{"id":130688,"date":"2020-12-11T00:48:25","date_gmt":"2020-12-10T21:48:25","guid":{"rendered":"https:\/\/en.buradabiliyorum.com\/study-details-first-artificial-intelligence-tool-to-help-labs-rule-out-covid-19\/"},"modified":"2020-12-11T00:48:25","modified_gmt":"2020-12-10T21:48:25","slug":"study-details-first-artificial-intelligence-tool-to-help-labs-rule-out-covid-19","status":"publish","type":"post","link":"https:\/\/buradabiliyorum.com\/en\/study-details-first-artificial-intelligence-tool-to-help-labs-rule-out-covid-19\/","title":{"rendered":"#Study details first artificial intelligence tool to help labs rule-out COVID-19"},"content":{"rendered":"<p>&#8220;<strong>#Study details first artificial intelligence tool to help labs rule-out COVID-19<\/strong>&#8221;<\/p>\n<div>\n<div class=\"article-gallery lightGallery\">\n<div data-thumb=\"https:\/\/scx1.b-cdn.net\/csz\/news\/tmb\/2020\/8-researchersp.jpg\" data-src=\"https:\/\/scx2.b-cdn.net\/gfx\/news\/2020\/8-researchersp.jpg\" data-sub-html=\"This scanning electron microscope image shows SARS-CoV-2 (yellow)\u2014also known as 2019-nCoV, the virus that causes COVID-19\u2014isolated from a patient, emerging from the surface of cells (blue\/pink) cultured in the lab. Credit: NIAID-RML\">\n<figure class=\"article-img\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/scx1.b-cdn.net\/csz\/news\/800\/2020\/8-researchersp.jpg\" alt=\"COVID-19, coronavirus\" title=\"This scanning electron microscope image shows SARS-CoV-2 (yellow)\u2014also known as 2019-nCoV, the virus that causes COVID-19\u2014isolated from a patient, emerging from the surface of cells (blue\/pink) cultured in the lab. Credit: NIAID-RML\" width=\"639\" height=\"426\"\/><figcaption class=\"text-darken text-low-up text-truncate-js text-truncate mt-3\">\n                This scanning electron microscope image shows SARS-CoV-2 (yellow)\u2014also known as 2019-nCoV, the virus that causes COVID-19\u2014isolated from a patient, emerging from the surface of cells (blue\/pink) cultured in the lab. Credit: NIAID-RML<br \/>\n            <\/figcaption><\/figure>\n<\/div>\n<\/div>\n<p>Hospital-based laboratories and doctors at the front line of the COVID-19 pandemic might soon add artificial intelligence to their testing toolkit. A recent study conducted with collaborators from the University of Vermont and Cedars-Sinai describes the performance of Biocogniv&#8217;s new AI-COVID software. The team found high accuracy in predicting the probability of COVID-19 infection using routine blood tests, which can help hospitals reduce the number of patients referred for scarce PCR testing.\n                                                <\/p>\n<p>                                                                                Their study in the <i>Journal of Medical Internet Research<\/i> is available online.<\/p>\n<p>&#8220;Nine months into this pandemic, we now have a better understanding of how to care for patients with COVID-19,&#8221; says lead author and University of Vermont Assistant Professor Timothy Plante, M.D., M.H.S., &#8220;but there&#8217;s still a big bottleneck in COVID-19 diagnosis with PCR testing.&#8221;<\/p>\n<p>PCR testing is the current standard diagnostic for COVID-19, and requires specific sampling, like a nasal swab, and specialized laboratory equipment to run.<\/p>\n<p>Biocogniv Chief Operating Officer Tanya Kanigan, Ph.D., says, &#8220;According to data from over 100 US hospitals, the national average turnaround time for COVID-19 tests ordered in emergency rooms is above 24 hours, far from the targeted one-hour turnaround.&#8221;<\/p>\n<p>Complete Blood Count and Complete Metabolic Panels are common laboratory tests ordered by emergency departments and have a rapid turnaround time. These tests provide insight into the immune system, electrolytes, kidney, and liver. The researchers were able to train a model that analyzes changes in these routine tests and assigns a probability of the patient being COVID-19 negative with high accuracy.<\/p>\n<p>&#8220;AI-COVID takes seconds to generate its informative result once these blood tests return, which can then be incorporated by the laboratory into its own test interpretation,&#8221; says Jennifer Joe, M.D., an emergency physician in Boston, Mass. and Biocogniv&#8217;s Chief Medical Officer. &#8220;In an efficient emergency department that prioritizes these routine blood tests, the door-to-result time could be under an hour.&#8221;<\/p>\n<p>Cedars-Sinai pulmonary and internal medicine specialist Victor Tapson, M.D., says such assistive tools that help physicians rule out possible diagnoses are familiar in emergency medicine.<\/p>\n<p>&#8220;For example, a low D-dimer blood test can help us rule out clots in certain patients, allowing providers to skip expensive, often time-consuming diagnostics such as chest CT scans,&#8221; says Tapson.<\/p>\n<p>The Biocogniv team believes a secondary benefit of laboratories incorporating AI-COVID might be reduced time for traditional PCR results.<\/p>\n<p>&#8220;With the help of AI-COVID, laboratories might relieve some of the testing bottleneck by helping providers better allocate rapid PCR testing for patients who really need it,&#8221; says Joe.<\/p>\n<p>The AI-COVID model was validated on real world data from Cedars-Sinai as well as on data from geographically and demographically diverse patient encounters from 22 U.S. hospitals, achieving an area under the curve (or AUC) of 0.91 out of 1.00.<\/p>\n<p>&#8220;This enables the model to achieve a high sensitivity of 95% while maintaining moderate specificity of 49%, which is very similar to the performance of other commonly used rule-out tests,&#8221; says Biocogniv Chief Scientific Officer George Hauser, MD, a pathologist.<\/p>\n<p>Biocogniv CEO Artur Adib, Ph.D., says, &#8220;I&#8217;m honored to have such an impressive team of medical scientists from the University of Vermont and Cedars-Sinai as collaborators in validating this timely model. AI has progressed considerably; the time is now to leverage this powerful tool for new healthcare breakthroughs, and we&#8217;re glad to direct it to help hospital laboratories and providers combat the current COVID-19 crisis.&#8221;\n                                                                                                                        <\/p>\n<hr\/>\n<div class=\"article-main__explore my-4 d-print-none\">\n<p>                                                                                        Follow the latest <a href=\"https:\/\/buradabiliyorum.com\/en\/category\/news\/\" data-internallinksmanager029f6b8e52c=\"2\" title=\"News\" target=\"_blank\" rel=\"noopener\">news<\/a> on the coronavirus (COVID-19) outbreak\n                                                                                    <\/p><\/div>\n<hr class=\"mb-4\"\/>\n<div class=\"article-main__more p-4\">\n                                                                                                <strong>More information:<\/strong><br \/>\n                                                Timothy B Plante et al, Development and External Validation of a Machine Learning Tool to Rule Out COVID-19 Among Adults in the Emergency Department Using Routine Blood Tests: A Large, Multicenter, Real-World Study, <i>Journal of Medical Internet Research<\/i> (2020).  <a rel=\"nofollow noopener noreferrer\" target=\"_blank\" data-doi=\"1\" href=\"http:\/\/dx.doi.org\/10.2196\/24048\">DOI: 10.2196\/24048<\/a><\/p><\/div>\n<p>\n                                                Provided by<br \/>\n                                                                                                    Larner College of Medicine at the University of Vermont<\/p>\n<p>                                        <!-- print only --><\/p>\n<div class=\"d-none d-print-block\">\n<p>                                                 <strong>Citation<\/strong>:<br \/>\n                                                 Study details first artificial intelligence tool to help labs rule-out COVID-19 (2020, December 10)<br \/>\n                                                 retrieved 10 December 2020<br \/>\n                                                 from https:\/\/medicalxpress.com\/news\/2020-12-artificial-intelligence-tool-labs-rule-out.html<\/p>\n<p>                                            This document is subject to copyright. 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Credit: NIAID-RML Hospital-based laboratories and doctors at the front line of the COVID-19 pandemic&#8230;<\/p>\n","protected":false},"author":1,"featured_media":130689,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"fifu_image_url":"https:\/\/scx2.b-cdn.net\/gfx\/news\/2020\/8-researchersp.jpg","fifu_image_alt":"","footnotes":""},"categories":[16],"tags":[],"class_list":["post-130688","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-sciencee"],"_links":{"self":[{"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/posts\/130688","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/comments?post=130688"}],"version-history":[{"count":0,"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/posts\/130688\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/media\/130689"}],"wp:attachment":[{"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/media?parent=130688"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/categories?post=130688"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/buradabiliyorum.com\/en\/wp-json\/wp\/v2\/tags?post=130688"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}