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DASH<a class="elsevierStyleCrossRef" href="#bib0085"><span class="elsevierStyleSup">2</span></a>&#44; HER-DOO2<a class="elsevierStyleCrossRef" href="#bib0090"><span class="elsevierStyleSup">3</span></a>&#160;y DAMOVES<a class="elsevierStyleCrossRef" href="#bib0095"><span class="elsevierStyleSup">4</span></a>&#41;&#46; Sin embargo&#44; estas escalas han mostrado una capacidad predictiva limitada en su validaci&#243;n externa<a class="elsevierStyleCrossRefs" href="#bib0100"><span class="elsevierStyleSup">5&#8211;11</span></a>&#46;&#160;En consecuencia&#44; las gu&#237;as actuales sobre ETEV no respaldan el uso de estos modelos para decidir la suspensi&#243;n o continuaci&#243;n de la terapia anticoagulante tras un periodo de tratamiento de al menos 3 meses&#46;</p><p id="par0015" class="elsevierStylePara elsevierViewall">La inteligencia artificial es la simulaci&#243;n de la inteligencia humana&#46; Desarrolla algoritmos capaces de realizar tareas normalmente asociadas a la inteligencia humana como el aprendizaje&#44; la toma de decisiones y el procesamiento del lenguaje natural&#46; Para ello necesita enormes cantidades de datos junto a una gran capacidad de computaci&#243;n que soporte los procesos de aprendizaje profundo o <span class="elsevierStyleItalic">deep learning&#46;</span> Recientemente&#44; la IA se ha incorporado a la medicina con el prop&#243;sito de acelerar procesos y favorecer la precisi&#243;n en &#225;mbitos como el diagn&#243;stico&#44; la predicci&#243;n o el tratamiento de las enfermedades mediante el reconocimiento de patrones&#46; Estas herramientas tecnol&#243;gicas pueden ayudar en la toma de decisiones en condiciones de incertidumbre y predecir datos futuros&#44; contribuyendo al desarrollo de una medicina m&#225;s personalizada con menores tasas de error&#46; Asimismo&#44; la IA puede ofrecer informaci&#243;n valiosa en pacientes que por sus caracter&#237;sticas se&#160;excluyen de los ensayos&#160;cl&#237;nicos&#46; Sin embargo&#44; su implementaci&#243;n no es sencilla&#46; Los escenarios de aprendizaje autom&#225;tico aplicados a la medicina suponen un esfuerzo de modernizaci&#243;n y coordinaci&#243;n sin precedentes&#46; Para su implementaci&#243;n&#44; hay una serie de retos tecnol&#243;gicos y &#233;ticos&#46; Dentro de los primeros se encuentran la cantidad de datos&#44; la capacidad de procesamiento y las plataformas de Machine Learning &#40;ML&#41;&#46; Dentro de los segundos estar&#237;a la calidad de los datos&#44; la representatividad y privacidad de estos&#44; la transparencia y explicabilidad de los algoritmos&#44; la supervisi&#243;n humana y la generaci&#243;n de evidencia a trav&#233;s de la validaci&#243;n externa&#46;</p><p id="par0020" class="elsevierStylePara elsevierViewall">Dentro de las t&#233;cnicas de IA aplicadas al &#225;mbito m&#233;dico existe cada d&#237;a mayor inter&#233;s por el ML cuyo objetivo es desarrollar algoritmos que permitan que unos sistemas inform&#225;ticos tomen decisiones y aprendan de su resultado&#46; Estos modelos basan su fortaleza en la predicci&#243;n analizando la informaci&#243;n disponible&#44; sin necesidad de conocer cu&#225;les son los mecanismos que relacionan las variables entre s&#237;&#46; El ML entrena un&#160;algoritmo&#160;con datos de entrada que recogen observaciones del pasado&#44; y construye un modelo para predecir resultados&#46; La siguiente etapa es la validaci&#243;n&#46; Para el proceso de entrenamiento-validaci&#243;n el conjunto de datos se divide en porcentajes habituales del 70 y el 30&#37;&#44; respectivamente&#46;</p><p id="par0025" class="elsevierStylePara elsevierViewall">Los modelos matem&#225;ticos podr&#237;an pronosticar con mayor precisi&#243;n el riesgo de recurrencia en paciente con ETEV&#46; En este sentido abordamos una&#160;revisi&#243;n&#160;de la&#160;literatura&#160;para conocer el rendimiento de los algoritmos de IA para predecir recidiva en pacientes con TEV comparado con los modelos de regresi&#243;n m&#250;ltiple &#40;<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>&#41;&#46; Calazans et al&#46;<a class="elsevierStyleCrossRef" href="#bib0135"><span class="elsevierStyleSup">12</span></a> realizaron un estudio de cohorte retrospectivo en el que seleccionaron 240 pacientes con un episodio de trombosis venosa profunda para investigar el rendimiento de un modelo de red neuronal&#46; En la fase de validaci&#243;n el algoritmo clasific&#243; con precisi&#243;n la presencia o ausencia de recurrencia&#44; con un <span class="elsevierStyleItalic">output</span> de 0&#44;97&#46; Martins et al&#46;<a class="elsevierStyleCrossRef" href="#bib0140"><span class="elsevierStyleSup">13</span></a> publicaron un estudio de pacientes con ETEV provocada y no provocada en el que se evalu&#243; el rendimiento de tres algoritmos de red neuronal&#46; Para ello&#44; analizaron 39 variables cl&#237;nicas y de laboratorio preseleccionadas en 235 pacientes&#46; La capacidad para distinguir la recurrencia en la cohorte de validaci&#243;n fue excelente&#44; con un &#225;rea bajo la curva &#62;0&#44;90 para los tres modelos&#46; En otro estudio retrospectivo se aplic&#243; la t&#233;cnica de ML en pacientes con c&#225;ncer y un episodio de ETEV tratado con anticoagulantes durante un periodo de 6 meses<a class="elsevierStyleCrossRef" href="#bib0145"><span class="elsevierStyleSup">14</span></a>&#46; La incidencia acumulada de TEV recurrente oscil&#243; entre el 2&#44;7 y 3&#44;9&#37; tras suspender la anticoagulaci&#243;n&#46; La capacidad del modelo Random Forest para distinguir la recurrencia fue buena&#44; calcul&#225;ndose una c-estad&#237;stica de 0&#44;72&#46; Finalmente&#44; el estudio de Mora et al&#46;<a class="elsevierStyleCrossRef" href="#bib0150"><span class="elsevierStyleSup">15</span></a> evalu&#243; 5 algoritmos de IA en pacientes con embolia pulmonar aguda que requirieron la interrupci&#243;n del tratamiento anticoagulante antes de 90 d&#237;as&#46; Se incluyeron 1&#46;348 pacientes del Registro Informatizado de Enfermedad Tromboemb&#243;lica &#40;RIETE&#41;&#44; durante un periodo de 18 a&#241;os&#46; Hubo 69 recurrencias&#46; La capacidad discriminativa de los algoritmos fue alta siendo Neural Network el m&#225;s preciso&#46;</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><p id="par0030" class="elsevierStylePara elsevierViewall">En conclusi&#243;n&#44; 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                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">N&#250;mero de pacientes&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Periodo de estudio&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Modelo&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Validaci&#243;n&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th><th class="td" title="\n
                  \t\t\t\t\ttable-head\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Resultado&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Marcucci et al&#46;&#44; 2015<a class="elsevierStyleCrossRef" href="#bib0100"><span class="elsevierStyleSup">5</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Prospectivo&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Pacientes con TEV no provocado&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">904&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">De 1992 a 2008&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Modelo predictivo de Viena&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Externa&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">AUC 0&#44;62&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Tritschler et al&#46;&#44; 2015<a class="elsevierStyleCrossRef" href="#bib0105"><span class="elsevierStyleSup">6</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Prospectivo&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Pacientes con TEV no provocado&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">156&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Desde septiembre de 2009 hasta diciembre de 2013&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Modelo predictivo de Viena&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Externa&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">AUC 0&#44;39 y 0&#44;43 a los 12 meses y 24 meses&#44; respectivamente&#46;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Timp et al&#46;&#44; 2019<a class="elsevierStyleCrossRef" href="#bib0110"><span class="elsevierStyleSup">7</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Prospectivo&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Pacientes con TEV no provocado&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">3&#46;750&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Desde marzo de 1999 hasta agosto de 2004&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Modelo predictivo de Viena&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Externa&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">AUC 0&#44;62&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Marin-Romero et al&#46;&#44; 2019<a class="elsevierStyleCrossRef" href="#bib0115"><span class="elsevierStyleSup">8</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Retrospectivo&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Pacientes con TEV no provocado&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">195&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">De 2006 a 2014&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Modelo predictivo de Viena&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Externa&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">AUC 0&#44;63&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Rodger et al&#46;&#44; 2017<a class="elsevierStyleCrossRef" href="#bib0120"><span class="elsevierStyleSup">9</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Prospectivo&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Pacientes con TEV no provocado&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">2&#46;785&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Desde noviembre de 2008 hasta febrero de 2015&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Regla HER-DOO2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Externa&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Incidencia acumulada de TEV recurrente del 3&#44;0&#37; y 8&#44;1&#37; en mujeres de bajo riesgo y en mujeres y hombres del alto riesgo&#44; respectivamente&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Tosetto et al&#46;&#44; 2017<a class="elsevierStyleCrossRef" href="#bib0125"><span class="elsevierStyleSup">10</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Retrospectivo&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Pacientes con de TEV no provocado&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">827&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Desde enero de 2007 hasta septiembre de 2016&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Score DASH&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Externa&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">AUC 0&#44;65&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Timp et al&#46;&#44; 2019<a class="elsevierStyleCrossRef" href="#bib0110"><span class="elsevierStyleSup">7</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Prospectivo&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Pacientes con TEV no provocado&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">3&#46;750&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Desde marzo de 1999 hasta agosto de 2004&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Score DASH&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Externa&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">AUC 0&#44;66&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Marin-Romero et al&#46;&#44; 2019<a class="elsevierStyleCrossRef" href="#bib0115"><span class="elsevierStyleSup">8</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Retrospectivo&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Pacientes con TEV no provocado&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">195&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">De 2006 a 2014&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Score DASH&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Externa&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">AUC 0&#44;63&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Franco et al&#46;&#44;2017<a class="elsevierStyleCrossRef" href="#bib0130"><span class="elsevierStyleSup">11</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Retrospectivo&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Pacientes con TEV no provocado&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">121&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Desde agosto de 2012 hasta octubre de 2015&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Nomograma DAMOVES&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Externa&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">AUC 0&#44;83&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Calazans et al&#46;&#44; 2016<a class="elsevierStyleCrossRef" href="#bib0135"><span class="elsevierStyleSup">12</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Retrospectivo&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Pacientes con TVP&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">240&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">NR&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Neural Network&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Interna&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">Output</span> 0&#44;97&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " rowspan="3" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Martins et al&#46;&#44; 2020<a class="elsevierStyleCrossRef" href="#bib0140"><span class="elsevierStyleSup">13</span></a></td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " rowspan="3" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Retrospectivo</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " rowspan="3" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Pacientes con TEV provocado y no provocado</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " rowspan="3" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">235</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " rowspan="3" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Desde enero de 2009 hasta agosto de 2016</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Neural Network 1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " rowspan="3" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Interna</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">AUC 0&#44;96&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Neural Network 2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">AUC 0&#44;93&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Neural Network 3&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">AUC 0&#44;98&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Mu&#241;oz et al&#46;&#44; 2022<a class="elsevierStyleCrossRef" href="#bib0145"><span class="elsevierStyleSup">14</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Retrospectivo&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Pacientes con c&#225;ncer activo y un episodio de TEV tratados con anticoagulantes 6 meses&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">21&#46;227&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">De 2014 a 2018&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Random Forest&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Interna&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">AUC 0&#44;72&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " rowspan="10" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Mora et al&#46;&#44; 2022<a class="elsevierStyleCrossRef" href="#bib0150"><span class="elsevierStyleSup">15</span></a></td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " rowspan="10" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Retrospectivo</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " rowspan="10" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Pacientes con EP que interrumpieron la anticoagulaci&#243;n antes de 90 d&#237;as</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " rowspan="10" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&#46;348</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " rowspan="10" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Desde marzo de 2001 hasta marzo de 2018</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " rowspan="2" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Decision tree</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " rowspan="10" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Interna</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">EP fatal&#58; AUC 0&#44;80&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">TEV no fatal&#58; AUC 0&#44;80&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " rowspan="2" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">K-nearest neighbors</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">EP fatal&#58; AUC 0&#44;87&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">TEV no fatal&#58; AUC 0&#44;87&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " rowspan="2" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Support vector machine</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">EP fatal&#58; AUC 0&#44;85&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">TEV no fatal&#58; AUC 0&#44;85&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " rowspan="2" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Ensemble</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">EP fatal&#58; AUC 0&#44;90&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">TEV no fatal&#58; AUC 0&#44;90&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " rowspan="2" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Neural Network</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">EP fatal&#58; AUC 0&#44;96&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">TEV no fatal&#58; AUC 0&#44;96&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
                  """
              ]
              "imagenFichero" => array:1 [
                0 => "xTab3395482.png"
              ]
            ]
          ]
        ]
        "descripcion" => array:1 [
          "es" => "<p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">Rendimiento de los modelos de regresi&#243;n m&#250;ltiple y de los algoritmos de inteligencia artificial para predecir recurrencia en pacientes con tromboembolismo venoso</p>"
        ]
      ]
    ]
    "bibliografia" => array:2 [
      "titulo" => "Bibliograf&#237;a"
      "seccion" => array:1 [
        0 => array:2 [
          "identificador" => "bibs0015"
          "bibliografiaReferencia" => array:15 [
            0 => array:3 [
              "identificador" => "bib0080"
              "etiqueta" => "1"
              "referencia" => array:1 [
                0 => array:2 [
                  "contribucion" => array:1 [
                    0 => array:2 [
                      "titulo" => "Risk assessment of recurrence in patients with unprovoked deep vein thrombosis or pulmonary embolism&#58; The Vienna prediction model"
                      "autores" => array:1 [
                        0 => array:2 [
                          "etal" => false
                          "autores" => array:4 [
                            0 => "S&#46; Eichinger"
                            1 => "G&#46; Heinze"
                            2 => "L&#46;M&#46; Jandeck"
                            3 => "P&#46;A&#46; Kyrle"
                          ]
                        ]
                      ]
                    ]
                  ]
                  "host" => array:1 [
                    0 => array:2 [
                      "doi" => "10.1161/CIRCULATIONAHA.109.925214"
                      "Revista" => array:6 [
                        "tituloSerie" => "Circulation"
                        "fecha" => "2010"
                        "volumen" => "121"
                        "paginaInicial" => "1630"
                        "paginaFinal" => "1636"
                        "link" => array:1 [
                          0 => array:2 [
                            "url" => "https://www.ncbi.nlm.nih.gov/pubmed/20351233"
                            "web" => "Medline"
                          ]
                        ]
                      ]
                    ]
                  ]
                ]
              ]
            ]
            1 => array:3 [
              "identificador" => "bib0085"
              "etiqueta" => "2"
              "referencia" => array:1 [
                0 => array:2 [
                  "contribucion" => array:1 [
                    0 => array:2 [
                      "titulo" => "Predicting disease recurrence in patients with previous unprovoked venous thromboembolism&#58; A proposed prediction score &#40;DASH&#41;"
                      "autores" => array:1 [
                        0 => array:2 [
                          "etal" => true
                          "autores" => array:6 [
                            0 => "A&#46; Tosetto"
                            1 => "A&#46; Iorio"
                            2 => "M&#46; Marcucci"
                            3 => "T&#46; Baglin"
                            4 => "M&#46; Cushman"
                            5 => "S&#46; Eichinger"
                          ]
                        ]
                      ]
                    ]
                  ]
                  "host" => array:1 [
                    0 => array:2 [
                      "doi" => "10.1111/j.1538-7836.2012.04735.x"
                      "Revista" => array:6 [
                        "tituloSerie" => "J Thromb Haemost"
                        "fecha" => "2012"
                        "volumen" => "10"
                        "paginaInicial" => "1019"
                        "paginaFinal" => "1025"
                        "link" => array:1 [
                          0 => array:2 [
                            "url" => "https://www.ncbi.nlm.nih.gov/pubmed/22489957"
                            "web" => "Medline"
                          ]
                        ]
                      ]
                    ]
                  ]
                ]
              ]
            ]
            2 => array:3 [
              "identificador" => "bib0090"
              "etiqueta" => "3"
              "referencia" => array:1 [
                0 => array:2 [
                  "contribucion" => array:1 [
                    0 => array:2 [
                      "titulo" => "Identifying unprovoked thromboembolism patients at low risk for recurrence who can discontinue anticoagulant therapy"
                      "autores" => array:1 [
                        0 => array:2 [
                          "etal" => true
                          "autores" => array:6 [
                            0 => "M&#46;A&#46; Rodger"
                            1 => "S&#46;R&#46; Kahn"
                            2 => "P&#46;S&#46; Wells"
                            3 => "D&#46;A&#46; Anderson"
                            4 => "I&#46; Chagnon"
                            5 => "G&#46; Le Gal"
                          ]
                        ]
                      ]
                    ]
                  ]
                  "host" => array:1 [
                    0 => array:2 [
                      "doi" => "10.1503/cmaj.080493"
                      "Revista" => array:6 [
                        "tituloSerie" => "CMAJ"
                        "fecha" => "2008"
                        "volumen" => "179"
                        "paginaInicial" => "417"
                        "paginaFinal" => "426"
                        "link" => array:1 [
                          0 => array:2 [
                            "url" => "https://www.ncbi.nlm.nih.gov/pubmed/18725614"
                            "web" => "Medline"
                          ]
                        ]
                      ]
                    ]
                  ]
                ]
              ]
            ]
            3 => array:3 [
              "identificador" => "bib0095"
              "etiqueta" => "4"
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Correspondencia
Inteligencia artificial para predecir recurrencia en pacientes con enfermedad tromboembólica venosa: hacia una nueva era
Artificial intelligence for recurrence in patients with venous thromboembolism: towards a new era
A. Franco-Morenoa,
Autor para correspondencia
afranco278@hotmail.com

Autor para correspondencia.
, N. Muñoz-Rivasa, J.M. Ruiz-Giardínb, C. de Ancos-Aracilc
a Medicina Interna, Unidad de Enfermedad Tromboembólica Venosa. Hospital Universitario Infanta Leonor-Virgen de la Torre, Madrid, España
b Medicina Interna, Hospital Universitario de Fuenlabrada, Madrid, España, Fuenlabrada, Madrid, España
c Medicina Interna, Unidad de Enfermedad Tromboembólica Venosa, Hospital Universitario de Fuenlabrada, Fuenlabrada, Madrid, España
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DASH<a class="elsevierStyleCrossRef" href="#bib0085"><span class="elsevierStyleSup">2</span></a>&#44; HER-DOO2<a class="elsevierStyleCrossRef" href="#bib0090"><span class="elsevierStyleSup">3</span></a>&#160;y DAMOVES<a class="elsevierStyleCrossRef" href="#bib0095"><span class="elsevierStyleSup">4</span></a>&#41;&#46; Sin embargo&#44; estas escalas han mostrado una capacidad predictiva limitada en su validaci&#243;n externa<a class="elsevierStyleCrossRefs" href="#bib0100"><span class="elsevierStyleSup">5&#8211;11</span></a>&#46;&#160;En consecuencia&#44; las gu&#237;as actuales sobre ETEV no respaldan el uso de estos modelos para decidir la suspensi&#243;n o continuaci&#243;n de la terapia anticoagulante tras un periodo de tratamiento de al menos 3 meses&#46;</p><p id="par0015" class="elsevierStylePara elsevierViewall">La inteligencia artificial es la simulaci&#243;n de la inteligencia humana&#46; Desarrolla algoritmos capaces de realizar tareas normalmente asociadas a la inteligencia humana como el aprendizaje&#44; la toma de decisiones y el procesamiento del lenguaje natural&#46; Para ello necesita enormes cantidades de datos junto a una gran capacidad de computaci&#243;n que soporte los procesos de aprendizaje profundo o <span class="elsevierStyleItalic">deep learning&#46;</span> Recientemente&#44; la IA se ha incorporado a la medicina con el prop&#243;sito de acelerar procesos y favorecer la precisi&#243;n en &#225;mbitos como el diagn&#243;stico&#44; la predicci&#243;n o el tratamiento de las enfermedades mediante el reconocimiento de patrones&#46; Estas herramientas tecnol&#243;gicas pueden ayudar en la toma de decisiones en condiciones de incertidumbre y predecir datos futuros&#44; contribuyendo al desarrollo de una medicina m&#225;s personalizada con menores tasas de error&#46; Asimismo&#44; la IA puede ofrecer informaci&#243;n valiosa en pacientes que por sus caracter&#237;sticas se&#160;excluyen de los ensayos&#160;cl&#237;nicos&#46; Sin embargo&#44; su implementaci&#243;n no es sencilla&#46; Los escenarios de aprendizaje autom&#225;tico aplicados a la medicina suponen un esfuerzo de modernizaci&#243;n y coordinaci&#243;n sin precedentes&#46; Para su implementaci&#243;n&#44; hay una serie de retos tecnol&#243;gicos y &#233;ticos&#46; Dentro de los primeros se encuentran la cantidad de datos&#44; la capacidad de procesamiento y las plataformas de Machine Learning &#40;ML&#41;&#46; Dentro de los segundos estar&#237;a la calidad de los datos&#44; la representatividad y privacidad de estos&#44; la transparencia y explicabilidad de los algoritmos&#44; la supervisi&#243;n humana y la generaci&#243;n de evidencia a trav&#233;s de la validaci&#243;n externa&#46;</p><p id="par0020" class="elsevierStylePara elsevierViewall">Dentro de las t&#233;cnicas de IA aplicadas al &#225;mbito m&#233;dico existe cada d&#237;a mayor inter&#233;s por el ML cuyo objetivo es desarrollar algoritmos que permitan que unos sistemas inform&#225;ticos tomen decisiones y aprendan de su resultado&#46; Estos modelos basan su fortaleza en la predicci&#243;n analizando la informaci&#243;n disponible&#44; sin necesidad de conocer cu&#225;les son los mecanismos que relacionan las variables entre s&#237;&#46; El ML entrena un&#160;algoritmo&#160;con datos de entrada que recogen observaciones del pasado&#44; y construye un modelo para predecir resultados&#46; La siguiente etapa es la validaci&#243;n&#46; Para el proceso de entrenamiento-validaci&#243;n el conjunto de datos se divide en porcentajes habituales del 70 y el 30&#37;&#44; respectivamente&#46;</p><p id="par0025" class="elsevierStylePara elsevierViewall">Los modelos matem&#225;ticos podr&#237;an pronosticar con mayor precisi&#243;n el riesgo de recurrencia en paciente con ETEV&#46; En este sentido abordamos una&#160;revisi&#243;n&#160;de la&#160;literatura&#160;para conocer el rendimiento de los algoritmos de IA para predecir recidiva en pacientes con TEV comparado con los modelos de regresi&#243;n m&#250;ltiple &#40;<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>&#41;&#46; Calazans et al&#46;<a class="elsevierStyleCrossRef" href="#bib0135"><span class="elsevierStyleSup">12</span></a> realizaron un estudio de cohorte retrospectivo en el que seleccionaron 240 pacientes con un episodio de trombosis venosa profunda para investigar el rendimiento de un modelo de red neuronal&#46; En la fase de validaci&#243;n el algoritmo clasific&#243; con precisi&#243;n la presencia o ausencia de recurrencia&#44; con un <span class="elsevierStyleItalic">output</span> de 0&#44;97&#46; Martins et al&#46;<a class="elsevierStyleCrossRef" href="#bib0140"><span class="elsevierStyleSup">13</span></a> publicaron un estudio de pacientes con ETEV provocada y no provocada en el que se evalu&#243; el rendimiento de tres algoritmos de red neuronal&#46; Para ello&#44; analizaron 39 variables cl&#237;nicas y de laboratorio preseleccionadas en 235 pacientes&#46; La capacidad para distinguir la recurrencia en la cohorte de validaci&#243;n fue excelente&#44; con un &#225;rea bajo la curva &#62;0&#44;90 para los tres modelos&#46; En otro estudio retrospectivo se aplic&#243; la t&#233;cnica de ML en pacientes con c&#225;ncer y un episodio de ETEV tratado con anticoagulantes durante un periodo de 6 meses<a class="elsevierStyleCrossRef" href="#bib0145"><span class="elsevierStyleSup">14</span></a>&#46; La incidencia acumulada de TEV recurrente oscil&#243; entre el 2&#44;7 y 3&#44;9&#37; tras suspender la anticoagulaci&#243;n&#46; La capacidad del modelo Random Forest para distinguir la recurrencia fue buena&#44; calcul&#225;ndose una c-estad&#237;stica de 0&#44;72&#46; Finalmente&#44; el estudio de Mora et al&#46;<a class="elsevierStyleCrossRef" href="#bib0150"><span class="elsevierStyleSup">15</span></a> evalu&#243; 5 algoritmos de IA en pacientes con embolia pulmonar aguda que requirieron la interrupci&#243;n del tratamiento anticoagulante antes de 90 d&#237;as&#46; Se incluyeron 1&#46;348 pacientes del Registro Informatizado de Enfermedad Tromboemb&#243;lica &#40;RIETE&#41;&#44; durante un periodo de 18 a&#241;os&#46; Hubo 69 recurrencias&#46; La capacidad discriminativa de los algoritmos fue alta siendo Neural Network el m&#225;s preciso&#46;</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><p id="par0030" class="elsevierStylePara elsevierViewall">En conclusi&#243;n&#44; los modelos de IA discriminaron adecuadamente los pacientes con riesgo de recurrencia de la ETEV&#46; Sin embargo&#44; estos resultados requieren de validaci&#243;n externa&#46; Es necesario incrementar la formaci&#243;n de los m&#233;dicos en an&#225;lisis avanzados de datos&#44; as&#237; como fomentar la colaboraci&#243;n con expertos en tecnolog&#237;as inteligentes de la informaci&#243;n&#46;</p><span id="sec0005" class="elsevierStyleSection elsevierViewall"><span class="elsevierStyleSectionTitle" id="sect0005">Conflicto de intereses</span><p id="par0035" class="elsevierStylePara elsevierViewall">Los autores declaran que no tienen ning&#250;n conflicto de inter&#233;s&#46;</p></span></span>"
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                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Pacientes con TEV no provocado&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">156&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Desde septiembre de 2009 hasta diciembre de 2013&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Modelo predictivo de Viena&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Externa&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">AUC 0&#44;39 y 0&#44;43 a los 12 meses y 24 meses&#44; respectivamente&#46;&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Timp et al&#46;&#44; 2019<a class="elsevierStyleCrossRef" href="#bib0110"><span class="elsevierStyleSup">7</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Prospectivo&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Pacientes con TEV no provocado&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">3&#46;750&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Desde marzo de 1999 hasta agosto de 2004&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Modelo predictivo de Viena&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Externa&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">AUC 0&#44;62&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Marin-Romero et al&#46;&#44; 2019<a class="elsevierStyleCrossRef" href="#bib0115"><span class="elsevierStyleSup">8</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Retrospectivo&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Pacientes con TEV no provocado&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">195&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">De 2006 a 2014&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Modelo predictivo de Viena&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Externa&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">AUC 0&#44;63&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Rodger et al&#46;&#44; 2017<a class="elsevierStyleCrossRef" href="#bib0120"><span class="elsevierStyleSup">9</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Prospectivo&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Pacientes con TEV no provocado&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">2&#46;785&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Desde noviembre de 2008 hasta febrero de 2015&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Regla HER-DOO2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Externa&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Incidencia acumulada de TEV recurrente del 3&#44;0&#37; y 8&#44;1&#37; en mujeres de bajo riesgo y en mujeres y hombres del alto riesgo&#44; respectivamente&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Tosetto et al&#46;&#44; 2017<a class="elsevierStyleCrossRef" href="#bib0125"><span class="elsevierStyleSup">10</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Retrospectivo&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Pacientes con de TEV no provocado&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">827&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Desde enero de 2007 hasta septiembre de 2016&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Score DASH&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Externa&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">AUC 0&#44;65&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Timp et al&#46;&#44; 2019<a class="elsevierStyleCrossRef" href="#bib0110"><span class="elsevierStyleSup">7</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Prospectivo&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Pacientes con TEV no provocado&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">3&#46;750&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Desde marzo de 1999 hasta agosto de 2004&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Score DASH&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Externa&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">AUC 0&#44;66&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Marin-Romero et al&#46;&#44; 2019<a class="elsevierStyleCrossRef" href="#bib0115"><span class="elsevierStyleSup">8</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Retrospectivo&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Pacientes con TEV no provocado&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">195&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">De 2006 a 2014&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Score DASH&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Externa&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">AUC 0&#44;63&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Franco et al&#46;&#44;2017<a class="elsevierStyleCrossRef" href="#bib0130"><span class="elsevierStyleSup">11</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Retrospectivo&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Pacientes con TEV no provocado&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">121&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Desde agosto de 2012 hasta octubre de 2015&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Nomograma DAMOVES&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Externa&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">AUC 0&#44;83&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Calazans et al&#46;&#44; 2016<a class="elsevierStyleCrossRef" href="#bib0135"><span class="elsevierStyleSup">12</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Retrospectivo&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Pacientes con TVP&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">240&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">NR&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Neural Network&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Interna&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t"><span class="elsevierStyleItalic">Output</span> 0&#44;97&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " rowspan="3" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Martins et al&#46;&#44; 2020<a class="elsevierStyleCrossRef" href="#bib0140"><span class="elsevierStyleSup">13</span></a></td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " rowspan="3" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Retrospectivo</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " rowspan="3" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Pacientes con TEV provocado y no provocado</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " rowspan="3" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">235</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " rowspan="3" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Desde enero de 2009 hasta agosto de 2016</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Neural Network 1&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " rowspan="3" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Interna</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">AUC 0&#44;96&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Neural Network 2&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">AUC 0&#44;93&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Neural Network 3&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">AUC 0&#44;98&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Mu&#241;oz et al&#46;&#44; 2022<a class="elsevierStyleCrossRef" href="#bib0145"><span class="elsevierStyleSup">14</span></a>&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Retrospectivo&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Pacientes con c&#225;ncer activo y un episodio de TEV tratados con anticoagulantes 6 meses&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">21&#46;227&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">De 2014 a 2018&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Random Forest&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Interna&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">AUC 0&#44;72&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " rowspan="10" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Mora et al&#46;&#44; 2022<a class="elsevierStyleCrossRef" href="#bib0150"><span class="elsevierStyleSup">15</span></a></td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " rowspan="10" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Retrospectivo</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " rowspan="10" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Pacientes con EP que interrumpieron la anticoagulaci&#243;n antes de 90 d&#237;as</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " rowspan="10" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">1&#46;348</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " rowspan="10" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Desde marzo de 2001 hasta marzo de 2018</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " rowspan="2" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Decision tree</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " rowspan="10" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Interna</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">EP fatal&#58; AUC 0&#44;80&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">TEV no fatal&#58; AUC 0&#44;80&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " rowspan="2" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">K-nearest neighbors</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">EP fatal&#58; AUC 0&#44;87&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">TEV no fatal&#58; AUC 0&#44;87&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " rowspan="2" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Support vector machine</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">EP fatal&#58; AUC 0&#44;85&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">TEV no fatal&#58; AUC 0&#44;85&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " rowspan="2" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Ensemble</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">EP fatal&#58; AUC 0&#44;90&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">TEV no fatal&#58; AUC 0&#44;90&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " rowspan="2" align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">Neural Network</td><td class="td" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t  " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">EP fatal&#58; AUC 0&#44;96&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n
                  \t\t\t\t\ttable-entry\n
                  \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n
                  \t\t\t\t\ttop\n
                  \t\t\t\t">TEV no fatal&#58; AUC 0&#44;96&nbsp;\t\t\t\t\t\t\n
                  \t\t\t\t</td></tr></tbody></table>
                  """
              ]
              "imagenFichero" => array:1 [
                0 => "xTab3395482.png"
              ]
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          ]
        ]
        "descripcion" => array:1 [
          "es" => "<p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">Rendimiento de los modelos de regresi&#243;n m&#250;ltiple y de los algoritmos de inteligencia artificial para predecir recurrencia en pacientes con tromboembolismo venoso</p>"
        ]
      ]
    ]
    "bibliografia" => array:2 [
      "titulo" => "Bibliograf&#237;a"
      "seccion" => array:1 [
        0 => array:2 [
          "identificador" => "bibs0015"
          "bibliografiaReferencia" => array:15 [
            0 => array:3 [
              "identificador" => "bib0080"
              "etiqueta" => "1"
              "referencia" => array:1 [
                0 => array:2 [
                  "contribucion" => array:1 [
                    0 => array:2 [
                      "titulo" => "Risk assessment of recurrence in patients with unprovoked deep vein thrombosis or pulmonary embolism&#58; The Vienna prediction model"
                      "autores" => array:1 [
                        0 => array:2 [
                          "etal" => false
                          "autores" => array:4 [
                            0 => "S&#46; Eichinger"
                            1 => "G&#46; Heinze"
                            2 => "L&#46;M&#46; Jandeck"
                            3 => "P&#46;A&#46; Kyrle"
                          ]
                        ]
                      ]
                    ]
                  ]
                  "host" => array:1 [
                    0 => array:2 [
                      "doi" => "10.1161/CIRCULATIONAHA.109.925214"
                      "Revista" => array:6 [
                        "tituloSerie" => "Circulation"
                        "fecha" => "2010"
                        "volumen" => "121"
                        "paginaInicial" => "1630"
                        "paginaFinal" => "1636"
                        "link" => array:1 [
                          0 => array:2 [
                            "url" => "https://www.ncbi.nlm.nih.gov/pubmed/20351233"
                            "web" => "Medline"
                          ]
                        ]
                      ]
                    ]
                  ]
                ]
              ]
            ]
            1 => array:3 [
              "identificador" => "bib0085"
              "etiqueta" => "2"
              "referencia" => array:1 [
                0 => array:2 [
                  "contribucion" => array:1 [
                    0 => array:2 [
                      "titulo" => "Predicting disease recurrence in patients with previous unprovoked venous thromboembolism&#58; A proposed prediction score &#40;DASH&#41;"
                      "autores" => array:1 [
                        0 => array:2 [
                          "etal" => true
                          "autores" => array:6 [
                            0 => "A&#46; Tosetto"
                            1 => "A&#46; Iorio"
                            2 => "M&#46; Marcucci"
                            3 => "T&#46; Baglin"
                            4 => "M&#46; Cushman"
                            5 => "S&#46; Eichinger"
                          ]
                        ]
                      ]
                    ]
                  ]
                  "host" => array:1 [
                    0 => array:2 [
                      "doi" => "10.1111/j.1538-7836.2012.04735.x"
                      "Revista" => array:6 [
                        "tituloSerie" => "J Thromb Haemost"
                        "fecha" => "2012"
                        "volumen" => "10"
                        "paginaInicial" => "1019"
                        "paginaFinal" => "1025"
                        "link" => array:1 [
                          0 => array:2 [
                            "url" => "https://www.ncbi.nlm.nih.gov/pubmed/22489957"
                            "web" => "Medline"
                          ]
                        ]
                      ]
                    ]
                  ]
                ]
              ]
            ]
            2 => array:3 [
              "identificador" => "bib0090"
              "etiqueta" => "3"
              "referencia" => array:1 [
                0 => array:2 [
                  "contribucion" => array:1 [
                    0 => array:2 [
                      "titulo" => "Identifying unprovoked thromboembolism patients at low risk for recurrence who can discontinue anticoagulant therapy"
                      "autores" => array:1 [
                        0 => array:2 [
                          "etal" => true
                          "autores" => array:6 [
                            0 => "M&#46;A&#46; Rodger"
                            1 => "S&#46;R&#46; Kahn"
                            2 => "P&#46;S&#46; Wells"
                            3 => "D&#46;A&#46; Anderson"
                            4 => "I&#46; Chagnon"
                            5 => "G&#46; Le Gal"
                          ]
                        ]
                      ]
                    ]
                  ]
                  "host" => array:1 [
                    0 => array:2 [
                      "doi" => "10.1503/cmaj.080493"
                      "Revista" => array:6 [
                        "tituloSerie" => "CMAJ"
                        "fecha" => "2008"
                        "volumen" => "179"
                        "paginaInicial" => "417"
                        "paginaFinal" => "426"
                        "link" => array:1 [
                          0 => array:2 [
                            "url" => "https://www.ncbi.nlm.nih.gov/pubmed/18725614"
                            "web" => "Medline"
                          ]
                        ]
                      ]
                    ]
                  ]
                ]
              ]
            ]
            3 => array:3 [
              "identificador" => "bib0095"
              "etiqueta" => "4"
              "referencia" => array:1 [
                0 => array:2 [
                  "contribucion" => array:1 [
                    0 => array:2 [
                      "titulo" => "A risk score for prediction of recurrence in patients with unprovoked venous thromboembolism &#40;DAMOVES&#41;"
                      "autores" => array:1 [
                        0 => array:2 [
                          "etal" => true
                          "autores" => array:6 [
                            0 => "A&#46;I&#46; Franco Moreno"
                            1 => "M&#46;J&#46; Garc&#237;a Navarro"
                            2 => "J&#46; Ortiz S&#225;nchez"
                            3 => "R&#46;M&#46; Mart&#237;n D&#237;az"
                            4 => "E&#46; Madro&#241;al Cerezo"
                            5 => "C&#46;L&#46; de Ancos Aracil"
                          ]
                        ]
                      ]
                    ]
                  ]
                  "host" => array:1 [
                    0 => array:2 [
                      "doi" => "10.1016/j.ejim.2015.12.010"
                      "Revista" => array:6 [
                        "tituloSerie" => "Eur J Intern Med"
                        "fecha" => "2016"
                        "volumen" => "29"
                        "paginaInicial" => "59"
                        "paginaFinal" => "64"
                        "link" => array:1 [
                          0 => array:2 [
                            "url" => "https://www.ncbi.nlm.nih.gov/pubmed/26775136"
                            "web" => "Medline"
                          ]
                        ]
                      ]
                    ]
                  ]
                ]
              ]
            ]
            4 => array:3 [
              "identificador" => "bib0100"
              "etiqueta" => "5"
              "referencia" => array:1 [
                0 => array:2 [
                  "contribucion" => array:1 [
                    0 => array:2 [
                      "titulo" => "Risk of recurrence after a first unprovoked venous thromboembolism&#58; External validation of the Vienna Prediction Model with pooled individual patient data"
                      "autores" => array:1 [
                        0 => array:2 [
                          "etal" => true
                          "autores" => array:6 [
                            0 => "M&#46; Marcucci"
                            1 => "A&#46; Iorio"
                            2 => "J&#46;D&#46; Douketis"
                            3 => "S&#46; Eichinger"
                            4 => "A&#46; Tosetto"
                            5 => "T&#46; Baglin"
                          ]
                        ]
                      ]
                    ]
                  ]
                  "host" => array:1 [
                    0 => array:2 [
                      "doi" => "10.1111/jth.12871"
                      "Revista" => array:5 [
                        "tituloSerie" => "J Thromb Haemost"
                        "fecha" => "2015"
                        "volumen" => "13"
                        "paginaInicial" => "775"
                        "paginaFinal" => "781"
                      ]
                    ]
                  ]
                ]
              ]
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            5 => array:3 [
              "identificador" => "bib0105"
              "etiqueta" => "6"
              "referencia" => array:1 [
                0 => array:2 [
                  "contribucion" => array:1 [
                    0 => array:2 [
                      "titulo" => "Predicting recurrence after unprovoked venous thromboembolism&#58; Prospective validation of the updated Vienna Prediction Model"
                      "autores" => array:1 [
                        0 => array:2 [
                          "etal" => false
                          "autores" => array:5 [
                            0 => "T&#46; Tritschler"
                            1 => "M&#46; M&#233;an"
                            2 => "A&#46; Limacher"
                            3 => "N&#46; Rodondi"
                            4 => "D&#46; Aujesky"
                          ]
                        ]
                      ]
                    ]
                  ]
                  "host" => array:1 [
                    0 => array:2 [
                      "doi" => "10.1182/blood-2015-04-641225"
                      "Revista" => array:6 [
                        "tituloSerie" => "Blood"
                        "fecha" => "2015"
                        "volumen" => "126"
                        "paginaInicial" => "1949"
                        "paginaFinal" => "1951"
                        "link" => array:1 [
                          0 => array:2 [
                            "url" => "https://www.ncbi.nlm.nih.gov/pubmed/26341256"
                            "web" => "Medline"
                          ]
                        ]
                      ]
                    ]
                  ]
                ]
              ]
            ]
            6 => array:3 [
              "identificador" => "bib0110"
              "etiqueta" => "7"
              "referencia" => array:1 [
                0 => array:2 [
                  "contribucion" => array:1 [
                    0 => array:2 [
                      "titulo" => "Risk prediction of recurrent venous thrombosis&#59; where are we now and what can we add&#63;"
                      "autores" => array:1 [
                        0 => array:2 [
                          "etal" => false
                          "autores" => array:5 [
                            0 => "J&#46;F&#46; Timp"
                            1 => "W&#46;M&#46; Lijfering"
                            2 => "F&#46;R&#46; Rosendaal"
                            3 => "S&#46; le Cessie"
                            4 => "S&#46;C&#46; Cannegieter"
                          ]
                        ]
                      ]
                    ]
                  ]
                  "host" => array:1 [
                    0 => array:2 [
                      "doi" => "10.1111/jth.14535"
                      "Revista" => array:6 [
                        "tituloSerie" => "J Thromb Haemost"
                        "fecha" => "2019"
                        "volumen" => "17"
                        "paginaInicial" => "1527"
                        "paginaFinal" => "1534"
                        "link" => array:1 [
                          0 => array:2 [
                            "url" => "https://www.ncbi.nlm.nih.gov/pubmed/31188515"
                            "web" => "Medline"
                          ]
                        ]
                      ]
                    ]
                  ]
                ]
              ]
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