{"id":19587,"date":"2025-04-03T05:14:07","date_gmt":"2025-04-03T03:14:07","guid":{"rendered":"https:\/\/thesmartcityjournal.cibeles.net\/sin-categorizar\/gmv-disena-un-innovador-simulador-basado-en-inteligencia-artificial-para-diagnosticar-enfermedades-pulmonares-intersticiales\/"},"modified":"2025-04-03T05:14:56","modified_gmt":"2025-04-03T03:14:56","slug":"gmv-disena-un-innovador-simulador-basado-en-inteligencia-artificial-para-diagnosticar-enfermedades-pulmonares-intersticiales","status":"publish","type":"post","link":"https:\/\/www.thesmartcityjournal.com\/es\/healthtech\/gmv-disena-un-innovador-simulador-basado-en-inteligencia-artificial-para-diagnosticar-enfermedades-pulmonares-intersticiales","title":{"rendered":"GMV dise\u00f1a un innovador simulador basado en inteligencia artificial para diagnosticar enfermedades pulmonares intersticiales"},"content":{"rendered":"

Utilizar\u00e1 un an\u00e1lisis avanzado de im\u00e1genes de tomograf\u00eda computarizada (TAC), permitiendo a la IA identificar con precisi\u00f3n todos los patrones visibles en las radiograf\u00edas relacionados con las Enfermedades Pulmonares Intersticiales Difusas.<\/p>\n

Las enfermedades respiratorias se encuentran entre las principales causas de mortalidad y discapacidad a nivel mundial. Dentro de este grupo, destacan las enfermedades pulmonares intersticiales difusas (EPID), como la fibrosis pulmonar idiop\u00e1tica (FPI) o la sarcoidosis, que provocan una progresiva formaci\u00f3n de cicatrices en el tejido pulmonar, dificultando la capacidad respiratoria y el suministro adecuado de ox\u00edgeno al organismo.<\/p>\n

El diagn\u00f3stico de este tipo de patolog\u00edas no es sencillo, ya que las im\u00e1genes m\u00e9dicas suelen mostrar caracter\u00edsticas superpuestas entre distintas enfermedades, lo que dificulta su interpretaci\u00f3n. Por otro lado, una vez realizado el diagn\u00f3stico, actualmente no existen factores capaces de predecir la evoluci\u00f3n de la enfermedad, ni de su respuesta a los tratamientos. Este hecho es importante en este tipo de enfermedades cuya morbimortalidad es elevada, donde el tratamiento correcto ha demostrado enlentecer la enfermedad, pero el retraso diagn\u00f3stico, as\u00ed como el tratamiento sub\u00f3ptimo se asocia a peor pron\u00f3stico.<\/p>\n

Conscientes de esta realidad, la multinacional tecnol\u00f3gica GMV<\/a>, en colaboraci\u00f3n con el Hospital Universitario La Paz y la Universidad Complutense de Madrid, ha asumido el reto propuesto por el Centro para el Desarrollo Tecnol\u00f3gico y la Innovaci\u00f3n (CDTI): desarrollar un simulador basado en inteligencia artificial (IA) que permita conocer y anticipar la evoluci\u00f3n de las enfermedades pulmonares intersticiales.<\/p>\n

IA y deep learning, claves en el diagn\u00f3stico m\u00e9dico del futuro<\/h2>\n

Seg\u00fan la Organizaci\u00f3n Mundial de la Salud (OMS), el 80 % de las decisiones m\u00e9dicas se basan en pruebas radiol\u00f3gicas, lo que sit\u00faa a la imagen m\u00e9dica como una herramienta clave en el diagn\u00f3stico, seguimiento e incluso tratamiento de los pacientes. Sin embargo, la interpretaci\u00f3n de las im\u00e1genes en el caso de las EPID sigue siendo especialmente compleja.<\/p>\n

En este contexto, tecnolog\u00edas como la inteligencia artificial (IA) y, en concreto, el deep learning<\/i> (aprendizaje autom\u00e1tico profundo supervisado, inspirado en el funcionamiento del cerebro humano) se posicionan como aliadas fundamentales para los especialistas en diagn\u00f3stico por imagen.<\/p>\n

Carlos Illana, responsable de Producto de Secure e-Solutions en GMV, explica: \u00abPara el dise\u00f1o del planificador hemos empleado una combinaci\u00f3n de un conjunto de datos completo y depurado, y unas t\u00e9cnicas de aprendizaje profundo para obtener un elevado nivel de precisi\u00f3n, explicabilidad y control del sesgo. No obstante, ser\u00e1 en su validaci\u00f3n en un entorno cl\u00ednico real \u2014en este caso, el Hospital de Bellvitge\u2014 cuando podamos confirmar si existen desviaciones respecto a los resultados obtenidos en entornos de prueba\u00bb.<\/p>\n

Avances disruptivos en imagen m\u00e9dica<\/h2>\n

El simulador desarrollado por GMV utilizar\u00e1 un an\u00e1lisis avanzado de im\u00e1genes de tomograf\u00eda computarizada (TAC), lo que permitir\u00e1 a la inteligencia artificial identificar con precisi\u00f3n todos los patrones visibles en las radiograf\u00edas relacionados con las EPIDs. Tambi\u00e9n podr\u00e1 determinar cu\u00e1l es el patr\u00f3n principal y se\u00f1alar si se trata de una enfermedad fibr\u00f3tica o no.<\/p>\n

Adem\u00e1s de esto, uno de los elementos m\u00e1s innovadores del proyecto reside en la capacidad de la IA para predecir la evoluci\u00f3n de la enfermedad, integrando las im\u00e1genes m\u00e9dicas con pruebas funcionales respiratorias. Se espera que esta capacidad predictiva ayude a los especialistas a anticiparse a la progresi\u00f3n de la enfermedad y adaptar los tratamientos a las necesidades espec\u00edficas de cada paciente, mejorando significativamente su calidad de vida.<\/p>\n

M\u00e1s all\u00e1 de las enfermedades pulmonares, este proyecto sienta las bases para una integraci\u00f3n m\u00e1s amplia de la inteligencia artificial en otras \u00e1reas m\u00e9dicas, gracias a un enfoque multidisciplinar que re\u00fane a expertos en ingenier\u00eda biom\u00e9dica, radiolog\u00eda, neumolog\u00eda e IA.<\/p>\n","protected":false},"excerpt":{"rendered":"

Utilizar\u00e1 un an\u00e1lisis avanzado de im\u00e1genes de tomograf\u00eda computarizada (TAC), permitiendo a la IA identificar con precisi\u00f3n todos los patrones visibles en las radiograf\u00edas relacionados con las Enfermedades Pulmonares Intersticiales Difusas. Las enfermedades respiratorias se encuentran entre las principales causas de mortalidad y discapacidad a nivel mundial. Dentro de este grupo, destacan las enfermedades pulmonares\u2026<\/p>\n","protected":false},"author":2,"featured_media":19586,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_scj_primary_category_id":91,"_scj_featured":false,"_scj_featured_from":"","_scj_featured_until":"","_scj_featured_order":0,"_scj_visibility_class":"current","_scj_layout_family":"standard","_scj_article_style":"","_scj_display_overrides":[],"_scj_intro_image_id":19586,"_scj_intro_alt":"GMV dise\u00f1a un innovador simulador basado en inteligencia artificial para diagnosticar enfermedades pulmonares intersticiales","_scj_intro_caption":"","_scj_intro_class":"","_scj_intro_float":"","_scj_full_image_id":19586,"_scj_full_alt":"GMV dise\u00f1a un innovador simulador basado en inteligencia artificial para diagnosticar enfermedades pulmonares 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