{"id":13350,"date":"2024-07-09T18:26:52","date_gmt":"2024-07-09T18:26:52","guid":{"rendered":"https:\/\/dailyai.com\/?p=13350"},"modified":"2024-07-09T18:35:05","modified_gmt":"2024-07-09T18:35:05","slug":"ai-breakthrough-rapidly-identifies-drug-resistant-typhoid-without-antibiotic-exposure","status":"publish","type":"post","link":"https:\/\/dailyai.com\/fr\/2024\/07\/ai-breakthrough-rapidly-identifies-drug-resistant-typhoid-without-antibiotic-exposure\/","title":{"rendered":"Une perc\u00e9e de l'IA permet d'identifier rapidement la typho\u00efde r\u00e9sistante aux m\u00e9dicaments sans exposition aux antibiotiques"},"content":{"rendered":"

Des chercheurs de l'universit\u00e9 de Cambridge ont mis l'IA au service de la lutte contre la r\u00e9sistance aux antibiotiques.\u00a0<\/strong><\/p>\n

L'\u00e9quipe de recherche, dirig\u00e9e par le professeur Stephen Baker, a cr\u00e9\u00e9 un outil d'apprentissage automatique utilisant uniquement des images de microscopie pour distinguer les bact\u00e9ries r\u00e9sistantes \u00e0 la ciprofloxacine (un antibiotique courant) de celles qui y sont sensibles.<\/span><\/p>\n

Cela pourrait r\u00e9duire consid\u00e9rablement le temps n\u00e9cessaire pour diagnostiquer la r\u00e9sistance aux antibiotiques, ce qui pourrait transformer la fa\u00e7on dont nous traitons les infections dangereuses comme la fi\u00e8vre typho\u00efde.<\/span><\/p>\n

Les <\/span>\u00e9tude<\/span><\/a>L'\u00e9tude, publi\u00e9e dans Nature Communications, porte sur Salmonella Typhimurium, une bact\u00e9rie qui provoque des maladies gastro-intestinales graves et peut entra\u00eener des maladies invasives potentiellement mortelles.\u00a0<\/span><\/p>\n

\"AI\"
La salmonelle est une bact\u00e9rie qui infecte g\u00e9n\u00e9ralement l'homme par le biais d'aliments contamin\u00e9s, et certaines souches ont acquis une r\u00e9sistance aux antibiotiques. Certaines souches ont acquis une r\u00e9sistance aux antibiotiques : Universit\u00e9 de Cambridge<\/a>.<\/figcaption><\/figure>\n

Le Dr Tuan-Anh Tran, l'un des principaux chercheurs du projet, a expliqu\u00e9 l'approche dans un communiqu\u00e9 de presse. <\/span>article de blog<\/span><\/a>: \"La beaut\u00e9 du mod\u00e8le d'apprentissage automatique est qu'il peut identifier les bact\u00e9ries r\u00e9sistantes sur la base de quelques caract\u00e9ristiques subtiles des images microscopiques que l'\u0153il humain ne peut pas d\u00e9tecter.\"<\/span><\/p>\n

Le processus de recherche a comport\u00e9 plusieurs \u00e9tapes cl\u00e9s :<\/span><\/p>\n

    \n
  1. Pr\u00e9paration de l'\u00e9chantillon bact\u00e9rien<\/strong>: L'\u00e9quipe a cultiv\u00e9 des \u00e9chantillons de S. Typhimurium dans des milieux nutritifs liquides, certains expos\u00e9s \u00e0 diff\u00e9rentes concentrations de ciprofloxacine et d'autres non.<\/span><\/li>\n
  2. Imagerie \u00e0 haut contenu<\/strong>: \u00c0 l'aide d'un microscope sophistiqu\u00e9, les chercheurs ont pris des photos d\u00e9taill\u00e9es des bact\u00e9ries \u00e0 plusieurs moments.<\/span><\/li>\n
  3. Analyse d'images<\/strong>: Un logiciel sp\u00e9cialis\u00e9 a extrait 65 caract\u00e9ristiques diff\u00e9rentes de chaque cellule bact\u00e9rienne, notamment la forme, la taille et l'interaction avec des colorants fluorescents.<\/span><\/li>\n
  4. D\u00e9veloppement de mod\u00e8les d'apprentissage automatique<\/strong>: Les chercheurs ont introduit ces donn\u00e9es dans divers algorithmes d'apprentissage automatique, en les entra\u00eenant \u00e0 reconna\u00eetre les sch\u00e9mas associ\u00e9s \u00e0 la r\u00e9sistance aux antibiotiques.<\/span><\/li>\n
  5. S\u00e9lection des caract\u00e9ristiques<\/strong>: L'\u00e9quipe a identifi\u00e9 les caract\u00e9ristiques les plus cruciales pour distinguer les bact\u00e9ries r\u00e9sistantes des bact\u00e9ries sensibles.<\/span><\/li>\n<\/ol>\n

    Les r\u00e9sultats de ce processus sont impressionnants. Le syst\u00e8me d'IA a correctement identifi\u00e9 les bact\u00e9ries r\u00e9sistantes aux antibiotiques dans environ 87% des cas.\u00a0<\/span><\/p>\n

    Plus important encore, les chercheurs ont constat\u00e9 que les bact\u00e9ries r\u00e9sistantes et sensibles pr\u00e9sentaient des sch\u00e9mas visuels distincts que l'IA pouvait d\u00e9tecter, m\u00eame lorsqu'elles n'avaient pas \u00e9t\u00e9 expos\u00e9es \u00e0 des antibiotiques.\u00a0<\/span><\/p>\n

    Cela sugg\u00e8re que la r\u00e9sistance aux antibiotiques modifie l'apparence des bact\u00e9ries de mani\u00e8re trop subtile pour l'homme, mais que l'IA peut d\u00e9tecter.<\/span><\/p>\n

    Les m\u00e9thodes actuelles n\u00e9cessitent g\u00e9n\u00e9ralement plusieurs jours de culture bact\u00e9rienne et de tests contre divers antimicrobiens. En revanche, la nouvelle m\u00e9thode bas\u00e9e sur l'IA pourrait fournir des r\u00e9sultats en quelques heures.\u00a0<\/span><\/p>\n

    Un diagnostic plus rapide permet aux m\u00e9decins de prescrire plus t\u00f4t les antibiotiques les plus efficaces, ce qui peut am\u00e9liorer les r\u00e9sultats pour les patients et r\u00e9duire la propagation des bact\u00e9ries r\u00e9sistantes.<\/p>\n

    \u00c0 l'avenir, l'\u00e9quipe de recherche souhaite \u00e9tendre son approche \u00e0 des \u00e9chantillons cliniques plus complexes, comme le sang ou l'urine, et les tester sur d'autres types de bact\u00e9ries et d'antibiotiques. Elle s'efforce \u00e9galement de rendre la technologie plus accessible aux h\u00f4pitaux et aux cliniques du monde entier.<\/span><\/p>\n

    Comme l'explique le professeur Baker : \"Ce qui serait vraiment important, en particulier dans un contexte clinique, ce serait de pouvoir pr\u00e9lever un \u00e9chantillon complexe - par exemple du sang, de l'urine ou des expectorations - et d'identifier la sensibilit\u00e9 et la r\u00e9sistance directement \u00e0 partir de cet \u00e9chantillon\".<\/p>\n

    \"Il s'agit d'un probl\u00e8me beaucoup plus complexe qui n'a pas encore \u00e9t\u00e9 r\u00e9solu, m\u00eame dans le domaine du diagnostic clinique en milieu hospitalier. Si nous pouvions trouver un moyen de le faire, nous pourrions r\u00e9duire le temps n\u00e9cessaire \u00e0 l'identification de la r\u00e9sistance aux m\u00e9dicaments, et ce \u00e0 un co\u00fbt bien moindre. Cela pourrait \u00eatre une v\u00e9ritable transformation\".<\/span><\/p>\n

    Le Dr Sushmita Sridhar a r\u00e9sum\u00e9 les impacts en d\u00e9clarant : \"\u00c9tant donn\u00e9 que cette approche utilise l'imagerie \u00e0 r\u00e9solution cellulaire unique, il ne s'agit pas encore d'une solution qui pourrait \u00eatre facilement d\u00e9ploy\u00e9e partout. Mais elle est tr\u00e8s prometteuse : en capturant seulement quelques param\u00e8tres sur la forme et la structure des bact\u00e9ries, elle peut nous donner suffisamment d'informations pour pr\u00e9dire la r\u00e9sistance aux m\u00e9dicaments avec une relative facilit\u00e9.\"<\/span><\/p>\n

    Alors que la r\u00e9sistance aux antibiotiques continue de repr\u00e9senter une menace croissante pour la sant\u00e9 mondiale, des approches innovantes telles que cette technique d'imagerie aliment\u00e9e par l'IA offrent un nouvel espoir.\u00a0<\/span><\/p>\n

    Cette d\u00e9marche s'inscrit dans une tendance plus large d'innovations bas\u00e9es sur l'IA dans le domaine de la recherche sur les antibiotiques. Au MIT, des chercheurs ont utilis\u00e9 des mod\u00e8les d'apprentissage profond pour d\u00e9couvrir un antibiotique. une classe d'antibiotiques enti\u00e8rement nouvelle<\/a>.<\/p>\n

    Dans le m\u00eame ordre d'id\u00e9es, une autre \u00e9quipe de scientifiques a annonc\u00e9 en mai de l'ann\u00e9e derni\u00e8re qu'elle avait utilis\u00e9 l'IA pour identifier un nouvel antibiotique<\/a> efficace contre les bact\u00e9ries r\u00e9sistantes aux m\u00e9dicaments.<\/p>\n

    L'IA permet une identification plus rapide et plus pr\u00e9cise des infections r\u00e9sistantes aux m\u00e9dicaments, ce qui ouvre la voie \u00e0 des traitements plus efficaces et \u00e0 de meilleurs r\u00e9sultats pour les patients.\u00a0<\/span><\/p>\n

    Les prochaines ann\u00e9es seront cruciales, car l'\u00e9quipe s'efforce de traduire les succ\u00e8s obtenus en laboratoire en applications cliniques r\u00e9elles.<\/span><\/p>","protected":false},"excerpt":{"rendered":"

    Des chercheurs de l'universit\u00e9 de Cambridge ont mis l'IA au service de la lutte contre la r\u00e9sistance aux antibiotiques. L'\u00e9quipe de recherche, dirig\u00e9e par le professeur Stephen Baker, a cr\u00e9\u00e9 un outil d'apprentissage automatique utilisant uniquement des images de microscopie pour distinguer les bact\u00e9ries r\u00e9sistantes \u00e0 la ciprofloxacine (un antibiotique courant) de celles qui y sont sensibles. Cela pourrait r\u00e9duire consid\u00e9rablement le temps n\u00e9cessaire pour diagnostiquer la r\u00e9sistance aux antibiotiques, ce qui pourrait transformer la fa\u00e7on dont nous traitons les infections dangereuses comme la fi\u00e8vre typho\u00efde. L'\u00e9tude, publi\u00e9e dans Nature Communications, a port\u00e9 sur Salmonella Typhimurium, une bact\u00e9rie qui provoque des maladies gastro-intestinales graves et peut entra\u00eener des maladies invasives potentiellement mortelles. Le Dr Tuan-Anh Tran, l'un des principaux chercheurs de l'\u00e9tude, s'est pench\u00e9 sur le cas de Salmonella Typhimurium.<\/p>","protected":false},"author":2,"featured_media":13352,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[88],"tags":[353,105],"class_list":["post-13350","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ethics","tag-biology","tag-machine-learning"],"yoast_head":"\nAI breakthrough rapidly identifies drug-resistant typhoid without antibiotic exposure | DailyAI<\/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:\/\/dailyai.com\/fr\/2024\/07\/ai-breakthrough-rapidly-identifies-drug-resistant-typhoid-without-antibiotic-exposure\/\" \/>\n<meta property=\"og:locale\" content=\"fr_FR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"AI breakthrough rapidly identifies drug-resistant typhoid without antibiotic exposure | DailyAI\" \/>\n<meta property=\"og:description\" content=\"Researchers at the University of Cambridge have harnessed AI in the fight against antibiotic resistance.\u00a0 The research team, led by Professor Stephen Baker, created a machine learning tool using only microscopy images to distinguish between bacteria resistant to ciprofloxacin (a common antibiotic) and those susceptible to it. This could dramatically reduce the time required for diagnosing antibiotic resistance, potentially transforming how we treat dangerous infections like typhoid fever. The study, published in Nature Communications, focused on Salmonella Typhimurium, a bacterium that causes severe gastrointestinal illness and can lead to life-threatening invasive disease.\u00a0 Dr. Tuan-Anh Tran, a key researcher on the\" \/>\n<meta property=\"og:url\" content=\"https:\/\/dailyai.com\/fr\/2024\/07\/ai-breakthrough-rapidly-identifies-drug-resistant-typhoid-without-antibiotic-exposure\/\" \/>\n<meta property=\"og:site_name\" content=\"DailyAI\" \/>\n<meta property=\"article:published_time\" content=\"2024-07-09T18:26:52+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2024-07-09T18:35:05+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/dailyai.com\/wp-content\/uploads\/2024\/07\/DALL\u00b7E-2024-07-09-19.25.37-A-high-tech-nightcore-themed-image-focusing-on-Salmonella-bacteria.-The-bacteria-should-be-prominently-displayed-with-a-background-infused-with-red.webp\" \/>\n\t<meta property=\"og:image:width\" content=\"1792\" \/>\n\t<meta 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