{"id":12140,"date":"2021-01-25T11:03:12","date_gmt":"2021-01-25T17:03:12","guid":{"rendered":"https:\/\/saluddigital.com\/?p=12140"},"modified":"2025-10-21T13:07:20","modified_gmt":"2025-10-21T19:07:20","slug":"en-reino-unido-utilizan-inteligencia-artificial-para-predecir-evolucion-o-complicaciones-de-pacientes-de-covid-19","status":"publish","type":"post","link":"https:\/\/saluddigital.com\/en\/avance-de-la-ciencia\/en-reino-unido-utilizan-inteligencia-artificial-para-predecir-evolucion-o-complicaciones-de-pacientes-de-covid-19\/","title":{"rendered":"Artificial Intelligence used in UK to predict evolution or complications of COVID-19 patients"},"content":{"rendered":"
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The NHSX has a database gathered during the pandemic from more than 40,000 CT scans, as well as X-rays and MRI images obtained from more than 10,000 COVID-19 patients. This has made it possible to search for patterns or markers of disease in new 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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The application of Artificial Intelligence in COVID-19 patients has benefited in patients receiving faster treatment and reducing hospital stays. The NHSX, the UK's national health service unit responsible for the development and implementation of technology- and data-driven policies and practices, has built a database of more than 40,000 CT scans, X-rays, and MRI scans from 10,000 patients who suffered from COVID-19.<\/p>

The data collection gave rise to the National Chest Imaging Database (NCCID), \"is a centralised UK database containing X-Ray, CT and MRI images from hospital patients across the country. This is to support a better understanding of the COVID-19 virus and develop technology which will enable the best care for patients hospitalised with a severe infection,\" they explain on their official site.<\/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 data collection allows for faster evaluation of critically ill patients and emergency patients, as well as saving time for radiologists. The database is available to the scientific community through GitHub, with the aim of developing solutions that help reduce hospital occupancy and save lives.<\/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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AI has already been used to treat patients: \"It is vital we always search for new ways to improve care, especially as we fight the pandemic with the recovery beyond. This excellent work is testament to how technology can help to save lives in the UK,\" explained Matt Hancock, Secretary of State for Health and Social Care.<\/p>

Professionals at Addenbrooke's Hospital in Cambridge have begun to develop an algorithm based on the NCCID images, which seeks to compare visual patterns in the images with those of patients, and speed up the diagnostic process. In addition, it is a benefit to hospital resource management by predicting whether additional beds, oxygen tanks, or drugs will be needed.<\/p>

Dominic Cushnan, director of AI imaging at NHSX, explained the importance of developing AI-based techniques and the possibilities it gives for improving patient treatment: \"We are applying the power of artificial intelligence to quickly detect disease patterns and develop new treatments for patients. There is huge potential for patient care, whether through quicker analysis of chest images or better identification of abnormalities.\"<\/p>

In addition, researchers from University College London and the University of Bradford have developed studies and research on the application of AI thanks to the database built by the NHSX and the Royal Surrey NHS Foundation Trust.<\/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

HEALTH TECH DIGITAL <\/strong><\/p>

https:\/\/www.healthtechdigital.com\/coronavirus-patients-to-benefit-from-ai\/<\/a><\/p>

\u00a0<\/p>

NHSX<\/strong><\/p>

https:\/\/www.nhsx.nhs.uk\/covid-19-response\/data-and-covid-19\/national-covid-19-chest-imaging-database-nccid\/<\/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":"

EL NHSX cuenta con una base de datos recolectados durante la pandemia de m\u00e1s de 40 mil tomograf\u00edas computarizadas, as\u00ed como rayos x e im\u00e1genes por resonancia magn\u00e9tica de m\u00e1s de 10 mil pacientes de COVID-19. Lo que ha permitido buscar patrones o marcas de enfermedad en nuevos pacientes. La aplicaci\u00f3n de Inteligencia Artificial en pacientes de COVID-19, ha beneficiado en que los pacientes reciban un tratamiento m\u00e1s \u00e1gil y que se reduzca la estancia en el hospital. La NHSX, la unidad del servicio nacional de salud del Reino Unido encargada del desarrollo y aplicaci\u00f3n de pol\u00edticas y pr\u00e1cticas enfocadas en la tecnolog\u00eda y los datos, ha formado una base de datos de m\u00e1s de 40 mil tomograf\u00edas computarizadas, rayos x, im\u00e1genes por resonancia magn\u00e9tica, de 10 mil pacientes que padecieron COVID-19. La recolecci\u00f3n de datos dio origen a la base de datos nacional de im\u00e1genes de t\u00f3rax (NCCID), \u201cuna base de datos centralizada del Reino Unido que contiene im\u00e1genes de rayos X, tomograf\u00eda computarizada y resonancia magn\u00e9tica de pacientes de hospitales de todo el pa\u00eds\u201d. Cuyo objetivo es \u201capoyar una mejor comprensi\u00f3n del virus COVID-19 y desarrollar tecnolog\u00eda que permita la mejor atenci\u00f3n para los pacientes hospitalizados con una infecci\u00f3n grave\u201d, explican en su sitio oficial. La recolecci\u00f3n de datos permite una evaluaci\u00f3n m\u00e1s r\u00e1pida de pacientes graves y pacientes de urgencias, adem\u00e1s ahorra tiempo a radi\u00f3logos. La base de datos est\u00e1 a disposici\u00f3n de la comunidad cient\u00edfica a trav\u00e9s de GitHub, con el objetivo de desarrollar soluciones que ayuden a reducir la ocupaci\u00f3n hospitalaria y a salvas vidas. La IA ya ha sido utilizada para el tratamiento de pacientes: \u201cEs vital que siempre busquemos nuevas formas de mejorar la atenci\u00f3n, especialmente cuando luchamos contra la pandemia con la recuperaci\u00f3n m\u00e1s all\u00e1. Este excelente trabajo es testimonio de c\u00f3mo la tecnolog\u00eda puede ayudar a salvar vidas en el Reino Unido\u201d, explic\u00f3 Matt Hancock, Secretario de Estado de Salud y Atenci\u00f3n Social. Profesionales del Addenbrooke’s Hospital en Cambridge, han comenzado a desarrollar un algoritmo basado en las im\u00e1genes del NCCID, que busca compara patrones visuales en las im\u00e1genes, con las de los pacientes, y acelerar el proceso de diagn\u00f3stico. Adem\u00e1s, es un beneficio para la administraci\u00f3n de los recursos del hospital, al predecir si ser\u00e1 necesario contar con m\u00e1s camas, tanques de ox\u00edgeno o medicamentos. Dominic Cushnan, director de im\u00e1genes de IA en NHSX, explic\u00f3 la importancia del desarrollo de t\u00e9cnicas basadas en IA y las posibilidades que da para mejorar el tratamiento de los pacientes: \u201cEstamos aplicando el poder de la inteligencia artificial para detectar r\u00e1pidamente patrones de enfermedades y desarrollar nuevos tratamientos para los pacientes. Existe un gran potencial para la atenci\u00f3n del paciente, ya sea mediante un an\u00e1lisis m\u00e1s r\u00e1pido de las im\u00e1genes del t\u00f3rax o una mejor identificaci\u00f3n de las anomal\u00edas\u201d. Adem\u00e1s, investigadores del University College London y University of Bradford, han desarrollado estudios e investigaciones sobre la aplicaci\u00f3n de IA gracias a la base de datos construida por el NHSX y el Royal Surrey NHS Foundation Trust. BIBLIOGRAF\u00cdA HEALTH TECH DIGITAL https:\/\/www.healthtechdigital.com\/coronavirus-patients-to-benefit-from-ai\/ \u00a0 NHSX https:\/\/www.nhsx.nhs.uk\/covid-19-response\/data-and-covid-19\/national-covid-19-chest-imaging-database-nccid\/<\/p>","protected":false},"author":1,"featured_media":12141,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[152,156],"tags":[145],"class_list":["post-12140","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-avance-de-la-ciencia","category-big-data","tag-noticias"],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/posts\/12140","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=12140"}],"version-history":[{"count":0,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/posts\/12140\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/media\/12141"}],"wp:attachment":[{"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/media?parent=12140"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/categories?post=12140"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/saluddigital.com\/en\/wp-json\/wp\/v2\/tags?post=12140"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}