{"id":26753,"date":"2022-05-30T08:47:03","date_gmt":"2022-05-30T13:47:03","guid":{"rendered":"https:\/\/saluddigital.com\/?p=26753"},"modified":"2025-10-20T11:52:37","modified_gmt":"2025-10-20T17:52:37","slug":"algoritmo-de-inteligencia-artificial-puede-estimar-la-edad-gestacional-de-un-feto","status":"publish","type":"post","link":"https:\/\/saluddigital.com\/en\/big-data\/algoritmo-de-inteligencia-artificial-puede-estimar-la-edad-gestacional-de-un-feto\/","title":{"rendered":"Artificial Intelligence algorithm can estimate the gestational age of a fetus\ufffc\ufffc"},"content":{"rendered":"
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An Artificial Intelligence (AI) model was tested to estimate the gestational age of fetuses, with the aim of using the technology in environments with low technological resources to perform ultrasounds.<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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Ultrasounds are necessary to know the estimation of the gestational age of a fetus, and also to offer quality obstetric care. However, the high cost of the equipment limits its use only to technologically equipped environments, therefore, in remote or rural communities they have better access not only to the necessary equipment but also to trained sonographers.<\/p>

This study is part of the Fetal Age Machine Learning Initiative (FAMLI), which aims to develop technologies that expand access to obstetric ultrasound in technology-constrained settings.<\/p>

A study published in NEJM Evidence showed an AI model for estimating the age of fetuses in gestation. That study used 8,775 blinded ultrasound scans of 4,695 pregnant volunteers in North Carolina, USA, and Zambia, between September 2018 and June 2021.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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"We trained a neural network to estimate gestational age from the scans and, on three test data sets, we evaluated the performance of the AI model and biometrics against previously established gestational age," the study explains.<\/p>

Thanks to the ultrasound data, the model was able to estimate the gestational age of the fetuses with an accuracy similar to that of trained sonographers. "The results were consistent across geographic sites and were supported in a test group of women who conceived through IVF," the study explains.<\/p>

The research details the great room for improvement that exists in delivery of obstetric care in low- and middle-income countries. Therefore, the use of this type of technology is useful in improving medical care, not only in obstetrics but also in general medicine and other specialties.<\/p>

Check the full study at the following link:<\/p>

https:\/\/evidence.nejm.org\/doi\/full\/10.1056\/EVIDoa2100058<\/a><\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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EIVENCE NEJM<\/strong><\/p>

https:\/\/evidence.nejm.org\/doi\/full\/10.1056\/EVIDoa2100058<\/a><\/p><\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>","protected":false},"excerpt":{"rendered":"

Un modelo de Inteligencia Artificial (IA), fue probado para estimar la edad gestacional de fetos, con el objetivo de utilizar la tecnolog\u00eda en entornos con bajos recursos tecnol\u00f3gicos para realizar ultrasonidos. Los ultrasonidos son necesarios para conocer la estimaci\u00f3n de la edad gestacional de un feto, y tambi\u00e9n para ofrecer una atenci\u00f3n obst\u00e9trica de calidad. Sin embargo, el alto costo del equipo limita su uso solamente para entornos dotados tecnol\u00f3gicamente, por lo tanto, en comunidades alejadas o rurales tienen mejor acceso no solo al equipo necesario sino tambi\u00e9n a ecografistas capacitados. Este estudio forma parte de la Iniciativa de aprendizaje autom\u00e1tico de la edad fetal (FAMLI), que tiene como prop\u00f3sito desarrollar tecnolog\u00edas que ampl\u00eden el acceso a ultrasonidos obst\u00e9tricos en entornos con limitaciones tecnol\u00f3gicas. Un estudio publicado en NEJM Evidence, mostr\u00f3 un modelo de IA para la estimaci\u00f3n de la edad de fetos en gestaci\u00f3n. Dicho estudio utiliz\u00f3 8,775 barridos de ultrasonido a ciegas de 4,695 voluntarias embarazadas en Carolina del Norte, EE.UU. y Zambia, entre septiembre de 2018 y junio de 2021. \u201cEntrenamos una red neuronal para estimar la edad gestacional a partir de los barridos y, en tres conjuntos de datos de prueba, evaluamos el rendimiento del modelo de IA y la biometr\u00eda frente a la edad gestacional previamente establecida\u201d, explica el estudio. Gracias a los datos de ultrasonidos, el modelo logr\u00f3 estimar la edad gestacional de los fetos con una precisi\u00f3n similar a la de ecografistas capacitados. \u201cLos resultados fueron consistentes en todos los sitios geogr\u00e1ficos y fueron respaldados en un grupo de prueba de mujeres que concibieron por fecundaci\u00f3n in vitro\u201d, explica el estudio. La investigaci\u00f3n detalla el gran margen de mejora que existe en la prestaci\u00f3n de servicios en la atenci\u00f3n obst\u00e9trica en pa\u00edses de ingresos bajos y medios. Por ello el uso de este tipo de tecnolog\u00edas resulta \u00fatil en el mejoramiento de la atenci\u00f3n m\u00e9dica, no solo en obstetricia sino en medicina general, y otras especialidades. Consulta el estudio completo en el siguiente enlace: https:\/\/evidence.nejm.org\/doi\/full\/10.1056\/EVIDoa2100058 BIBLIOGRAF\u00cdA EIVENCE NEJM https:\/\/evidence.nejm.org\/doi\/full\/10.1056\/EVIDoa2100058<\/p>","protected":false},"author":1,"featured_media":26755,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3399,156,160],"tags":[145],"class_list":["post-26753","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai-analitica","category-big-data","category-noticias","tag-noticias"],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/posts\/26753","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/comments?post=26753"}],"version-history":[{"count":0,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/posts\/26753\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/media\/26755"}],"wp:attachment":[{"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/media?parent=26753"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/categories?post=26753"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/tags?post=26753"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}