{"id":6277,"date":"2021-02-08T08:33:22","date_gmt":"2021-02-08T13:33:22","guid":{"rendered":"https:\/\/www.bu.edu\/neidl\/?p=6277"},"modified":"2021-02-08T08:33:22","modified_gmt":"2021-02-08T13:33:22","slug":"artificial-intelligence-could-help-fine-tune-vaccine-priority-lists-predict-mortality-study-reports","status":"publish","type":"post","link":"https:\/\/www.bu.edu\/neidl\/2021\/02\/artificial-intelligence-could-help-fine-tune-vaccine-priority-lists-predict-mortality-study-reports\/","title":{"rendered":"Artificial intelligence could help \u2018fine-tune\u2019 vaccine priority lists, predict mortality, study reports"},"content":{"rendered":"<p><strong>Original article from The Boston Globe <\/strong><strong class=\"article-header__byline article-header__byline--article\"><span class=\"author | align_items_center bold font_primary margin_right_3\"><span class=\"bold\">by Dasia Moore. February 4<\/span><\/span>, 2021<\/strong><\/p>\n<div class=\"lead | border_box gutter_16--desktop gutter_16--tablet relative\">\n<div class=\"lead | border_box gutter_16--desktop gutter_16--tablet relative\">\n<div data-type=\"text\" class=\"card collection-item \">\n<div class=\"card-content card-article\" id=\"\">\n<section class=\"article-section--content hang-punctuation article-section--first article-section--centered\" data-reactid=\"277\">\n<section>\n<div class=\"lead | border_box gutter_16--desktop gutter_16--tablet relative\">\n<div class=\"lead | border_box gutter_16--desktop gutter_16--tablet relative\">\n<p class=\"paragraph | gutter_20_0\"><span class=\"html-render\">Much of the debate around vaccine prioritization hinges on one question: Who faces the greatest risk of dying if they become infected with COVID-19? Thus far, it is a question without a definitive answer.<\/span><\/p>\n<p class=\"paragraph | gutter_20_0\"><span class=\"html-render\">Age is one way to gauge risk, with the Centers for Disease Control and Prevention recommending that people aged 75 and older be among the first members of the general public to have access to the vaccine. But in the next phase of distribution, as the CDC tries to factor in underlying medical conditions, the calculation becomes much more complex.<\/span><\/p>\n<p class=\"paragraph | gutter_20_0\"><span class=\"html-render\">Artificial intelligence, when applied to standard patient medical records, can help untangle that web, a new <a href=\"https:\/\/www.nature.com\/articles\/s41746-021-00383-x.epdf?sharing_token=7CHnt937q9Xeadb-bH3Z_9RgN0jAjWel9jnR3ZoTv0N1ZKr9Rm3v2nwRsMwrKD-36pDxlro699Xqxw43SmcYrzOdySPC2q9F7vehYHtGlBZcwKPDZTCfeN5zmjDKkz8mpsULECde2AY1GaqCqPL9_lbJ64RzmDjQCwL9i2DE4Kw%3D\" class=\"\" target=\"_blank\" rel=\"noopener noreferrer\">study<\/a> by Massachusetts General Hospital and Harvard researchers<b> <\/b>found.<\/span><\/p>\n<p class=\"paragraph | gutter_20_0\"><span class=\"html-render\">Using only information known before a patient\u2019s COVID-19 infection \u2014 diagnosed health problems, medications, and basic demographic information \u2014 researchers were able to identify factors that predict a heightened risk of COVID-related death. Age emerged as the most important predictor, immediately followed by a history of pneumonia, a condition not currently listed in the CDC\u2019s prioritization plan.<\/span><\/p>\n<p class=\"paragraph | gutter_20_0\"><span class=\"html-render\">\u201cIf we can predict [mortality] so well, based off of all these features that happen before individuals even get sick, this can really be applied in ways that I think are novel for an algorithm like this,\u201d said Dr. Zachary Strasser, one of the study\u2019s lead researchers, along with Hossein Estiri, an assistant professor of medicine at MGH and Harvard. \u201cWe can really think about who needs to get prioritized for limited resources, because these are the people that are probably going to do worse.\u201d<\/span><\/p>\n<\/div>\n<\/div>\n<\/section>\n<\/section>\n<\/div>\n<\/div>\n<\/div>\n<p><a href=\"https:\/\/businessmirror.com.ph\/2021\/02\/05\/does-wearing-two-masks-provide-more-protection\/\">Click to Read Full Article in The Boston Globe<\/a><\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>Original article from The Boston Globe by Dasia Moore. February&#8230;<\/p>\n","protected":false},"author":6107,"featured_media":6278,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[3075,1298],"tags":[],"_links":{"self":[{"href":"https:\/\/www.bu.edu\/neidl\/wp-json\/wp\/v2\/posts\/6277"}],"collection":[{"href":"https:\/\/www.bu.edu\/neidl\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.bu.edu\/neidl\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.bu.edu\/neidl\/wp-json\/wp\/v2\/users\/6107"}],"replies":[{"embeddable":true,"href":"https:\/\/www.bu.edu\/neidl\/wp-json\/wp\/v2\/comments?post=6277"}],"version-history":[{"count":1,"href":"https:\/\/www.bu.edu\/neidl\/wp-json\/wp\/v2\/posts\/6277\/revisions"}],"predecessor-version":[{"id":6279,"href":"https:\/\/www.bu.edu\/neidl\/wp-json\/wp\/v2\/posts\/6277\/revisions\/6279"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.bu.edu\/neidl\/wp-json\/wp\/v2\/media\/6278"}],"wp:attachment":[{"href":"https:\/\/www.bu.edu\/neidl\/wp-json\/wp\/v2\/media?parent=6277"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.bu.edu\/neidl\/wp-json\/wp\/v2\/categories?post=6277"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.bu.edu\/neidl\/wp-json\/wp\/v2\/tags?post=6277"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}