<?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>0003-3170</journal-id>
<journal-title><![CDATA[Angiología]]></journal-title>
<abbrev-journal-title><![CDATA[Angiología]]></abbrev-journal-title>
<issn>0003-3170</issn>
<publisher>
<publisher-name><![CDATA[Arán Ediciones S.L.]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0003-31702021000200003</article-id>
<article-id pub-id-type="doi">10.20960/angiologia.00177</article-id>
<title-group>
<article-title xml:lang="es"><![CDATA[Inteligencia artificial y modelado computacional avanzado en cirugía vascular. Implicaciones para la práctica clínica]]></article-title>
<article-title xml:lang="en"><![CDATA[Artificial intelligence, machine learning, vascular surgery, automatic image processing. Implications for clinical practice]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Álvarez Marcos]]></surname>
<given-names><![CDATA[Francisco]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
<xref ref-type="aff" rid="Aaf"/>
<xref ref-type="aff" rid="Aa "/>
<xref ref-type="aff" rid="Af2"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Alonso Gómez]]></surname>
<given-names><![CDATA[Noelia]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
<xref ref-type="aff" rid="A a"/>
<xref ref-type="aff" rid="A2b"/>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Haro Miralles]]></surname>
<given-names><![CDATA[Joaquín de]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
<xref ref-type="aff" rid="A a"/>
<xref ref-type="aff" rid="A2b"/>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,Hospital Universitario Central de Asturias (HUCA) Servicio de Angiología, Cirugía Vascular y Endovascular ]]></institution>
<addr-line><![CDATA[Oviedo ]]></addr-line>
<country>España</country>
</aff>
<aff id="A2a">
<institution><![CDATA[,Red de Investigación Vascular Sociedad Española de Angiología y Cirugía Vascular (SEACV) ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>España</country>
</aff>
<aff id="A2b">
<institution><![CDATA[,Hospital Universitario de Getafe  ]]></institution>
<addr-line><![CDATA[Getafe Madrid]]></addr-line>
<country>España</country>
</aff>
<aff id="Af3">
<institution><![CDATA[,Hospital Central de la Defensa Gómez Ulla Servicio de Angiología, Cirugía Vascular y Endovascular ]]></institution>
<addr-line><![CDATA[Madrid ]]></addr-line>
<country>España</country>
</aff>
<aff id="Af4">
<institution><![CDATA[,Hospital Universitario de Getafe Servicio de Angiología, Cirugía Vascular y Endovascular ]]></institution>
<addr-line><![CDATA[Getafe Madrid]]></addr-line>
<country>España</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>04</month>
<year>2021</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>04</month>
<year>2021</year>
</pub-date>
<volume>73</volume>
<numero>2</numero>
<fpage>65</fpage>
<lpage>75</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://scielo.isciii.es/scielo.php?script=sci_arttext&amp;pid=S0003-31702021000200003&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.isciii.es/scielo.php?script=sci_abstract&amp;pid=S0003-31702021000200003&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://scielo.isciii.es/scielo.php?script=sci_pdf&amp;pid=S0003-31702021000200003&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="es"><p><![CDATA[Resumen La decisión clínica basada en la evidencia se asienta, fundamentalmente, en estudios aleatorizados a gran escala. Sin embargo, la realidad del paciente puede ser mucho más compleja y capturarla en su totalidad para adaptarla a cada caso individual justifica la llamada medicina de precisión, que toma en cuenta sus características genéticas, fenotípicas o psicosociales. Este abordaje es posible gracias al manejo de grandes volúmenes de datos mediante sistemas informáticos complejos basados en inteligencia artificial (IA) y machine learning (ML). Esta actualización divulgativa, basada en más de 50 artículos, pretende aproximarse a la aplicación de IA y ML en todos los aspectos de la angiología, cirugía vascular y endovascular contemporánea. El campo con mayor desarrollo potencial es el procesamiento y la automatización de la imagen vascular, que permite también la segmentación automática de vasos, la estimación de movimiento y deformaciones y su posterior integración en el guiado del tratamiento. La IA y el ML también ofrecen grandes posibilidades en simulación de procedimientos, cada vez más importante en cirugía abierta, y en la mejora de la interacción del operador con las estaciones de trabajo y sistemas de ayuda, tanto de imagen como robóticos. Por último, la integración masiva de datos abre nuevos horizontes en la predicción de resultados, acercando la calidad y el potencial impacto de los registros a los de los estudios aleatorizados y mejorando los resultados de la estadística convencional.]]></p></abstract>
<abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract Evidence-based clinical decision is based overall in broad-spectrum randomized studies. However, the patient's reality may be much more complex, and capturing it as a whole justifies the so-called precision medicine, which takes into account genetic, phenotypic and psycho-social variables. This approach is possible thanks to the management of big data, using complex computing system based in artificial intelligence (AI) and machine learning (ML). This update, based on over 50 publications, intends to give a view on IA and ML application on every aspect of contemporary vascular and endovascular practice. The field with a greater potential development is automatic image processing, that allows vessel segmentation, deformation and movement estimations and the subsequent integration into treatment guidance. IA and ML also offer great possibilities in simulation, especially of open surgical procedures, and also in the improvement of machine-operator interaction with workstations and robotic systems. Finally, big data integration opens new horizons in outcome prediction, almost matching the quality and potential impact of register to these of randomized evidence, and overcoming the results of traditional statistics.]]></p></abstract>
<kwd-group>
<kwd lng="es"><![CDATA[Inteligencia artificial]]></kwd>
<kwd lng="es"><![CDATA[Machine learning]]></kwd>
<kwd lng="es"><![CDATA[Procesado automático de imagen]]></kwd>
<kwd lng="es"><![CDATA[Simulación]]></kwd>
<kwd lng="es"><![CDATA[Big data]]></kwd>
<kwd lng="en"><![CDATA[Artificial intelligence]]></kwd>
<kwd lng="en"><![CDATA[Machine learning]]></kwd>
<kwd lng="en"><![CDATA[Automatic image processing]]></kwd>
<kwd lng="en"><![CDATA[Simulation]]></kwd>
<kwd lng="en"><![CDATA[Big data]]></kwd>
</kwd-group>
</article-meta>
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