{"id":13115,"date":"2020-06-10T15:17:37","date_gmt":"2020-06-10T13:17:37","guid":{"rendered":"https:\/\/idibell.cat\/?p=13115"},"modified":"2020-06-10T15:17:37","modified_gmt":"2020-06-10T13:17:37","slug":"intelligencia-artificial-aplicada-a-loncologia-clinica","status":"publish","type":"post","link":"https:\/\/idibell.cat\/2020\/06\/intelligencia-artificial-aplicada-a-loncologia-clinica\/","title":{"rendered":"Intel\u00b7lig\u00e8ncia artificial aplicada a l\u2019oncologia cl\u00ednica"},"content":{"rendered":"<p>ModGraProDep es un sistema innovador que, mitjan\u00e7ant la intel\u00b7lig\u00e8ncia artificial i el disseny de models probabil\u00edstics, millora la predicci\u00f3 d\u2019indicadors de superviv\u00e8ncia en malalts de c\u00e0ncer de mama. L\u2019estudi, publicat a la revista <a href=\"https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0933365719311595\"><em>Artificial Intelligence in Medicine<\/em><\/a>, ha estat dirigit per Ramon Cl\u00e8ries, professor del Departament de Ci\u00e8ncies Cl\u00edniques de la Facultat de Medicina i Ci\u00e8ncies de la Salut de la Universitat de Barcelona (UB), i membre l&#8217;Institut d&#8217;Investigaci\u00f3 Biom\u00e8dica de Bellvitge (IDIBELL).<\/p>\n<p>En nou treball ha estat desplegat per un ampli equip d\u2019experts en epidemiologia, oncologia i gesti\u00f3 de dades del Pla Director d\u2019Oncologia-IDIBELL, la Universitat de Barcelona (UB), la Universitat Polit\u00e8cnica de Catalunya (UPC), l\u2019Institut Catal\u00e0 d\u2019Oncologia (ICO), l\u2019Institut d\u2019Investigaci\u00f3 Biom\u00e8dica de Girona (IDIBGI), la Universitat de Girona (UdG), la Universitat d&#8217;Alacant (UA), el CIBER d\u2019Epidemiologia i Salut P\u00fablica (CIBERESP), l\u2019Institut de Salut Carlos III, l\u2019Hospital Universitari Sant Joan de Reus, el Servei d\u2019Oncologia M\u00e8dica del Hospital Josep Trueta de Girona, els Registres de C\u00e0ncer de Girona i Tarragona i l\u2019entitat MC Mutual.<\/p>\n<p>&nbsp;<\/p>\n<h3>Modelitzaci\u00f3 matem\u00e0tica: noves fronteres en la lluita contra el c\u00e0ncer<\/h3>\n<p>Predir la superviv\u00e8ncia dels malalts \u00e9s un element decisiu per avaluar futurs escenaris d\u2019evoluci\u00f3 en els pacients de c\u00e0ncer i valorar tractaments. No obstant aix\u00f2, sovint aquesta informaci\u00f3 s\u2019ha d\u2019estimar mitjan\u00e7ant models matem\u00e0tics at\u00e8s que no existeix una poblaci\u00f3 mostral suficient per calcular aquests indicadors cl\u00ednics de manera espec\u00edfica.<\/p>\n<p>Aquesta nova metodologia ModGraProDep (ModelingGraphicalProbabilistcDependencies) ha impulsat dos estudis coordinats per la professora Mireia Vilardell, del Departament de Gen\u00e8tica, Microbiologia i Estad\u00edstica de la Facultat de Biologia UB, i la investigadora Maria Bux\u00f3, de l\u2019IDIBGI. En el primer estudi, ModGraProDep permet simular una poblaci\u00f3 de pacients de c\u00e0ncer, a partir de una base de dades reals, per identificar possibles nous patrons i calcular indicadors (per exemple, la superviv\u00e8ncia de un pacient en funci\u00f3 de les seves caracter\u00edstiques). En el segon estudi, ModGraProDep \u00e9s capa\u00e7 de predir i assignar valors (de manera probabil\u00edstica) a variables de les quals no s\u2019havia pogut recollir informaci\u00f3.<\/p>\n<p>L\u2019equip cient\u00edfic tamb\u00e9 ha dissenyat una aplicaci\u00f3 web, de gran inter\u00e8s cl\u00ednic en l\u2019\u00e0mbit de l\u2019oncologia, que permet obtenir una predicci\u00f3, fins a un termini m\u00e0xim de vint anys, \u00a0d\u2019indicadors de superviv\u00e8ncia i risc de mortalitat per cada pacient.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>ModGraProDep es un sistema innovador que, mitjan\u00e7ant la intel\u00b7lig\u00e8ncia artificial i el disseny de models probabil\u00edstics, millora la predicci\u00f3 d\u2019indicadors de superviv\u00e8ncia en malalts de c\u00e0ncer de mama. L\u2019estudi, publicat a la revista Artificial Intelligence in Medicine, ha estat dirigit per Ramon Cl\u00e8ries, professor del Departament de Ci\u00e8ncies Cl\u00edniques de la Facultat de Medicina i [&hellip;]<\/p>\n","protected":false},"author":8,"featured_media":13118,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"default","ast-site-content-layout":"","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"default","adv-header-id-meta":"","stick-header-meta":"default","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""}},"footnotes":""},"categories":[1],"tags":[],"publishpress_future_action":{"enabled":false,"date":"2024-05-11 01:29:23","action":"change-status","newStatus":"draft","terms":[],"taxonomy":"category"},"_links":{"self":[{"href":"https:\/\/idibell.cat\/wp-json\/wp\/v2\/posts\/13115"}],"collection":[{"href":"https:\/\/idibell.cat\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/idibell.cat\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/idibell.cat\/wp-json\/wp\/v2\/users\/8"}],"replies":[{"embeddable":true,"href":"https:\/\/idibell.cat\/wp-json\/wp\/v2\/comments?post=13115"}],"version-history":[{"count":0,"href":"https:\/\/idibell.cat\/wp-json\/wp\/v2\/posts\/13115\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/idibell.cat\/wp-json\/wp\/v2\/media\/13118"}],"wp:attachment":[{"href":"https:\/\/idibell.cat\/wp-json\/wp\/v2\/media?parent=13115"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/idibell.cat\/wp-json\/wp\/v2\/categories?post=13115"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/idibell.cat\/wp-json\/wp\/v2\/tags?post=13115"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}