{"id":2092,"date":"2024-06-26T21:23:20","date_gmt":"2024-06-26T21:23:20","guid":{"rendered":"https:\/\/www.tun.com\/home\/?p=2092"},"modified":"2024-10-16T21:31:35","modified_gmt":"2024-10-16T21:31:35","slug":"ai-breakthrough-identifies-high-risk-endometrial-cancer-with-potential-to-save-lives","status":"publish","type":"post","link":"https:\/\/www.tun.com\/home\/ai-breakthrough-identifies-high-risk-endometrial-cancer-with-potential-to-save-lives\/","title":{"rendered":"AI Breakthrough Identifies High-Risk Endometrial Cancer With Potential to Save Lives"},"content":{"rendered":"\n<div class=\"wp-block-group\"><div class=\"wp-block-group__inner-container is-layout-constrained wp-block-group-is-layout-constrained\">\n<div class=\"wp-block-uagb-blockquote uagb-block-e7eb3fc3 uagb-blockquote__skin-border uagb-blockquote__stack-img-none\"><blockquote class=\"uagb-blockquote\"><div class=\"uagb-blockquote__content\">Scientists at the University of British Columbia have used artificial intelligence to identify a high-risk subtype of endometrial cancer, paving the way for better patient outcomes and more targeted treatments.<\/div><footer><div class=\"uagb-blockquote__author-wrap uagb-blockquote__author-at-left\"><\/div><\/footer><\/blockquote><\/div>\n\n\n\n<div class=\"wp-block-group is-content-justification-space-between is-nowrap is-layout-flex wp-container-core-group-is-layout-0dfbf163 wp-block-group-is-layout-flex\"><div style=\"font-size:16px;\" class=\"has-text-align-left wp-block-post-author\"><div class=\"wp-block-post-author__content\"><p class=\"wp-block-post-author__name\">The University Network<\/p><\/div><\/div>\n\n\n<div class=\"wp-block-uagb-social-share uagb-social-share__outer-wrap uagb-social-share__layout-horizontal uagb-block-ee584a31\">\n<div class=\"wp-block-uagb-social-share-child uagb-ss-repeater uagb-ss__wrapper uagb-block-ec619ce7\"><span class=\"uagb-ss__link\" data-href=\"https:\/\/www.facebook.com\/sharer.php?u=\" tabindex=\"0\" role=\"button\" aria-label=\"facebook\"><span class=\"uagb-ss__source-wrap\"><span class=\"uagb-ss__source-icon\"><svg xmlns=\"https:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 512 512\"><path d=\"M504 256C504 119 393 8 256 8S8 119 8 256c0 123.8 90.69 226.4 209.3 245V327.7h-63V256h63v-54.64c0-62.15 37-96.48 93.67-96.48 27.14 0 55.52 4.84 55.52 4.84v61h-31.28c-30.8 0-40.41 19.12-40.41 38.73V256h68.78l-11 71.69h-57.78V501C413.3 482.4 504 379.8 504 256z\"><\/path><\/svg><\/span><\/span><\/span><\/div>\n\n\n\n<div class=\"wp-block-uagb-social-share-child uagb-ss-repeater uagb-ss__wrapper uagb-block-32d99934\"><span class=\"uagb-ss__link\" data-href=\"https:\/\/twitter.com\/share?url=\" tabindex=\"0\" role=\"button\" aria-label=\"twitter\"><span class=\"uagb-ss__source-wrap\"><span class=\"uagb-ss__source-icon\"><svg xmlns=\"https:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 512 512\"><path d=\"M389.2 48h70.6L305.6 224.2 487 464H345L233.7 318.6 106.5 464H35.8L200.7 275.5 26.8 48H172.4L272.9 180.9 389.2 48zM364.4 421.8h39.1L151.1 88h-42L364.4 421.8z\"><\/path><\/svg><\/span><\/span><\/span><\/div>\n\n\n\n<div class=\"wp-block-uagb-social-share-child uagb-ss-repeater uagb-ss__wrapper uagb-block-1d136f14\"><span class=\"uagb-ss__link\" data-href=\"https:\/\/www.linkedin.com\/shareArticle?url=\" tabindex=\"0\" role=\"button\" aria-label=\"linkedin\"><span class=\"uagb-ss__source-wrap\"><span class=\"uagb-ss__source-icon\"><svg xmlns=\"https:\/\/www.w3.org\/2000\/svg\" viewBox=\"0 0 448 512\"><path d=\"M416 32H31.9C14.3 32 0 46.5 0 64.3v383.4C0 465.5 14.3 480 31.9 480H416c17.6 0 32-14.5 32-32.3V64.3c0-17.8-14.4-32.3-32-32.3zM135.4 416H69V202.2h66.5V416zm-33.2-243c-21.3 0-38.5-17.3-38.5-38.5S80.9 96 102.2 96c21.2 0 38.5 17.3 38.5 38.5 0 21.3-17.2 38.5-38.5 38.5zm282.1 243h-66.4V312c0-24.8-.5-56.7-34.5-56.7-34.6 0-39.9 27-39.9 54.9V416h-66.4V202.2h63.7v29.2h.9c8.9-16.8 30.6-34.5 62.9-34.5 67.2 0 79.7 44.3 79.7 101.9V416z\"><\/path><\/svg><\/span><\/span><\/span><\/div>\n<\/div>\n<\/div>\n<\/div><\/div>\n\n\n\n<p>Groundbreaking research from the University of British Columbia (UBC) could revolutionize care for patients with endometrial cancer, the most common type of gynecologic malignancy. Leveraging the capabilities of artificial intelligence, scientists have uncovered a high-risk subset of this cancer that conventional pathology often misses.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">AI Unmasks Hidden Risks<\/h2>\n\n\n\n<p>This <a href=\"https:\/\/www.nature.com\/articles\/s41467-024-49017-2\" title=\"\">study<\/a>, published in Nature Communications, revealed that AI could detect patterns in thousands of cancer cell images, identifying a higher-risk subset of endometrial cancer that would otherwise go undetected by traditional methods.<\/p>\n\n\n\n<p>&#8220;Endometrial cancer is a diverse disease, with some patients much more likely to see their cancer return than others,&#8221; Jessica McAlpine, a UBC professor and surgeon-scientist at BC Cancer and Vancouver General Hospital, said in a <a href=\"https:\/\/www.med.ubc.ca\/news\/scientists-discover-high-risk-form-of-endometrial-cancer-and-how-to-test-for-it-using-ai\/\" title=\"\">news release<\/a>. &#8220;It\u2019s so important that patients with high-risk disease are identified so we can intervene and hopefully prevent recurrence. This AI-based approach will help ensure no patient misses an opportunity for potentially lifesaving interventions.&#8221;<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Precision Medicine Through AI<\/h2>\n\n\n\n<p>McAlpine&#8217;s team has a history of groundbreaking work in this area. Back in 2013, their work helped classify endometrial cancer into four distinct subtypes based on molecular characteristics. This led to the development of ProMiSE, a molecular diagnostic tool that has been widely adopted to improve cancer treatment decisions. Despite these advancements, the largest category, representing roughly 50% of endometrial cancers, remained a catch-all group where patient outcomes varied significantly.<\/p>\n\n\n\n<p>To bridge this gap, McAlpine collaborated with machine learning expert Ali Bashashati, an assistant professor of biomedical engineering at UBC. Bashashati&#8217;s team developed a deep learning AI model that analyzed over 2,300 tissue sample images, successfully identifying a subgroup with significantly poorer survival rates.<\/p>\n\n\n\n<p>&#8220;The power of AI is that it can objectively look at large sets of images and identify patterns that elude human pathologists,&#8221; Bashashati said in the news release. &#8220;It\u2019s finding the needle in the haystack. It tells us this group of cancers with these characteristics are the worst offenders and represent a higher risk for patients.&#8221;<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Expanding Access and Equity in Cancer Diagnosis<\/h2>\n\n\n\n<p>The researchers now plan to integrate the AI tool into clinical practice, complementing existing diagnostics. Supported by a grant from the Terry Fox Research Institute, their goal is to make this advanced tool accessible across various settings, from major urban centers to rural communities.<\/p>\n\n\n\n<p>&#8220;The two work hand-in-hand, with AI providing an additional layer on top of the testing we\u2019re already doing,&#8221; said McAlpine. The AI-driven approach stands out for its cost-efficiency and potential to be deployed even in less resourced facilities, thus improving equity in cancer care across geographic locations.<\/p>\n\n\n\n<p>&#8220;What is really compelling to us is the opportunity for greater equity and access,&#8221; added Dr. Bashashati. &#8220;The AI doesn\u2019t care if you\u2019re in a large urban center or rural community, it would just be available, so our hope is that this could really transform how we diagnose and treat endometrial cancer for patients everywhere.&#8221;<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Significance of the Breakthrough<\/h2>\n\n\n\n<p>Endometrial cancer is known for its biological diversity, making it challenging to treat effectively. This AI-based discovery not only refines the classification of endometrial cancers but also has the potential to significantly improve patient outcomes through more targeted and personalized treatment plans.<\/p>\n\n\n\n<p>Overall, this breakthrough marks a significant step forward in the use of artificial intelligence in health care, promising to enhance the precision and accessibility of cancer diagnostics worldwide.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Groundbreaking research from the University of British Columbia (UBC) could revolutionize care for patients with endometrial cancer, the most common type of gynecologic malignancy. Leveraging the capabilities of artificial intelligence, scientists have uncovered a high-risk subset of this cancer that conventional pathology often misses. AI Unmasks Hidden Risks This study, published in Nature Communications, revealed [&hellip;]<\/p>\n","protected":false},"author":3,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"single-no-separators","format":"standard","meta":{"_acf_changed":false,"_uag_custom_page_level_css":"","_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":""},"categories":[8,12],"tags":[],"class_list":["post-2092","post","type-post","status-publish","format-standard","hentry","category-ai","category-health"],"acf":[],"aioseo_notices":[],"uagb_featured_image_src":{"full":false,"thumbnail":false,"medium":false,"medium_large":false,"large":false,"1536x1536":false,"2048x2048":false},"uagb_author_info":{"display_name":"The University Network","author_link":"https:\/\/www.tun.com\/home\/author\/funky_junkie\/"},"uagb_comment_info":0,"uagb_excerpt":"Groundbreaking research from the University of British Columbia (UBC) could revolutionize care for patients with endometrial cancer, the most common type of gynecologic malignancy. Leveraging the capabilities of artificial intelligence, scientists have uncovered a high-risk subset of this cancer that conventional pathology often misses. AI Unmasks Hidden Risks This study, published in Nature Communications, revealed&hellip;","_links":{"self":[{"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/posts\/2092","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/comments?post=2092"}],"version-history":[{"count":7,"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/posts\/2092\/revisions"}],"predecessor-version":[{"id":2134,"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/posts\/2092\/revisions\/2134"}],"wp:attachment":[{"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/media?parent=2092"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/categories?post=2092"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/tags?post=2092"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}