{"id":436,"date":"2021-02-13T16:15:35","date_gmt":"2021-02-13T16:15:35","guid":{"rendered":"https:\/\/wellai.health\/blog\/?p=436"},"modified":"2024-04-03T03:13:51","modified_gmt":"2024-04-03T03:13:51","slug":"wellai-scientists-to-present-research-based-on-the-covid-19-research-tool-at-the-global-ifcc-conference","status":"publish","type":"post","link":"https:\/\/wellai.health\/blog\/wellai-scientists-to-present-research-based-on-the-covid-19-research-tool-at-the-global-ifcc-conference\/","title":{"rendered":"WellAI Scientists Set to Present Their Machine Learning Research at the Global IFCC Conference"},"content":{"rendered":"

SHERIDAN, Wyo.<\/span>,\u00a0Feb. 13, 2021<\/span>\u00a0\/PRNewswire\/ — WellAI data scientists Sergei Polevikov and\u00a0Daniel Satchkov<\/span>\u00a0are to present their COVID-19 research based on an advanced machine learning technology at the IFCC (International Federation of Clinical Chemistry and Laboratory Medicine) annual conference on\u00a0February 15<\/span>, 2021.\u00a0 The title of their talk is “Comprehending Hundreds of Thousands of COVID-19 Studies using Mathematical Models of Language and AI”.<\/p>\n

The WellAI COVID-19 tool is available at\u00a0https:\/\/wellai.health\/covid<\/a>.\u00a0This research behind this tool was published in a peer-reviewed article “Artificial Intelligence-Powered Search Tools and Resources in the Fight Against COVID-19” in the eJIFCC (electronic Journal of the IFCC) in June 2020.\u00a0 The article is available at\u00a0https:\/\/pubmed.ncbi.nlm.nih.gov\/32549878\/<\/a>.<\/p>\n

Daniel Satchkov<\/span>, the lead data scientist at WellAI, emphasized: “The analytical tool we’ve developed processes an enormous amount of data, based on over 30 million medical studies.\u00a0 It is impossible for any human to know this much information.\u00a0 Our algorithms understand and sort medical concepts in the order of their relevance to other medical concepts, in this case \u2013 to COVID-19.\u00a0 With all the synonyms and correlated concepts, there is currently a total of 4,224,512 medical concepts in the WellAI database, 60,892 of which are specifically related to COVID. We have been able to resolve the so-called dimensionality problem in machine learning by assigning medical concepts to clusters (also known as factors).\u00a0 In fact, we have saved these clusters in a GitHub repository and will offer complimentary access to the repository to the IFCC conference participants.”<\/p>\n

Sergei Polevikov, CEO of WellAI, explained:\u00a0 “We are proud to make our contribution to the fight against COVID.\u00a0 The machine learning tool we have developed at WellAI is unique, as it can read and comprehend medical articles at human expert level or better, and certainly much faster.\u00a0 This tool could help researchers from many fields of medicine understand how COVID and other coronaviruses develop and how they affect human body, and what the possible side effects and consequences are.\u00a0 This knowledge will help us be better prepared for the next pandemic, should it ever happen.\u00a0 In addition, we have been working on a number of exciting AI applications in genomics research, as part of the international IFCC Working Group on Artificial Intelligence and Genomic Diagnostics (WG-AIGD).\u00a0Daniel Satchkov<\/span>\u00a0and I have recently had an honor to join this prestigious group.”<\/p>\n

For more information about WellAI, visit\u00a0https:\/\/wellai.health<\/a>\u00a0or call 307-278-1819.<\/p>\n

Source – https:\/\/www.prnewswire.com\/news-releases\/wellai-scientists-to-present-research-based-on-the-covid-19-research-tool-at-the-global-ifcc-conference-301227976.html<\/a><\/p>\n

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SHERIDAN, Wyo.,\u00a0Feb. 13, 2021\u00a0\/PRNewswire\/ — WellAI data scientists Sergei Polevikov and\u00a0Daniel Satchkov\u00a0are to present their COVID-19 research based on an<\/p>\n","protected":false},"author":3,"featured_media":437,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[178,174],"tags":[],"jetpack_featured_media_url":"https:\/\/i0.wp.com\/wellai.health\/blog\/wp-content\/uploads\/2021\/12\/press-release-2-e1640794767314.jpg?fit=1194%2C630&ssl=1","jetpack_sharing_enabled":true,"jetpack_likes_enabled":true,"_links":{"self":[{"href":"https:\/\/wellai.health\/blog\/wp-json\/wp\/v2\/posts\/436"}],"collection":[{"href":"https:\/\/wellai.health\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/wellai.health\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/wellai.health\/blog\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/wellai.health\/blog\/wp-json\/wp\/v2\/comments?post=436"}],"version-history":[{"count":4,"href":"https:\/\/wellai.health\/blog\/wp-json\/wp\/v2\/posts\/436\/revisions"}],"predecessor-version":[{"id":837,"href":"https:\/\/wellai.health\/blog\/wp-json\/wp\/v2\/posts\/436\/revisions\/837"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/wellai.health\/blog\/wp-json\/wp\/v2\/media\/437"}],"wp:attachment":[{"href":"https:\/\/wellai.health\/blog\/wp-json\/wp\/v2\/media?parent=436"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/wellai.health\/blog\/wp-json\/wp\/v2\/categories?post=436"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/wellai.health\/blog\/wp-json\/wp\/v2\/tags?post=436"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}