{"id":368,"date":"2020-05-27T14:40:26","date_gmt":"2020-05-27T14:40:26","guid":{"rendered":"https:\/\/aimonks.com\/aibytes\/?p=368"},"modified":"2020-05-27T14:40:28","modified_gmt":"2020-05-27T14:40:28","slug":"wada-explores-ai-potential-to-detect-dopers","status":"publish","type":"post","link":"https:\/\/aimonks.com\/aibytes\/2020\/05\/27\/wada-explores-ai-potential-to-detect-dopers\/","title":{"rendered":"WADA Explores AI Potential To Detect Dopers"},"content":{"rendered":"<span class=\"rt-reading-time\" style=\"display: block;\"><span class=\"rt-label rt-prefix\">Reading Time: <\/span> <span class=\"rt-time\">2<\/span> <span class=\"rt-label rt-postfix\">minutes<\/span><\/span>\n<p>The<strong> World Anti-doping Agency (WADA) <\/strong>has turned to Artificial Intelligence to detect athletes with signs of drug use, which even experienced human investigators can&#8217;t discover.<br>They don&#8217;t intend to suspend athletes based on the word of a machine but <strong>use AI to find suspect athletes<\/strong> and get them tested.<\/p>\n\n\n\n<p>WADA senior executive director Oliver Rabin explains how information regarding a suspect athlete&#8217;s competition calendar, whereabouts, and previous results are analyzed. Doing all this work manually is time-consuming and not safe during this pandemic, hence WADA leverages AI to do the job<strong> remotely and efficiently<\/strong>.<\/p>\n\n\n\n<p>The technology analyzes an athlete&#8217;s blood or urine sample to find a performance-enhancing substance, and track testosterone levels and RBC count. WADA hopes to <strong>utilize AI to improve the system<\/strong> in a way that enables it to track patterns between the markets and to cross-reference them with other information. They aim at making EPO and steroid detection more precise.<\/p>\n\n\n\n<p>WADA plans on <strong>employing ML to detect similarities<\/strong> between confirmed dirty and clean profiles to filter out potential suspects<\/p>\n\n\n\n<p>Rabin elaborates on the existence of a Montreal-based global project which can <strong>predict the risk <\/strong>of doping based on data evaluated from a broader range of sources.<\/p>\n\n\n\n<p>They are trying to<strong> find a balance betw<\/strong>een protecting data and protecting individuals while trying to determine the potential of AI in drug detection.<\/p>\n\n\n\n<p>AI is an expensive domain with a high demand for specialists.WADA is funding three projects in Canada. It costs around $425,000, and one in Germany costs about $60,000 for the EPO project to find out if AI could <strong>spot signs of drug use<\/strong>, which even experienced human investigators might overlook.<\/p>\n\n\n\n<p>#AIMonks #AI #ArtificialIntelligence #ML #MachineLearning #WADA #DrugAbuse #Athletes #Technology #Steroids<\/p>\n","protected":false},"excerpt":{"rendered":"<p><span class=\"rt-reading-time\" style=\"display: block;\"><span class=\"rt-label rt-prefix\">Reading Time: <\/span> <span class=\"rt-time\">2<\/span> <span class=\"rt-label rt-postfix\">minutes<\/span><\/span> The World Anti-doping Agency (WADA) has turned to Artificial Intelligence to detect athletes with signs of drug use, which even experienced human investigators can&#8217;t discover.They don&#8217;t intend to suspend athletes based on the word of a machine but use AI to find suspect athletes and get them tested. WADA senior [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":370,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[34],"tags":[35,24,25,234,233,32,33,235,22,232],"class_list":["post-368","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ethics-and-compliance","tag-ai","tag-ai-monks","tag-artificial-intelligence","tag-athletes","tag-drug-abuse","tag-machine-learning","tag-ml","tag-steroids","tag-technology","tag-wada"],"rttpg_featured_image_url":{"full":["https:\/\/aimonks.com\/aibytes\/wp-content\/uploads\/2020\/05\/syringe-1884784_640.jpg",640,384,false],"landscape":["https:\/\/aimonks.com\/aibytes\/wp-content\/uploads\/2020\/05\/syringe-1884784_640.jpg",640,384,false],"portraits":["https:\/\/aimonks.com\/aibytes\/wp-content\/uploads\/2020\/05\/syringe-1884784_640.jpg",640,384,false],"thumbnail":["https:\/\/aimonks.com\/aibytes\/wp-content\/uploads\/2020\/05\/syringe-1884784_640-150x150.jpg",150,150,true],"medium":["https:\/\/aimonks.com\/aibytes\/wp-content\/uploads\/2020\/05\/syringe-1884784_640-300x180.jpg",300,180,true],"large":["https:\/\/aimonks.com\/aibytes\/wp-content\/uploads\/2020\/05\/syringe-1884784_640.jpg",640,384,false],"1536x1536":["https:\/\/aimonks.com\/aibytes\/wp-content\/uploads\/2020\/05\/syringe-1884784_640.jpg",640,384,false],"2048x2048":["https:\/\/aimonks.com\/aibytes\/wp-content\/uploads\/2020\/05\/syringe-1884784_640.jpg",640,384,false],"hestia-blog":["https:\/\/aimonks.com\/aibytes\/wp-content\/uploads\/2020\/05\/syringe-1884784_640-360x240.jpg",360,240,true]},"rttpg_author":{"display_name":"AI Bytes","author_link":"https:\/\/aimonks.com\/aibytes\/author\/aibytes_kashika\/"},"rttpg_comment":0,"rttpg_category":"<a href=\"https:\/\/aimonks.com\/aibytes\/category\/daily-bytes\/ethics-and-compliance\/\" rel=\"category tag\">Ethics and Compliance<\/a>","rttpg_excerpt":"Reading Time: 2 minutes The World Anti-doping Agency (WADA) has turned to Artificial Intelligence to detect athletes with signs of drug use, which even experienced human investigators can&#8217;t discover.They don&#8217;t intend to suspend athletes based on the word of a machine but use AI to find suspect athletes and get them tested. WADA senior [&hellip;]","_links":{"self":[{"href":"https:\/\/aimonks.com\/aibytes\/wp-json\/wp\/v2\/posts\/368","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/aimonks.com\/aibytes\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/aimonks.com\/aibytes\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/aimonks.com\/aibytes\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/aimonks.com\/aibytes\/wp-json\/wp\/v2\/comments?post=368"}],"version-history":[{"count":1,"href":"https:\/\/aimonks.com\/aibytes\/wp-json\/wp\/v2\/posts\/368\/revisions"}],"predecessor-version":[{"id":371,"href":"https:\/\/aimonks.com\/aibytes\/wp-json\/wp\/v2\/posts\/368\/revisions\/371"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/aimonks.com\/aibytes\/wp-json\/wp\/v2\/media\/370"}],"wp:attachment":[{"href":"https:\/\/aimonks.com\/aibytes\/wp-json\/wp\/v2\/media?parent=368"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/aimonks.com\/aibytes\/wp-json\/wp\/v2\/categories?post=368"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/aimonks.com\/aibytes\/wp-json\/wp\/v2\/tags?post=368"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}