{"id":31044,"date":"2022-08-19T10:23:01","date_gmt":"2022-08-19T15:23:01","guid":{"rendered":"https:\/\/saluddigital.com\/?p=31044"},"modified":"2025-10-20T11:16:39","modified_gmt":"2025-10-20T17:16:39","slug":"nuevo-modelo-de-inteligencia-artificial-es-capaz-de-predecir-resultados-del-cancer","status":"publish","type":"post","link":"https:\/\/saluddigital.com\/en\/big-data\/nuevo-modelo-de-inteligencia-artificial-es-capaz-de-predecir-resultados-del-cancer\/","title":{"rendered":"New Artificial Intelligence model is capable of predicting cancer outcomes"},"content":{"rendered":"
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A study conducted by the Mahmood Laboratory at Brigham and Women's Hospital in Boston showed how Artificial Intelligence (AI) uses specific medical factors to anticipate possible cancer outcomes in patients.<\/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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Researchers at the Mahmood Lab developed a test model that incorporates genomic and histology data to make improved data-driven prognoses for cancer patients. The prediction of results in cancer patients needs to consider different factors about the patient's health, such as their medical history, genetic data, disease pathology, among others.<\/p>

The study, conducted at Brigham and Women's Hospital, shows a test model that uses AI to combine multiple data from different sources to predict patient outcomes for 14 different types of cancer.<\/p>

\u201cExperts look at many tests to predict how well a patient may do. These early exams become the basis for making decisions about enrollment in a clinical trial or specific treatment regimens. But that means that this multimodal prediction occurs at the expert level. We are trying to approach the problem computationally,\u201d Dr. Faisal Mahmood, an assistant professor in the Division of Computational Pathology at Brigham.<\/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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The AI models were built using The Cancer Genome Atlas (TCGA), a resource open to the public that has a database on multiple types of cancer. Subsequently, the researchers developed an algorithm based on multimodal deep learning that can interpret multiple data sources, such as those mentioned above, related to histology and genomics.<\/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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\u201cThis study highlights that it is feasible to use AI to integrate different types of clinically informed data to predict disease outcomes,\u201d explains the hospital. In this sense, the models could allow researchers to find biomarkers that take into account various clinical factors for the diagnosis of different types of cancer. In this way it will be possible to carry out larger studies that incorporate AI and data from multiple sources.<\/p>

"In a broader sense, our findings emphasize the need to build computational pathology prognostic models with much larger data sets and subsequent clinical trials to establish utility," concluded Mahmood.<\/p>

The results of the study were published in the scientific journal Cancer Cell, consult it at the following link: https:\/\/www.cell.com\/cancer-cell\/fulltext\/S1535-6108(22)00317-8<\/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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\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

BRIGHAM AND WOMEN'S HOSPITAL<\/strong><\/p>

https:\/\/www.brighamandwomens.org\/about-bwh\/newsroom\/research-briefs-detail?id=4227<\/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":"

Estudio realizado por el Laboratorio Mahmood del Brigham and Women’s Hospital en Boston, mostr\u00f3 como la Inteligencia Artificial (IA), utiliza factores m\u00e9dicos espec\u00edficos para anticipar posibles resultados del c\u00e1ncer en pacientes. Investigadores del Mahmood Lab, desarrollaron un modelo de prueba que incorpora datos gen\u00f3micos y de histolog\u00eda para realizar pron\u00f3sticos mejorados basados en datos a pacientes con c\u00e1ncer. La predicci\u00f3n de resultados en pacientes con c\u00e1ncer necesita considerar diferentes factores sobre la salud del paciente, como su historial m\u00e9dico, datos gen\u00e9ticos, patolog\u00eda de la enfermedad, entre otros. El estudio realizado en el Brigham and Women’s Hospital, muestra un modelo de prueba que utiliza IA para combinar m\u00faltiples datos de diferentes fuentes para predecir los resultados de pacientes para 14 tipos diferentes de c\u00e1ncer. \u201cLos expertos analizan muchas pruebas para predecir qu\u00e9 tan bien puede evolucionar un paciente. Estos primeros ex\u00e1menes se convierten en la base para tomar decisiones sobre la inscripci\u00f3n en un ensayo cl\u00ednico o reg\u00edmenes de tratamiento espec\u00edficos. Pero eso significa que esta predicci\u00f3n multimodal ocurre al nivel del experto. Estamos tratando de abordar el problema computacionalmente\u201d, Dr. Faisal Mahmood, profesor asistente en la Divisi\u00f3n de Patolog\u00eda Computacional en Brigham. Los modelos de IA fueron construidos utilizando The Cancer Genome Atlas (TCGA), un recurso abierto al p\u00fablico que cuenta con una base de datos sobre m\u00faltiples tipos de c\u00e1ncer. Posteriormente los investigadores desarrollaron un algoritmo basado en aprendizaje profundo multimodal que puede interpretar m\u00faltiples fuentes de datos, como los antes mencionados, relacionados con histolog\u00eda y gen\u00f3mica. \u201cEste estudio destaca que es factible usar IA para integrar diferentes tipos de datos cl\u00ednicamente informados para predecir los resultados de la enfermedad\u201d, explica el hospital. En este sentido, los modelos podr\u00edan permitir que investigadores encuentren biomarcadores que tomen en cuenta diversos factores cl\u00ednicos para el diagn\u00f3stico de diferentes tipos de c\u00e1ncer. De esta forma ser\u00e1 posible realizar estudios m\u00e1s amplios que incorporen IA y datos de m\u00faltiples fuentes. \u201cEn un sentido m\u00e1s amplio, nuestros hallazgos enfatizan la necesidad de construir modelos de pron\u00f3stico de patolog\u00eda computacional con conjuntos de datos mucho m\u00e1s grandes y ensayos cl\u00ednicos posteriores para establecer la utilidad\u201d, concluy\u00f3 Mahmood. Los resultados del estudio fueron publicados en la revista cient\u00edfica Cancer Cell, cons\u00faltalo en el siguiente enlace: https:\/\/www.cell.com\/cancer-cell\/fulltext\/S1535-6108(22)00317-8 BIBLIOGRAF\u00cdA BRIGHAM AND WOMEN\u2019S HOSPITAL https:\/\/www.brighamandwomens.org\/about-bwh\/newsroom\/research-briefs-detail?id=4227<\/p>","protected":false},"author":1,"featured_media":31046,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[156,3400,160],"tags":[145],"class_list":["post-31044","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\/31044","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=31044"}],"version-history":[{"count":0,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/posts\/31044\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/media\/31046"}],"wp:attachment":[{"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/media?parent=31044"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/categories?post=31044"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/tags?post=31044"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}