{"id":11593,"date":"2020-12-22T09:31:24","date_gmt":"2020-12-22T15:31:24","guid":{"rendered":"https:\/\/saluddigital.com\/?p=11593"},"modified":"2025-10-21T14:02:33","modified_gmt":"2025-10-21T20:02:33","slug":"google-lanzo-herramienta-de-ia-para-organizar-textos-medicos","status":"publish","type":"post","link":"https:\/\/saluddigital.com\/en\/plataformas-digitales\/google-lanzo-herramienta-de-ia-para-organizar-textos-medicos\/","title":{"rendered":"Google launches Artificial Intelligence tool to organize medical texts"},"content":{"rendered":"
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t

Google Cloud introduced two tools based on Artificial Intelligence in its Cloud Healthcare library. Both tools are intended to support organizations dedicated to scientific research in health. <\/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
\n\t\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t

These tools based on Artificial Intelligence (AI) and automatic learning launched by Google Cloud present a way to reduce the work for data managers in health systems or hospitals. Google Cloud Healthcare, presented the preliminary versions of the APIs of these two tools. Healthcare Natural Language and the AutoML extraction model were published in the Google Cloud library. Both tools were designed to facilitate the tasks of organizations in the organization of medical information, since both facilitate text scanning and are capable of analyzing large amounts of unstructured text, i.e., data that is not in organized databases and is difficult to process.<\/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

\n\t\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\"\"\t\t\t\t\t\t\t\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
\n\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t

API Healthcare Natural Language, is capable of being implemented in health care organizations, and provides automatic learning techniques for obtaining statistics from medical text. One of the characteristics of this API is that it is a service independent of the Google Cloud Healthcare platform, which makes it easy to use. \"Natural Language's Healthcare API analyzes unstructured medical text, such as medical records or insurance claims. It then generates a structured data representation of the medical knowledge entities stored in these data sources for further analysis and automation,\" they mention in their description.<\/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

\n\t\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t\t\t

On the other hand, AutoML, is a tool for data extraction and training through automatic learning, for example, this system can be trained to obtain data or trends in medical records and thus make predictions. In his description of Google Cloud, they explain that the AutoML API is capable of making predictions on a single document or predictions in batches, in which the user sends a series of documents that the model analyzes asynchronously.<\/p>

The Healthcare Natural Language API was available free of charge to companies until December 10th. Auto ML and its Entity Extraction for Healthcare API is free for the first 5,000 text records and up to 1000 pages of documents.<\/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

\n\t\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t\t\t
\n\t\t\t\t\t
\n\t\t\t\t\t\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/i><\/span>\n\t\t\t\t\t\t\t\t<\/i><\/span>\n\t\t\t\t\t\t\t\t\t\t\t\t\t<\/span>\n\t\t\t\t\t\t\t\t\t\t\t\tBIBLIOGRAPHY<\/a>\n\t\t\t\t\t<\/div>\n\n\t\t\t\t\t

GOOGLE CLOUD<\/strong><\/p>

https:\/\/cloud.google.com\/healthcare\/docs\/how-tos\/nlp<\/a><\/p>

\u00a0<\/p>

https:\/\/cloud.google.com\/natural-language\/automl\/docs\/automl-healthcare<\/a><\/p>

\u00a0<\/p>

MOBIHEALTH NEWS<\/strong><\/p>

https:\/\/www.mobihealthnews.com\/news\/google-cloud-unveils-ai-tools-help-healthcare-analyze-unstructured-medical-text<\/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":"

Google Cloud present\u00f3 dos herramientas basadas en inteligencia Artificial en su biblioteca de Cloud Healthcare. Ambas herramientas tienen como prop\u00f3sito ser un apoyo para las organizaciones dedicadas a la investigaci\u00f3n cient\u00edfica en salud. Estas herramientas basadas en Inteligencia Artificial (AI) y aprendizaje autom\u00e1tico lanzadas por Google Cloud presentan una manera de reducir el trabajo para encargados de la gesti\u00f3n de datos en sistemas de salud u hospitales. Google Cloud Healthcare, present\u00f3 las versiones preliminares de las API de estas dos herramientas. Healthcare Natural Language y el modelo de extracci\u00f3n de AutoML fueron publicadas en la biblioteca de Google Cloud. Ambas herramientas fueron dise\u00f1adas para facilitar las tareas a organizaciones en la organizaci\u00f3n de informaci\u00f3n m\u00e9dica, ya que ambas facilitan el escaneo de texto y son capaces de analizar grandes cantidades de texto no estructurado, es decir datos que no se encuentran en bases organizadas y son dif\u00edciles de procesar. API Healthcare Natural Language, es capaz de implementarse en organizaciones de salud, y proporciona t\u00e9cnicas de aprendizaje autom\u00e1tico para la obtenci\u00f3n de estad\u00edsticas a partir de texto m\u00e9dico. Una de las caracter\u00edsticas de esta API, es que se trata de un servicio independiente de la plataforma de Google Cloud Healthcare, lo que facilita su uso. \u201cLa API de Healthcare de Natural Language analiza texto m\u00e9dico no estructurado, como registros m\u00e9dicos o afirmaciones de seguros. Luego, genera una representaci\u00f3n de datos estructurados de las entidades de conocimiento m\u00e9dico almacenadas en estas fuentes de datos para el an\u00e1lisis y la automatizaci\u00f3n posteriores\u201d, mencionan en su descripci\u00f3n. Por otra parte, AutoML, es una herramienta de extracci\u00f3n de datos y de entrenamiento a trav\u00e9s de aprendizaje autom\u00e1tico, por ejemplo, este sistema puede entrenarse para obtener datos o tendencias en registros m\u00e9dicos y as\u00ed realizar predicciones. En su descripci\u00f3n de Google Cloud, explica que la API de AutoML es capaz de realizar predicciones sobre un solo documento o predicciones por lotes, en las que el usuario env\u00eda una serie de documentos que el modelo analiza asincr\u00f3nicamente. La API de Healthcare Natural Language estuvo disponible de forma gratuita para empresas hasta el 10 de diciembre. Auto ML y su API de Entity Extraction for Healthcare es gratuita para los primeros 5 mil registros de texto y hasta mil p\u00e1ginas de documentos. BIBLIOGRAF\u00cdA GOOGLE CLOUD https:\/\/cloud.google.com\/healthcare\/docs\/how-tos\/nlp \u00a0 https:\/\/cloud.google.com\/natural-language\/automl\/docs\/automl-healthcare \u00a0 MOBIHEALTH NEWS https:\/\/www.mobihealthnews.com\/news\/google-cloud-unveils-ai-tools-help-healthcare-analyze-unstructured-medical-text<\/p>","protected":false},"author":1,"featured_media":11594,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[156,153],"tags":[145],"class_list":["post-11593","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-big-data","category-plataformas-digitales","tag-noticias"],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/posts\/11593","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=11593"}],"version-history":[{"count":0,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/posts\/11593\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/media\/11594"}],"wp:attachment":[{"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/media?parent=11593"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/categories?post=11593"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/tags?post=11593"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}