{"id":1106,"date":"2019-12-27T10:26:48","date_gmt":"2019-12-27T09:26:48","guid":{"rendered":"http:\/\/www.bordeaux-population-health.center\/prosit-project-the-medicines-and-erias-teams-laureates-of-the-research-call-preps-2019\/"},"modified":"2019-12-27T10:26:48","modified_gmt":"2019-12-27T09:26:48","slug":"prosit-project-the-medicines-and-erias-teams-laureates-of-the-research-call-preps-2019","status":"publish","type":"post","link":"https:\/\/www.bordeaux-population-health.center\/fr\/prosit-project-the-medicines-and-erias-teams-laureates-of-the-research-call-preps-2019\/","title":{"rendered":"PROSIT project: The Medicines and ERIAS teams laureates of the Research Call PREPS 2019"},"content":{"rendered":"<p>The <strong>PROSIT project<\/strong> coordinated by the BPH <a href=\"https:\/\/www.bordeaux-population-health.center\/en\/teams\/pharmacoepidemiology-and-population-impact-of-drugs\/\">Pharmacoepi team<\/a> was selected as part of the <strong>2019 DGOS-PREPS Research Call<\/strong>. Using machine learning and text mining methods, the objective of this project is first to identify and analyze potential drug interactions from hospital discharge medical prescriptions. Second, it will assess the impact of using a tool developed from these techniques to reduce this risk of interactions. This project, which consortiates the teaching hospitals of Bordeaux, Rennes and Paris HEGP will be conducted in partnership with the <a href=\"https:\/\/synapse-medicine.com\/index.html\" target=\"_blank\" rel=\"noopener noreferrer\">start-up Synapse Medicine<\/a>.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>The PROSIT project coordinated by the BPH Pharmacoepi team was selected as part of the 2019 DGOS-PREPS Research Call. Using machine learning and text mining methods, the objective of this project is first to identify and analyze potential drug interactions from hospital discharge medical prescriptions. Second, it will assess the impact of using a tool [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[24],"tags":[],"class_list":["post-1106","post","type-post","status-publish","format-standard","hentry","category-actualites-du-centre"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.4 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>PROSIT project: The Medicines and ERIAS teams laureates of the Research Call PREPS 2019 | Bordeaux population health<\/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:\/\/www.bordeaux-population-health.center\/fr\/prosit-project-the-medicines-and-erias-teams-laureates-of-the-research-call-preps-2019\/\" \/>\n<meta property=\"og:locale\" content=\"fr_FR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"PROSIT project: The Medicines and ERIAS teams laureates of the Research Call PREPS 2019 | Bordeaux population health\" \/>\n<meta property=\"og:description\" content=\"The PROSIT project coordinated by the BPH Pharmacoepi team was selected as part of the 2019 DGOS-PREPS Research Call. Using machine learning and text mining methods, the objective of this project is first to identify and analyze potential drug interactions from hospital discharge medical prescriptions. 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