Palabras clave
Inteligencia artificial
Obstetricia
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Resumen
Objetivo: Analizar y sintetizar la evidencia científica disponible en la literatura sobre los métodos de inteligencia artificial (IA) en la predicción y diagnóstico tempranos de complicaciones en el embarazo. Métodos: Se trata de una revisión integrativa, realizada en las bases de datos EMBASE, PubMed, Scopus y Web of Science, utilizando los siguientes descriptores: “Artificial Intelligence”, “Machine Learning”, “Deep Learning”, “Pregnancy Complications”, “perinatal complications” y “Postpartum”. Se incluyeron estudios publicados entre 2019 y 2023 que utilizan métodos de IA para predecir complicaciones en el embarazo. Resultados: La muestra final consistió en 13 artículos, con una mayor concentración de publicaciones en los años 2019 y 2020. La mayoría de los estudios se realizaron en China, y los diseños de investigación predominantes fueron estudios de cohortes. Los modelos de IA utilizados demostraron eficacia en la predicción de complicaciones como preeclampsia, diabetes mellitus gestacional, parto prematuro e invasión placentaria, utilizando registros médicos electrónicos y otros biomarcadores. Consideraciones finales: Esta revisión evidencia el impacto significativo de los modelos de IA en la mejora de la predicción y diagnóstico de complicaciones en el embarazo. Los resultados subrayan la necesidad de integrar continuamente estas tecnologías en la práctica clínica obstétrica, así como de investigaciones futuras para validar y expandir su aplicabilidad en diferentes contextos clínicos.
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