How to harness AI for genomic insights in drug-resistant tuberculosis? | Discovery

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In this AI for Good Discovery talk, learn about a novel approach using artificial intelligence to better understand genomics. Focusing on recent work on AI has provided insights into how the genomics of tuberculosis determine antibiotic resistance. This talk also touches upon the broader implications of diagnostic AI tools on their journey to clinical integration. \n\n Speakers:\nAnna G. Green, Postdoctoral fellow, Harvard Medical School\nChang Ho Yoon, Wellcome Trust Ph.D. Scholar, Oxford University’s Big Data Institute\n\n\n Watch the latest #AIforGood videos!\n\n\nExplore more #AIforGood content:\n AI for Good Top Hits\n   • Top Hits  \n\n AI for Good Webinars\n   • AI for Good Webinars  \n\n AI for Good Keynotes\n   • AI for Good Keynotes  \n\n Stay updated and join our weekly AI for Good newsletter:\nhttp://eepurl.com/gI2kJ5\n\n Discover what's next on our programme!\nhttps://aiforgood.itu.int/programme/\n\nCheck out the latest AI for Good news:\nhttps://aiforgood.itu.int/newsroom/\n\nExplore the AI for Good blog:\nhttps://aiforgood.itu.int/ai-for-good-blog/\n\n Connect on our social media:\nWebsite: https://aiforgood.itu.int/\nTwitter: https://twitter.com/ITU_AIForGood\nLinkedIn Page: https://www.linkedin.com/company/26511907 \nLinkedIn Group: https://www.linkedin.com/groups/8567748 \nInstagram: https://www.instagram.com/aiforgood \nFacebook: https://www.facebook.com/AIforGood\n\nWhat is AI for Good?\nThe AI for Good series is the leading action-oriented, global & inclusive United Nations platform on AI. The Summit is organized all year, always online, in Geneva by the ITU with XPRIZE Foundation in partnership with over 35 sister United Nations agencies, Switzerland and ACM. The goal is to identify practical applications of AI and scale those solutions for global impact.\n\nDisclaimer:\nThe views and opinions expressed are those of the panelists and do not reflect the official policy of the ITU.\n\n#AIforHealth #AIforGoodDiscovery




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