{"id":6230,"date":"2025-05-03T10:55:48","date_gmt":"2025-05-03T08:55:48","guid":{"rendered":"https:\/\/rvh-synergie.org\/actualites\/les-chercheurs-developpent-une-boite-a-outils-de-lia-explicable-pour-predire-la-maladie-avant-lapparition-des-symptomes\/"},"modified":"2025-05-03T10:55:53","modified_gmt":"2025-05-03T08:55:53","slug":"les-chercheurs-developpent-une-boite-a-outils-de-lia-explicable-pour-predire-la-maladie-avant-lapparition-des-symptomes","status":"publish","type":"post","link":"https:\/\/rvh-synergie.org\/actualites\/les-chercheurs-developpent-une-boite-a-outils-de-lia-explicable-pour-predire-la-maladie-avant-lapparition-des-symptomes\/","title":{"rendered":"Les chercheurs d\u00e9veloppent une bo\u00eete \u00e0 outils de l’IA explicable pour pr\u00e9dire la maladie avant l’apparition des sympt\u00f4mes"},"content":{"rendered":"
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Des chercheurs du D\u00e9partement de psychiatrie de l’Universit\u00e9 de l’Utah et du Huntsman Mental Health Institute ont publi\u00e9 un article dans Motifs<\/i> Introduction de RiskPath, une bo\u00eete \u00e0 outils logiciels open source qui utilise l’intelligence artificielle explicable (XAI) pour pr\u00e9dire si les individus d\u00e9velopperont des maladies progressives et chroniques des ann\u00e9es avant la pr\u00e9sence des sympt\u00f4mes, transformant potentiellement la fa\u00e7on dont les soins de sant\u00e9 pr\u00e9ventifs sont dispens\u00e9s.<\/p>\n

XAI est un syst\u00e8me d’intelligence artificielle qui peut expliquer les d\u00e9cisions complexes d’une mani\u00e8re que les humains peuvent comprendre.<\/p>\n

La nouvelle technologie repr\u00e9sente une progression significative de la pr\u00e9diction et de la pr\u00e9vention des maladies en analysant les mod\u00e8les de donn\u00e9es de sant\u00e9 collect\u00e9es sur plusieurs ann\u00e9es pour identifier les personnes \u00e0 risque avec une pr\u00e9cision sans pr\u00e9c\u00e9dent de 85 \u00e0 99%.<\/p>\n

Les syst\u00e8mes de pr\u00e9diction m\u00e9dicale actuels pour les donn\u00e9es longitudinales manquent souvent la marque, identifiant correctement les patients \u00e0 risque seulement environ de la moiti\u00e9 aux trois quarts du temps.<\/p>\n

Contrairement aux syst\u00e8mes de pr\u00e9diction existants pour les donn\u00e9es longitudinales, RiskPath utilise des algorithmes AI de s\u00e9ries chronologiques avanc\u00e9es et les rend explicables afin de fournir des mod\u00e8les complets qui fournissent des informations cruciales sur la fa\u00e7on dont les facteurs de risque interagissent et changent d’importance tout au long du processus de d\u00e9veloppement de la maladie.<\/p>\n

\u00ab\u00a0Les maladies chroniques et progressives repr\u00e9sentent plus de 90% des co\u00fbts et de la mortalit\u00e9 des soins de sant\u00e9\u00a0\u00bb, explique Nina de Lacy, MBA, MD, professeur adjoint de psychiatrie \u00e0 l’Universit\u00e9 de l’Utah Health et premier auteur de l’\u00e9tude.<\/p>\n

Elle ajoute: \u00ab\u00a0En identifiant les individus \u00e0 haut risque avant que les sympt\u00f4mes n’apparaissent ou au d\u00e9but de l’\u00e9volution de la maladie et que les facteurs de risque importent le plus \u00e0 diff\u00e9rents stades de vie, nous pouvons d\u00e9velopper des strat\u00e9gies pr\u00e9ventives plus cibl\u00e9es et efficaces. Les soins de sant\u00e9 pr\u00e9ventifs sont peut-\u00eatre l’aspect le plus important des soins de sant\u00e9 en ce moment, plut\u00f4t que de traiter les probl\u00e8mes apr\u00e8s qu’ils se mat\u00e9rialisent.\u00a0\u00bb<\/p>\n

L’\u00e9quipe de recherche a valid\u00e9 RiskPath dans trois grandes cohortes de patients \u00e0 long terme impliquant des milliers de participants pour pr\u00e9dire avec succ\u00e8s huit conditions diff\u00e9rentes, notamment la d\u00e9pression, l’anxi\u00e9t\u00e9, le TDAH, l’hypertension et le syndrome m\u00e9tabolique. Ils disent que la technologie offre plusieurs avantages cl\u00e9s:<\/p>\n

    \n
  • Compr\u00e9hension am\u00e9lior\u00e9e de la progression de la maladie: RiskPath peut cartographier comment diff\u00e9rents facteurs de risque changent dans l’importance au fil du temps, r\u00e9v\u00e9lant des fen\u00eatres critiques pour l’intervention. Par exemple, l’\u00e9tude a montr\u00e9 comment le temps d’\u00e9cran et la fonction ex\u00e9cutive sont devenus des contributeurs de risques de plus en plus importants pour le TDAH \u00e0 l’approche de l’adolescence.<\/li>\n
  • \u00c9valuation des risques rationalis\u00e9e: Bien que RiskPath puisse analyser des centaines de variables de sant\u00e9, les chercheurs ont constat\u00e9 que la plupart des conditions peuvent \u00eatre pr\u00e9dites avec une pr\u00e9cision similaire en utilisant seulement 10 facteurs cl\u00e9s, ce qui rend la mise en \u0153uvre plus r\u00e9alisable en milieu clinique.<\/li>\n
  • Visualisation pratique des risques: Le syst\u00e8me fournit des visualisations intuitives montrant quelles p\u00e9riodes dans la vie d’une personne contribuent le plus au risque de maladie, aidant les chercheurs \u00e0 identifier les temps optimaux pour les interventions pr\u00e9ventives.<\/li>\n<\/ul>\n

    L’\u00e9quipe de recherche explore maintenant comment RiskPath pourrait \u00eatre int\u00e9gr\u00e9 aux syst\u00e8mes de soutien \u00e0 la d\u00e9cision clinique, aux programmes de soins pr\u00e9ventifs et aux fondements neuronaux de la maladie mentale. Ils pr\u00e9voient d’\u00e9tendre leurs recherches pour inclure des maladies suppl\u00e9mentaires et diverses populations.<\/p>\n

    <\/p><\/div>\n","protected":false},"excerpt":{"rendered":"

    Des chercheurs du D\u00e9partement de psychiatrie de l’Universit\u00e9 de l’Utah et du Huntsman Mental Health<\/p>\n","protected":false},"author":1,"featured_media":6231,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[86],"tags":[37,2038,288,16,620,5150,4048,49,363,248,1330,8,799,42,47],"class_list":["post-6230","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-les-maladies","tag-avant","tag-boite","tag-chercheurs","tag-des","tag-developpent","tag-explicable","tag-lapparition","tag-les","tag-lia","tag-maladie","tag-outils","tag-pour","tag-predire","tag-symptomes","tag-une","generate-columns","tablet-grid-50","mobile-grid-100","grid-parent","grid-50","resize-featured-image"],"yoast_head":"\nLes chercheurs d\u00e9veloppent une bo\u00eete \u00e0 outils de l'IA explicable pour pr\u00e9dire la maladie avant l'apparition des sympt\u00f4mes - RVH-Synergie.org<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/rvh-synergie.org\/actualites\/les-chercheurs-developpent-une-boite-a-outils-de-lia-explicable-pour-predire-la-maladie-avant-lapparition-des-symptomes\/\" \/>\n<meta property=\"og:locale\" content=\"fr_FR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Les chercheurs d\u00e9veloppent une bo\u00eete \u00e0 outils de l'IA explicable pour pr\u00e9dire la maladie avant l'apparition des sympt\u00f4mes - 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