{"id":1303,"date":"2024-10-14T22:57:10","date_gmt":"2024-10-14T20:57:10","guid":{"rendered":"https:\/\/rvh-synergie.org\/actualites\/lintegration-de-lapprentissage-automatique-aux-methodes-statistiques-ameliore-les-modeles-de-prevision-des-risques-de-maladie\/"},"modified":"2024-10-14T22:57:13","modified_gmt":"2024-10-14T20:57:13","slug":"lintegration-de-lapprentissage-automatique-aux-methodes-statistiques-ameliore-les-modeles-de-prevision-des-risques-de-maladie","status":"publish","type":"post","link":"https:\/\/rvh-synergie.org\/actualites\/lintegration-de-lapprentissage-automatique-aux-methodes-statistiques-ameliore-les-modeles-de-prevision-des-risques-de-maladie\/","title":{"rendered":"L&rsquo;int\u00e9gration de l&rsquo;apprentissage automatique aux m\u00e9thodes statistiques am\u00e9liore les mod\u00e8les de pr\u00e9vision des risques de maladie"},"content":{"rendered":"<div>\n<div class=\"article-gallery lightGallery\">\n<div data-thumb=\"https:\/\/scx1.b-cdn.net\/csz\/news\/tmb\/2024\/integrating-machine-le.jpg\" data-src=\"https:\/\/scx2.b-cdn.net\/gfx\/news\/hires\/2024\/integrating-machine-le.jpg\" data-sub-html=\"Scientists from Peking University conducted a systematic review of studies on integrating machine learning into statistical methods in disease prediction models. Credit: Feng Sun, Peking University\">\n<figure class=\"article-img\">\n<\/figure><\/div>\n<\/div>\n<p>Des chercheurs de l&rsquo;Universit\u00e9 de P\u00e9kin ont men\u00e9 une \u00e9tude syst\u00e9matique compl\u00e8te sur l&rsquo;int\u00e9gration de l&rsquo;apprentissage automatique dans les m\u00e9thodes statistiques pour les mod\u00e8les de pr\u00e9vision des risques de maladie, mettant en lumi\u00e8re le potentiel de tels mod\u00e8les int\u00e9gr\u00e9s dans les pratiques de diagnostic clinique et de d\u00e9pistage. L&rsquo;\u00e9tude, dirig\u00e9e par le professeur Feng Sun du D\u00e9partement d&rsquo;\u00e9pid\u00e9miologie et de biostatistique de l&rsquo;\u00c9cole de sant\u00e9 publique de l&rsquo;Universit\u00e9 de P\u00e9kin, a \u00e9t\u00e9 publi\u00e9e dans <i>Science des donn\u00e9es de sant\u00e9<\/i>.<\/p>\n<p>La pr\u00e9vision du risque de maladie est cruciale pour un diagnostic pr\u00e9coce et une prise de d\u00e9cision clinique efficace. Cependant, les mod\u00e8les statistiques traditionnels, tels que la r\u00e9gression logistique et la r\u00e9gression \u00e0 risques proportionnels de Cox, se heurtent souvent \u00e0 des limites dues \u00e0 des hypoth\u00e8ses sous-jacentes qui ne sont pas toujours valables dans la pratique.<\/p>\n<p>Parall\u00e8lement, les m\u00e9thodes d\u2019apprentissage automatique, malgr\u00e9 leur flexibilit\u00e9 et leur capacit\u00e9 \u00e0 g\u00e9rer des donn\u00e9es complexes et non structur\u00e9es, n\u2019ont pas toujours d\u00e9montr\u00e9 des performances sup\u00e9rieures par rapport aux mod\u00e8les traditionnels dans certains sc\u00e9narios. Pour relever ces d\u00e9fis, l\u2019int\u00e9gration de l\u2019apprentissage automatique aux m\u00e9thodes statistiques traditionnelles peut offrir des mod\u00e8les de pr\u00e9diction plus robustes et plus pr\u00e9cis.<\/p>\n<p>L&rsquo;examen syst\u00e9matique a analys\u00e9 diverses strat\u00e9gies d&rsquo;int\u00e9gration pour les mod\u00e8les de classification et de r\u00e9gression, notamment le vote majoritaire, le vote pond\u00e9r\u00e9, l&#8217;empilement et la s\u00e9lection de mod\u00e8les, selon que les pr\u00e9dictions des m\u00e9thodes statistiques et de l&rsquo;apprentissage automatique \u00e9taient en d\u00e9saccord. L\u2019\u00e9tude a r\u00e9v\u00e9l\u00e9 que les mod\u00e8les d\u2019int\u00e9gration surpassaient g\u00e9n\u00e9ralement les m\u00e9thodes statistiques et d\u2019apprentissage automatique lorsqu\u2019ils \u00e9taient utilis\u00e9s seuls. Par exemple, l\u2019empilement s\u2019est av\u00e9r\u00e9 particuli\u00e8rement efficace pour les mod\u00e8les impliquant plus de 100 pr\u00e9dicteurs, car il permet de combiner les points forts de diff\u00e9rents mod\u00e8les tout en minimisant les faiblesses.<\/p>\n<p>\u00ab\u00a0Nos r\u00e9sultats sugg\u00e8rent que l&rsquo;int\u00e9gration de l&rsquo;apprentissage automatique dans les m\u00e9thodes statistiques traditionnelles peut fournir des mod\u00e8les plus pr\u00e9cis et g\u00e9n\u00e9ralisables pour la pr\u00e9vision des risques de maladie\u00a0\u00bb, a d\u00e9clar\u00e9 le professeur Feng Sun, chercheur principal. \u00ab\u00a0Cette approche a le potentiel d&rsquo;am\u00e9liorer la prise de d\u00e9cision clinique et d&rsquo;am\u00e9liorer les r\u00e9sultats pour les patients.\u00a0\u00bb<\/p>\n<p>Pour l\u2019avenir, l\u2019\u00e9quipe de recherche pr\u00e9voit de valider et d\u2019am\u00e9liorer davantage les m\u00e9thodes d\u2019int\u00e9gration existantes et de d\u00e9velopper des outils complets pour \u00e9valuer ces mod\u00e8les dans divers contextes cliniques. L\u2019objectif ultime est d\u2019\u00e9tablir des mod\u00e8les d\u2019int\u00e9gration plus efficaces et g\u00e9n\u00e9ralisables, adapt\u00e9s \u00e0 diff\u00e9rents sc\u00e9narios, faisant ainsi progresser les pratiques de diagnostic clinique et de d\u00e9pistage.<\/p>\n<p>\t\t\t\t\t\t\t\t\t\t\t\tFourni par Science des donn\u00e9es sur la sant\u00e9<\/p>\n<p>                                        <!-- print only --><\/p><\/div>\n","protected":false},"excerpt":{"rendered":"<p>Des chercheurs de l&rsquo;Universit\u00e9 de P\u00e9kin ont men\u00e9 une \u00e9tude syst\u00e9matique compl\u00e8te sur l&rsquo;int\u00e9gration de<\/p>\n","protected":false},"author":1,"featured_media":1304,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[86],"tags":[1378,1652,171,16,1651,49,1650,248,553,1275,1654,397,1653],"class_list":["post-1303","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-les-maladies","tag-ameliore","tag-automatique","tag-aux","tag-des","tag-lapprentissage","tag-les","tag-lintegration","tag-maladie","tag-methodes","tag-modeles","tag-prevision","tag-risques","tag-statistiques","generate-columns","tablet-grid-50","mobile-grid-100","grid-parent","grid-50","resize-featured-image"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v23.4 - 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