{"id":2301,"date":"2023-05-16T22:25:58","date_gmt":"2023-05-16T22:25:58","guid":{"rendered":"https:\/\/lp.stitcloud.com\/?p=2301"},"modified":"2025-07-12T11:29:28","modified_gmt":"2025-07-12T11:29:28","slug":"estudo-de-caso-st-it-cloud-machine-learning-assertivo","status":"publish","type":"post","link":"https:\/\/www.stitcloud.com\/es\/blog\/estudo-de-caso-st-it-cloud-machine-learning-assertivo\/","title":{"rendered":"Estudio de caso de ST IT CLOUD: aprendizaje autom\u00e1tico asertivo"},"content":{"rendered":"

Estudio de caso de ST IT CLOUD: aprendizaje autom\u00e1tico asertivo\u00a0<\/h3>\n\n

\u00a0 \u00a0 \u00a0En este art\u00edculo vamos a hablar del caso de estudio del segmento salud, siendo su principal desaf\u00edo el procesamiento de un gran volumen de clientes, lo que provoca cuellos de botella de alta complejidad, en lo que se refiere a la auditor\u00eda m\u00e9dica en autorizaciones de ex\u00e1menes y procedimientos. El trabajo de ST IT Cloud, fue a trav\u00e9s de Data Lake y Machine Learning, para desarrollar un sistema que funcionara de forma orquestada y econ\u00f3mica.\u00a0<\/p>\n\n

\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 EL DESAF\u00cdO ST IT\u00a0<\/strong><\/p>\n\n

\u00a0 \u00a0 \u00a0 \u00a0 \u00a0Como se mencion\u00f3 anteriormente, el procesamiento de informaci\u00f3n dentro de Unimed \u2013 BH se estaba volviendo extremadamente complejo, cuando se trataba de aprobar ex\u00e1menes m\u00e9dicos y autorizar Gu\u00edas. Con eso, el superintendente de TI, Ezequiel Ribeiro da Silva, explica que actualmente se generan m\u00e1s de 180 mil solicitudes de tr\u00e1mites por mes. \u201cAlrededor de 145.000 de estas solicitudes ya son manejadas por los sistemas Unimed-BH a trav\u00e9s de reglas fijas. Sin embargo, hay 35.000 solicitudes mensuales que se env\u00edan a los m\u00e9dicos auditores, cuyo papel es evaluar estas solicitudes caso por caso\u201d, dice.<\/p>\n\n

\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 Con esto, se vieron tres puntos principales como necesarios para automatizar el proceso, \u00e9chale un vistazo:<\/p>\n\n

    \n
  1. Disminuir gastos con auditor\u00eda m\u00e9dica en solicitudes de ex\u00e1menes y tr\u00e1mites\u00a0<\/li>\n\n
  2. Haga que las evaluaciones para aprobaci\u00f3n y auditor\u00eda sean m\u00e1s efectivas<\/li>\n\n
  3. Agilice el proceso de aprobaci\u00f3n del examen<\/li>\n<\/ol>\n\n

    \u00a0 \u00a0 \u00a0 CONOZCA LAS SOLUCIONES ST IT\u00a0<\/strong><\/p>\n\n

    \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 Elaboraci\u00f3n de la Arquitectura y desarrollo de un sistema que fuera capaz de cargar datos y archivos, estructurados y semiestructurados, transaccionales e hist\u00f3ricos en un Data Lake de forma Orquestada y Econ\u00f3mica.<\/p>\n\n

    \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 Adem\u00e1s, tambi\u00e9n se llev\u00f3 a cabo el desarrollo de un modelo de Machine Learning lo suficientemente asertivo como para autorizar autom\u00e1ticamente ex\u00e1menes y procedimientos m\u00e9dicos, validaci\u00f3n, visualizaci\u00f3n de informaci\u00f3n y alertas en Tiempo Casi Real.<\/p>\n

    \u201cLa soluci\u00f3n actual es el resultado de varios experimentos y dise\u00f1os de diferentes arquitecturas en diferentes pilotos. La flexibilidad de utilizar diferentes servicios disponibles en AWS, con el sistema de facturaci\u00f3n por asignaci\u00f3n, permiti\u00f3 a Unimed-BH experimentar con varios escenarios antes de llegar al m\u00e1s adecuado\u201d, revela Silva para AWS.\u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0 \u00a0\u00a0<\/p>\n\n

    \"\"<\/p>\n\n

    \u00a0<\/p>\n

    Actualmente, el proyecto est\u00e1 teniendo buenos resultados, con m\u00e1s agilidad en los procesos con un 40% m\u00e1s r\u00e1pido y tenemos la intenci\u00f3n de mejorar a 60% a medida que el modelo madure, \u00a1mejorando a\u00fan m\u00e1s la experiencia y los resultados!\u00a0<\/p>\n\n

    Si tu empresa tiene un reto de datos, innovaci\u00f3n o migraci\u00f3n a la Nube, contacta a nuestros expertos.<\/p>\n\n

    Confira o case na integra acesse: Case AWS\u00a0<\/a><\/p>","protected":false},"excerpt":{"rendered":"

    Estudo de caso ST IT CLOUD: Machine Learning Assertivo\u00a0 \u00a0 \u00a0 \u00a0Neste artigo, vamos falar sobre o estudo de caso do segmento de sa\u00fade, sendo o seu principal desafio, o processamento de um grande volume de clientes, o que ocasiona gargalos de alta complexibilidade, no que se refere a auditoria m\u00e9dica nas autoriza\u00e7\u00f5es de exames […]<\/p>","protected":false},"author":2,"featured_media":2302,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[21],"tags":[],"class_list":["post-2301","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-machine-learning"],"yoast_head":"\nEstudo de caso ST IT CLOUD: Machine Learning Assertivo<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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