{"id":32936,"date":"2022-08-30T14:58:57","date_gmt":"2022-08-30T18:58:57","guid":{"rendered":"https:\/\/web.uri.edu\/riinbre\/?p=32936"},"modified":"2022-09-13T11:30:23","modified_gmt":"2022-09-13T15:30:23","slug":"announcing-the-nih-long-covid-computational-challenge-l3c","status":"publish","type":"post","link":"https:\/\/web.uri.edu\/riinbre\/announcing-the-nih-long-covid-computational-challenge-l3c\/","title":{"rendered":"Announcing The NIH Long COVID Computational Challenge (L3C)"},"content":{"rendered":"<p align=\"center\">Join the challenge to develop, train, and test models to aid in predicting the susceptibility to and likelihood of developing PASC\/Long COVID in patients with SARS-CoV-2 infection.<\/p>\n<p align=\"left\">Long COVID, can affect anyone, including children, and it can develop in people who had asymptomatic, mild, or severe COVID-19. To complement the National Institutes of Health (NIH) other Long COVID research initiatives, like&nbsp;Researching COVID to Enhance Recovery (RECOVER), the&nbsp;RADx-Radical (RADx-rad) program&nbsp;at the NIH is launching the&nbsp;Long COVID Computational Challenge (L3C). NIH designed this challenge to support creative data-driven solutions that meaningfully advance the current understanding of the risks of developing PASC\/Long COVID. The total prize for this Challenge will be up to $500,000.<\/p>\n<p align=\"left\">Webinar: September 21<\/p>\n<p align=\"left\">Submissions Due: December 15<\/p>\n<p align=\"left\"><a href=\"https:\/\/www.imagwiki.nibib.nih.gov\/index.php\/news-events\/announcements\/announcing-nih-long-covid-computational-challenge-l3c\" target=\"_blank\" rel=\"noopener\">More Information<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Join the challenge to develop, train, and test models to aid in predicting the susceptibility to and likelihood of developing PASC\/Long COVID in patients with SARS-CoV-2 infection. Long COVID, can affect anyone, including children, and it can develop in people who had asymptomatic, mild, or severe COVID-19. To complement the National Institutes of Health (NIH) [&hellip;]<\/p>\n","protected":false},"author":3192,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":"","_links_to":"","_links_to_target":""},"categories":[72,644],"tags":[780,643,642,778,779],"class_list":["post-32936","post","type-post","status-publish","format-standard","hentry","category-bioinfo","category-mic","tag-artificial-intelligence","tag-covid","tag-data-science","tag-funding","tag-machine-learning"],"acf":[],"_links":{"self":[{"href":"https:\/\/web.uri.edu\/riinbre\/wp-json\/wp\/v2\/posts\/32936","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/web.uri.edu\/riinbre\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/web.uri.edu\/riinbre\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/web.uri.edu\/riinbre\/wp-json\/wp\/v2\/users\/3192"}],"replies":[{"embeddable":true,"href":"https:\/\/web.uri.edu\/riinbre\/wp-json\/wp\/v2\/comments?post=32936"}],"version-history":[{"count":1,"href":"https:\/\/web.uri.edu\/riinbre\/wp-json\/wp\/v2\/posts\/32936\/revisions"}],"predecessor-version":[{"id":32937,"href":"https:\/\/web.uri.edu\/riinbre\/wp-json\/wp\/v2\/posts\/32936\/revisions\/32937"}],"wp:attachment":[{"href":"https:\/\/web.uri.edu\/riinbre\/wp-json\/wp\/v2\/media?parent=32936"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/web.uri.edu\/riinbre\/wp-json\/wp\/v2\/categories?post=32936"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/web.uri.edu\/riinbre\/wp-json\/wp\/v2\/tags?post=32936"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}