{"id":10594,"date":"2024-11-14T19:23:37","date_gmt":"2024-11-14T19:23:37","guid":{"rendered":"https:\/\/www.tun.com\/home\/?p=10594"},"modified":"2024-11-14T19:23:57","modified_gmt":"2024-11-14T19:23:57","slug":"revolutionary-ai-model-by-wsu-speeds-up-disease-detection","status":"publish","type":"post","link":"https:\/\/www.tun.com\/home\/revolutionary-ai-model-by-wsu-speeds-up-disease-detection\/","title":{"rendered":"Revolutionary AI Model by WSU Speeds Up Disease Detection"},"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\">Researchers at Washington State University have unveiled a deep learning AI model that can identify disease in tissue images with unprecedented speed and accuracy. This breakthrough promises to revolutionize both medical diagnostics and disease-related research.<\/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>Researchers at Washington State University have developed a groundbreaking &#8220;deep learning&#8221; artificial intelligence model that can identify pathologies, or signs of disease, in animal and human tissue images much faster and often more accurately than human experts. This development holds the promise of revolutionizing both the pace of disease research and medical diagnostics.<\/p>\n\n\n\n<p>&#8220;This AI-based deep learning program was very, very accurate at looking at these tissues,&#8221; co-corresponding author Michael Skinner, a professor in the School of Biological Sciences at WSU, said in a <a href=\"https:\/\/news.wsu.edu\/press-release\/2024\/11\/14\/ai-method-can-spot-potential-disease-faster-better-than-humans\/\" title=\"\">news release<\/a>. &#8220;It could revolutionize this type of medicine for both animals and humans, essentially better facilitating these kinds of analysis.&#8221;<\/p>\n\n\n\n<p><\/p>\n\n\n\n<p>Developed by computer scientists Colin Greeley, a former WSU graduate student, and his advising professor Lawrence Holder, the AI model was trained using images from past epigenetic studies conducted in Skinner\u2019s laboratory. <\/p>\n\n\n\n<p>These studies focused on molecular-level signs of disease in various tissues from rats and mice. Subsequently, the AI was tested with images from other studies, including those identifying breast cancer and lymph node metastasis.<\/p>\n\n\n\n<p>Impressively, the deep learning model not only identified pathologies quickly but also found instances that human pathologists had missed. <\/p>\n\n\n\n<p>&#8220;I think we now have a way to identify disease and tissue that is faster and more accurate than humans,&#8221; Holder, a co-corresponding author, said in the news release.<\/p>\n\n\n\n<p>Traditionally, analyzing tissue slides has been a painstaking process performed by teams of specially trained people. These experts meticulously examine and annotate the slides under a microscope, often spending hours on just one image to reduce human error.<\/p>\n\n\n\n<p>In the realm of epigenetics research, where Skinner&#8217;s team studies molecular processes influencing gene behavior without changing the DNA itself, such analysis can take a year or more for large studies. With the new AI model, the same data can be acquired within a few weeks.<\/p>\n\n\n\n<p>Deep learning is an advanced AI method that emulates the human brain\u2019s neural networks. Unlike traditional machine learning, which relies on predefined algorithms, deep learning adjusts its processes over time through a network of neurons and synapses. If the model makes an error, it &#8220;learns&#8221; from it using backpropagation, which fine-tunes the network to improve its performance.<\/p>\n\n\n\n<p>The WSU AI model is designed to handle high-resolution, gigapixel images, each containing billions of pixels. To manage these large files, the researchers configured the AI to analyze smaller, individual tiles while still considering their context within larger image sections, akin to zooming in and out on a microscope.<\/p>\n\n\n\n<p>Other researchers have already taken interest in this deep learning model. Holder\u2019s team is currently collaborating with WSU veterinary medicine researchers to diagnose diseases in deer and elk tissue samples.<\/p>\n\n\n\n<p>The implications of this technology extend beyond animal health. The AI model could significantly enhance human medical research and diagnostics, particularly for cancer and other gene-related diseases. <\/p>\n\n\n\n<p>According to Holder, as long as there is annotated data identifying diseases within tissue samples, the AI can be trained to perform those analyses.<\/p>\n\n\n\n<p>\u201cThe network that we\u2019ve designed is state-of-the-art,\u201d Holder added. \u201cWe did comparisons to several other systems and other data sets for this paper, and it beat them all.\u201d<\/p>\n\n\n\n<p><\/p>\n\n\n\n<p><a href=\"https:\/\/www.nature.com\/articles\/s41598-024-76807-x\" title=\"\">Published<\/a> in the journal Scientific Reports, this groundbreaking research outlines a bright future for integrating AI into medical diagnoses and research.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Researchers at Washington State University have developed a groundbreaking &#8220;deep learning&#8221; artificial intelligence model that can identify pathologies, or signs of disease, in animal and human tissue images much faster and often more accurately than human experts. This development holds the promise of revolutionizing both the pace of disease research and medical diagnostics. &#8220;This AI-based [&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],"tags":[],"class_list":["post-10594","post","type-post","status-publish","format-standard","hentry","category-ai"],"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":"Researchers at Washington State University have developed a groundbreaking &#8220;deep learning&#8221; artificial intelligence model that can identify pathologies, or signs of disease, in animal and human tissue images much faster and often more accurately than human experts. This development holds the promise of revolutionizing both the pace of disease research and medical diagnostics. &#8220;This AI-based&hellip;","_links":{"self":[{"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/posts\/10594","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=10594"}],"version-history":[{"count":8,"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/posts\/10594\/revisions"}],"predecessor-version":[{"id":10659,"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/posts\/10594\/revisions\/10659"}],"wp:attachment":[{"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/media?parent=10594"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/categories?post=10594"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.tun.com\/home\/wp-json\/wp\/v2\/tags?post=10594"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}