{"id":31052,"date":"2022-08-19T10:31:44","date_gmt":"2022-08-19T15:31:44","guid":{"rendered":"https:\/\/saluddigital.com\/?p=31052"},"modified":"2025-10-20T11:16:34","modified_gmt":"2025-10-20T17:16:34","slug":"aprendizaje-profundo-es-modelado-para-mejorar-la-identificacion-de-tumores-cerebrales","status":"publish","type":"post","link":"https:\/\/saluddigital.com\/en\/big-data\/aprendizaje-profundo-es-modelado-para-mejorar-la-identificacion-de-tumores-cerebrales\/","title":{"rendered":"Deep learning is modeled to improve identification of brain tumors"},"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

Researchers in China have developed a deep learning model that may improve brain tumor classification and diagnosis.<\/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

A study published in Jama Network entitled, \u201cDevelopment and validation of a deep learning model for brain tumor diagnosis and classification using magnetic resonance imaging\u201d, shows how this tool can be trained through standard MRI and improve the work of the radiologists.<\/p>

The initial premise of the research was to find out how deep learning can be used for the classification and diagnosis of brain tumors. The main objective of the study was precisely to develop and clinically validate a learning system that would automatically achieve the automated identification and classification of 18 types of brain tumors based on MRI data from patients.<\/p>

The diagnostic study was used using MRI data from 37,871, collected between 2000 and 2019. Likewise, the deep learning system for the segmentation of 18 types of intracranial tumors was based on T1 and T2 images weighted by MR.<\/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\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

\u201cThe diagnostic accuracy of the system was tested using one internal and three external independent data sets. The clinical value of the system was evaluated by comparing the tumor diagnostic accuracy of neuroradiologists assisted by the proposed system versus those without, using an independent internal test data set. The data was analyzed from March 2019 to February 2020\u201d, the authors explain in the study.<\/p>

The study findings showed that the model had better results than the neuroradiologists in the classification and identification of tumors, while the neuroradiologists had greater precision when they relied on the deep learning system.<\/p>

"These findings suggest that automated diagnosis based on a deep learning system may be associated with better classification and diagnosis of intracranial tumors from MRI data among neuroradiologists," the authors conclude.<\/p>

For more details see the full study at the following link: https:\/\/jamanetwork.com\/journals\/jamanetworkopen\/fullarticle\/2794975<\/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

\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\t BIBLIOGRAPHY<\/a>\n\t\t\t\t\t<\/div>\n\n\t\t\t\t\t

JAMA NETWORK<\/strong><\/p>

https:\/\/jamanetwork.com\/journals\/jamanetworkopen\/fullarticle\/2794975<\/a><\/p>

HEALTH IT ANALYTICS<\/strong><\/p>

https:\/\/healthitanalytics.com\/news\/deep-learning-may-improve-identification-of-brain-tumors<\/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":"

Investigadores en China desarrollaron un modelo de aprendizaje profundo que ser\u00eda capaz de mejorar la clasificaci\u00f3n de tumores cerebrales y su diagn\u00f3stico. Estudio publicado en Jama Network titulado, \u201cDesarrollo y validaci\u00f3n de un modelo de aprendizaje profundo para el diagn\u00f3stico y clasificaci\u00f3n de tumor de cerebro utilizando im\u00e1genes por resonancia magn\u00e9tica\u201d, muestra c\u00f3mo esta herramienta puede ser entrenada a trav\u00e9s de IRM est\u00e1ndar y mejorar el trabajo de los radi\u00f3logos. La premisa inicial de la investigaci\u00f3n fue conocer c\u00f3mo puede ser utilizado el aprendizaje profundo para la clasificaci\u00f3n y diagn\u00f3stico de tumores cerebrales. El objetivo principal del estudio fue precisamente desarrollar y validar cl\u00ednicamente un sistema de aprendizaje produjo que de manera automatizada lograra la identificaci\u00f3n y clasificaci\u00f3n automatizada de 18 tipos de tumores cerebrales basados en datos de IRM de pacientes. El estudio de diagn\u00f3stico fue utilizado utilizando datos de IRM de 37,871, recolectada entre el a\u00f1o 2000 y 2019. Asimismo, el sistema de aprendizaje profundo para la segmentaci\u00f3n de 18 tipos de tumores intracraneales fue basado en im\u00e1genes T1 y T2 ponderadas por RM. \u201cLa precisi\u00f3n diagn\u00f3stica del sistema se prob\u00f3 utilizando un conjunto de datos independientes internos y tres externos. El valor cl\u00ednico del sistema se evalu\u00f3 comparando la precisi\u00f3n diagn\u00f3stica de tumores de los neuro radi\u00f3logos con la asistencia del sistema propuesto frente a los que no la ten\u00edan, utilizando un conjunto de datos de prueba interno independiente. Los datos se analizaron desde marzo de 2019 hasta febrero de 2020\u201d, explican los autores en el estudio. Los hallazgos del estudio mostraron que el modelo tuvo mejores resultados que los neuro radi\u00f3logos en la clasificaci\u00f3n e identificaci\u00f3n de tumores, en cambio los neuro radi\u00f3logos tuvieron mayor precisi\u00f3n cuando se apoyaron en el sistema de aprendizaje profundo. \u201cEstos hallazgos sugieren que el diagn\u00f3stico automatizado basado en un sistema de aprendizaje profundo puede estar asociado con una mejor clasificaci\u00f3n y diagn\u00f3stico de tumores intracraneales a partir de datos de resonancia magn\u00e9tica entre los neuro radi\u00f3logos\u201d, concluyen los autores. Para conocer m\u00e1s detalles consulta el estudio completo en el siguiente enlace: https:\/\/jamanetwork.com\/journals\/jamanetworkopen\/fullarticle\/2794975 BIBLIOGRAF\u00cdA JAMA NETWORK https:\/\/jamanetwork.com\/journals\/jamanetworkopen\/fullarticle\/2794975 HEALTH IT ANALYTICS https:\/\/healthitanalytics.com\/news\/deep-learning-may-improve-identification-of-brain-tumors<\/p>","protected":false},"author":1,"featured_media":31053,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[156,3400,160],"tags":[145],"class_list":["post-31052","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-big-data","category-diagnostico","category-noticias","tag-noticias"],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/posts\/31052","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=31052"}],"version-history":[{"count":0,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/posts\/31052\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/media\/31053"}],"wp:attachment":[{"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/media?parent=31052"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/categories?post=31052"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/tags?post=31052"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}