></given-names>
</name>
<name>
<surname><![CDATA[Hagan]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
<name>
<surname><![CDATA[Aghaeepour]]></surname>
<given-names><![CDATA[N]]></given-names>
</name>
<name>
<surname><![CDATA[Neu]]></surname>
<given-names><![CDATA[J]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Digital twins, synthetic patient data, and in silico trials: Can they empower paediatric clinical trials?]]></article-title>
<source><![CDATA[Lancet Digit Health]]></source>
<year>2025</year>
<volume>7</volume>
<page-range>100851</page-range></nlm-citation>
</ref>
<ref id="B38">
<label>38.</label><nlm-citation citation-type="journal">
<person-group person-group-type="author">
<name>
<surname><![CDATA[Delanerolle]]></surname>
<given-names><![CDATA[G]]></given-names>
</name>
<name>
<surname><![CDATA[Phiri]]></surname>
<given-names><![CDATA[P]]></given-names>
</name>
<name>
<surname><![CDATA[Cavalini]]></surname>
<given-names><![CDATA[H]]></given-names>
</name>
<name>
<surname><![CDATA[Benfield]]></surname>
<given-names><![CDATA[D]]></given-names>
</name>
<name>
<surname><![CDATA[Shetty]]></surname>
<given-names><![CDATA[A]]></given-names>
</name>
<name>
<surname><![CDATA[Bouchareb]]></surname>
<given-names><![CDATA[Y]]></given-names>
</name>
</person-group>
<article-title xml:lang=""><![CDATA[Synthetic data and the future of women&#8217;s health: A synergistic relationship]]></article-title>
<source><![CDATA[Int J Med Inf]]></source>
<year>2023</year>
<volume>179</volume>
<page-range>105238</page-range></nlm-citation>
</ref>
</ref-list>
</back>
</article>
